[HN Gopher] Mistral 7B ___________________________________________________________________ Mistral 7B Author : jasondavies Score : 673 points Date : 2023-09-27 14:52 UTC (8 hours ago) (HTM) web link (mistral.ai) (TXT) w3m dump (mistral.ai) | say_it_as_it_is wrote: | Will this run on my 486sx/16mhz w/8MB of ram? | speedgoose wrote: | If you have enough storage to use as swap, it should. | ComputerGuru wrote: | The announcement says a lot (and has plenty of numbers) but I | feel like the most important one is missing: how many GB of GPU | memory does this need, quantized and unquantized? | | (Searching tells me Llama2-7b unquantized needs close to 15GB; | presumably this is similar?) | brucethemoose2 wrote: | Llama 7B will squeeze on a 6GB GPU quantized. Maybe even less | with EX2 quantization. | | Foundational model trainers dont seem to worry about | quantization much, they just throw the base model out there and | then let the community take care of easing the runtime | requirements. | sp332 wrote: | One parameter is 16 bits == 2 bytes. So a model with 7 billion | parameters needs 14GB of RAM for the un-quantized model, plus | some overhead for the KV cache and other "working memory" stuff | but that should be fairly low for a 7B model. I expect it will | work on a 16GB GPU just fine. | | Quantized ones are also easy. 8 bits == 1 byte so that's 7GB | for the model. 4-bit gets you below 4GB. | semi-extrinsic wrote: | From the Mistral docs, it seems they need 24GB which is kind | of odd? | | https://docs.mistral.ai/llm/mistral-v0.1 | sp332 wrote: | Interesting, and that requirement is repeated on the cloud | deployment pages, even the unfinished ones where that is | the _only_ requirement listed so far. | https://docs.mistral.ai/category/cloud-deployment I wonder | if that sliding context window really blows up the RAM | usage or something. | sebzim4500 wrote: | Unless I've misunderstood something, the sliding context | window should decrease memory usage at inference compared | to normal flash attention. | lerela wrote: | We have clarified the documentation, sorry about the | confusion! 16GB should be enough but it requires some vLLM | cache tweaking that we still need to work on, so we put | 24GB to be safe. Other deployment methods and quantized | versions can definitely fit on 16GB! | brucethemoose2 wrote: | Shouldn't it be much less than 16GB with vLLM's 4-bit | AWQ? Probably consumer GPU-ish depending on the batch | size? | brucethemoose2 wrote: | Its not so straightforward, as theres some overhead aside | from the weights, especially with 7B at ~4 bit. | | But this is _probably_ capable of squeezing onto a 6GB (or | less?) GPU with the right backend. | tormeh wrote: | Not a big fan of how server-centric the LLM landscape is. I want | something that can run locally, and doesn't require any special | setup. One install + one model import maximum. Currently unless I | want to go clone git repos, install Python dependencies and buy | an Nvidia GPU I'm stuck waiting for it to become part of | https://webllm.mlc.ai/. That's a website, come to think of it, | but at least the computation happens locally with minimal fuss. | dwringer wrote: | You can get llama CPP or kobold.cpp binaries and load a | quantized model right into them on the CPU only, no need to | install Python or have an Nvidia GPU. | tormeh wrote: | Well, I'd like it to respond in something close to real-time, | and since I have a pretty good non-Nvidia GPU, it makes more | sense to wait for the WebGPU port. | programd wrote: | 7 tokens per sec on an i5-11400 CPU using llama.cpp - | that's pretty real time for personal use I would think. | winddude wrote: | Are you going to continue to train to a larger param size, say | 13b or 30b? | [deleted] | brucethemoose2 wrote: | There is definitely a demand for a 30B model (aka a model that | will comfortably fit on 24GB GPUs (or 32GB of system RAM) and | _squeeze_ into 16GB). | anish_m wrote: | What are the SOTA benchmarks for LLMs now? Love the progress on | opensource models, but would like to see an uncontaminated and | objective framework to evaluate them. | rgbrgb wrote: | This model runs in FreeChat for macOS [0] because it's supported | by llama.cpp :) | | You'll just need to download a nice GGUF here: | https://huggingface.co/TheBloke/Mistral-7B-v0.1-GGUF | | [0]: https://github.com/psugihara/FreeChat | local_crmdgeon wrote: | The video recording on the Readme is broken for me on FF/MacOS | rgbrgb wrote: | Thanks for letting me know! I think it broke when I made the | repo public this morning. Should be fixed now. | Patrick_Devine wrote: | also works w/ `ollama run mistral`. | stavros wrote: | Thanks for that, I didn't see it in the list and thought it | wouldn't be available to just run. | [deleted] | anonyfox wrote: | can it run on my macbook air locally yet, with acceptable | performance? Guess the answer is still no | fredoliveira wrote: | You'll be able to use it with llama.cpp soon [1], so, should | run fine on your macbook, yes. | | [1]: | https://github.com/ggerganov/llama.cpp/pull/3362#issuecommen... | anonyfox wrote: | that really was "soon", wow - already pulling it with ollama! | riedel wrote: | Can anyone provide details about the training of the model. What | data is it based on? Common Crawl? (Being a french company the | also rather focus on English language tasks) Where was it trained | and with how many resources? They mention Leonardo. I was in an | interesting meeting at the German Research Ministry last week | where people where complaining that the EuroHPC resources were | not sufficient atm to train decent LLMs. I guess the guys in the | end went also to CoreWeave in the US. | brucethemoose2 wrote: | > Inspecting the tokenizer model, there is evidence indicated a | training dataset of 8T tokens (/mnt/test/datasets/tokenizer_tra | ining/8T_train_data/shuffled.txt) | | https://github.com/ggerganov/llama.cpp/pull/3362#issuecommen... | pmarreck wrote: | `pip` is a horribly broken way to install more than 1 Python | package on a single Linux OS install and I sincerely wish the LLM | people would move away from it because I neither want to run | every new project in a Docker image, nor do I want to start a new | Nix project for every Python project I want to try out | RockRobotRock wrote: | Have you heard of virtual environments? | pmarreck wrote: | Have you ever googled "broken virtualenv"? Mine have broken | numerous times, including the problem where updating the | system breaks ALL of them. I know what you're going to say | next- "You're a technologist, you know how to fix it." True, | but I don't like wasted effort, even talented wasted effort | is still wasted effort. Meanwhile, Nix stuff _just works_ , | and I will never use another package manager ever again | (unless it is something that uses the core Nix idea, but | makes it easier!) | | https://www.google.com/search?q=broken+virtualenv | okwhateverdude wrote: | Yeah, gotta setup miniconda to keep things manageable. | Basically a generic virtual env manager that is trivial to use. | This way you can ensure each one of these LLM projects that | want different versions of different libs will get them without | stepping on each other or polluting your system. | pmarreck wrote: | I don't want to have to set up miniconda. I don't like | Python, I am not part of the Python ecosystem, and I don't | want to add a bunch of Python tools to my toolchain just to | run a friggin' LLM project. | | I'm not a C coder either, but I don't complain about those | projects because they're almost always "config; make; make | install". I basically want something like that, but for | Python. The nerd-tapdancing required here is ridiculous. | sp332 wrote: | Aside from the sliding attention window, I don't see them mention | any particular reasons for the incredible performance. I would | like to see some tests for benchmark contamination in the | training set. | brucethemoose2 wrote: | This ^ | | I am suspicious of contamination in every finetune I see, and | _very_ suspicious in a new foundational model like this. | | (For those reading and not following, "contamination" is | training a model/finetune on the very test it will be tested | on. Normally these known tests are specifically excluded from | training datasets so the models can be properly evaluated, but | throwing them in is an easy way to "cheat" and claim a model is | better than it is. | | In a foundational model with a huge dataset, there's also a | high probability that well-known evaluation questions snuck | into the dataset by accident). | londons_explore wrote: | Theres also a good chance that simply people discussing the | test questions and answers on forums like reddit sneaks into | the dataset, even if the exact question is filtered out. | Workaccount2 wrote: | We need an AI that can generate bespoke AI tests... | loudmax wrote: | Agreed. It's great that they're model available under a | permissive license. But without more information about the | training data and methodology, it isn't exactly "open source". | Tommstein wrote: | > But without more information about the training data and | methodology, it isn't exactly "open source". | | Being or not being open source has exactly jack shit to do | with that. | falcor84 wrote: | I actually would support that statement. An AI model is a | software artifact generated as part of a complex "build" | process. Without having access to the details of the | process that generated the artifact, including the training | data, it's no more open-source than a compiled binary. | capableweb wrote: | I'd argue that it goes against the intent of open source | very much. | | The idea behind OSS is that you're able to modify it | yourself and then use it again from that point. With | software, we enable this by making the source code public, | and include instructions for how to build/run the project. | Then I can achieve this. | | But with these "OSS" models, I cannot do this. I don't have | the training data and I don't have the training | workflow/setup they used for training the model. All they | give me is the model itself. | | Similar to how "You can't see the source but here is a | binary" wouldn't be called OSS, it feels slightly unfair to | call LLM models being distributed this way OSS. | computerex wrote: | Whilst not wrong, understand that having the weights be | released explicitly under Apache is a hell of a lot | better than the weights being released under a non open | source license and commercially friendly license. At | least people can legally use this for their solutions. | pk-protect-ai wrote: | They use some improvements on attention mechanisms. It is on | the main page ... That is why 7B model requires 24GB VRAM, | there might be increased amount of attention heads as well... | sp332 wrote: | They clarified https://news.ycombinator.com/item?id=37677311 | that it should only need 16GB, but the unoptimized runtime | currently takes 24. | rafaelero wrote: | Yeah, they should have mentioned details about the dataset. | iamcreasy wrote: | How difficult it is to fine tune model like this with specific | domain knowledge? I am currently looking into gpt-3.5-turbo- | instruct for this same purpose. | nabakin wrote: | They don't mention what datasets were used. I've come across too | many models in the past which gave amazing results because | benchmarks leaked into their training data. How are we supposed | to verify one of these HuggingFace datasets didn't leak the | benchmarks into the training data boosting their results? Did | they do any checking of their datasets for leaks? How are we | supposed to know this is a legit result? | | At this point, it should be standard practice to address this | concern. Any model which fails provide good evidence they don't | have benchmark leaks, should not be trusted until its datasets | can be verified, the methodology can be replicated, or a good, | independent, private benchmark can be made and can be used to | evaluate the model. | londons_explore wrote: | One solution is to come up with a new benchmark yourself. | | Manually benchmarking it by coming up with 20 questions and | feeding it to a pair of models and blindly choosing the best | result can give you a pretty good figure. | | And that can probably be done in under 20 mins of human time. | beernet wrote: | This is exceptionally meh. It reads like an excuse to investors. | | A free 7B model is great, however, the practical implications of | the potential adaptors are near 0. You must be crazy or have an | easy use case (that requires no LLM in the first place) if you | certainly believe that this model makes more sense per token | that, say, ChatGPT. | brucethemoose2 wrote: | Its extremely cheap to run locally or on a cheap cloud GPU, and | (if the claims are true) better than 3.5 Turbo with finetuning. | Its also unaligned. | all2 wrote: | For those running ollama, here's the ollama release for | Mistral-7B | | https://ollama.ai/library/mistral | wg0 wrote: | If I give you a binary (all binaries are numbers) but I don't | give you the source code and I say it is open source. Is it open | source? | | Also, I give you a model (all models are numbers) and I say it is | open source but I don't give you the program and data that | resulted in "compilation" of that model (numbers) so is it open | source? | | Wouldn't it be more of a new word - open use? | brucethemoose2 wrote: | The "source data" is allegedly 8 trillion tokens. You can't | just distribute that like its source code. | | The "binary" is the transformers python code, which in this | case is essentially llamav2. | | Now, the _documentation_ for this model is inexcusably poor. | Hot dropping random code on a git repo without one drop of | human language would be similarly "open source," but its bad | practice, and unfortunately this is the standard in AI Research | Land. | wg0 wrote: | Open source doesn't mean source code (or data) must accompany | the program as it is distributed but rather there should be a | way (CD ROM with a price tag or S3 bucket or torrent etc.) to | get access to it. | kpennell wrote: | sorry for the dumb question. Is there somewhere I can try it? | Like a chatbot? | brucethemoose2 wrote: | Huggingface Spaces. Be sure to get the prompting syntax right: | https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 | | I will try to host an instance on the AI Horde later today, | which has a better UI and doesn't need a login. | brucethemoose2 wrote: | OK I am hosting the instruct model on the horde now. I will | throw up the raw base model too: | | https://lite.koboldai.net/# | | Note that you must switch to instruct mode in the UI, and use | the "LLama 2 chat" preset, but you also need a <s> token in | the instruction (memory) tab: | | https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1#in. | .. | jxy wrote: | ehhh, the design of the webpage infuriates me. Who thought | sprinkling faint dots swimming across the webpage was a good | thing? I almost thought something's wrong with my eyes or my | display! | BrutalCoding wrote: | Fully agree. I was thinking that there was a tiny fruit fly | crawling over the screen for a good few seconds. | covi wrote: | Cloud deployment docs: https://docs.mistral.ai/cloud- | deployment/skypilot/ | slim wrote: | they should've called it winamp | Ataraxy wrote: | ...because it whips the llama's ass. | spiderfarmer wrote: | And adopt a real llama as a mascot, just like Justin Frankel. | jesperwe wrote: | I see what you did there :-D | code51 wrote: | Correctly lists US presidents in chronological order (which is an | important test to me). | | However for "List Led Zeppelin albums in chronological order"... | | Here is a list of Led Zeppelin albums in chronological order: 1. | Led Zeppelin (1968) 2. Led Zeppelin II (1969) 3. Led Zeppelin III | (1970) 4. Led Zeppelin IV (1971) 5. Houses of the Holy (1973) 6. | Physical Graffiti (1975) 7. Presence (1976) 8. In Through the Out | Door (1979) 9. Cymbals and Wine (1980) | | It's missing "The Song Remains the Same", weird but important. | | GPT-4 is also missing it: 1. Led Zeppelin (1969) 2. Led Zeppelin | II (1969) 3. Led Zeppelin III (1970) 4. Led Zeppelin IV (1971) 5. | Houses of the Holy (1973) 6. Physical Graffiti (1975) 7. Presence | (1976) 8. In Through the Out Door (1979) 9. Coda (1982) | | "The Song Remains the Same" is a live album of the "concert | film". Both GPT-4 and Mistral don't seem to treat it as _also_ an | album. | | When asked as a follow-up, GPT-4 says: | | ""The Song Remains the Same" is a live album and soundtrack by | Led Zeppelin, released in 1976. The list you asked for was | comprised of their studio albums only." (note that I didn't | specifically say _studio albums only_ ) | | Mistral says something else: | | "The Song Remains the Same was released as a single in 1976, not | as an album. As a result, it is not included in the list of Led | Zeppelin albums in chronological order." | | Same behavior, different explanation. | | Interesting to see alignment is this hard, even in basic stuff. | sacnoradhq wrote: | MS Copilot is apparently a music fan. | | Most LLMs have problems with subtly, such as compound anagrams | tend to repeat the same words in reverse order rather than | reversing all of the letters in all words. | sireat wrote: | One should be able to run Mistral 7B locally on something as low | as 1070 8GB would they not? | | That is assuming 8bit weights. | | I have not kept up with local LLM news. I assume the steps needed | would be somewhat similar to | https://followfoxai.substack.com/p/how-to-run-llama-in-an-ol... | which is from April 2023. | brucethemoose2 wrote: | Its already kind of outdated, lol. | | The backends de joure are either llama.cpp frontends (I use | Kobold.cpp at the moment) or oobabooga as the guide specifies, | but with the exLlamav2 backend. | | If you are serving a bunch of people, run a vLLM backend | instead since it supports batching, and host it on the Horde if | you are feeling super nice: https://lite.koboldai.net/# | | Technically only vLLM will work with this new model at the | moment, but I'm sure cpp/ooba support will be added within | days. | | This comment will probably be obsolete within a month, when | llama.cpp gets batching, MLC gets a better frontend, or some | other breakthrough happens :P | sp332 wrote: | llama.cpp support is here already via | https://huggingface.co/TheBloke/Mistral-7B-v0.1-GGUF And yes | it works fine in oobabooga. | burningion wrote: | For anyone who missed it, the twitter announcement of the model | was just a torrent tracker uri: | https://twitter.com/MistralAI/status/1706877320844509405 | brucethemoose2 wrote: | I have thrown the base+instruct models up on AI Horde, you can | try it with no login: | | https://lite.koboldai.net/# | sharperguy wrote: | Is there a plugin for vim, or other code editors that allows such | an LLM to function similarly to copilot? | brucethemoose2 wrote: | https://dev.to/chenhunghan/use-code-llama-and-other-open-llm... | | Many LLM frameworks implement the OpenAI API, so if you can get | that into your code editor and change the address, you can run | it with any LLM you want. | | Doing it _smoothly_ is another matter. | swaroop wrote: | Try https://github.com/huggingface/llm.nvim (no affiliation) | tikkun wrote: | Regular reminder that most LLM benchmarks are pretty terrible. | I've looked inside the datasets and it's not stuff that I'd want | to dictate what determines which models are best! | cosmojg wrote: | In my experience, HellaSwag seems to correlate highly enough | with model performance for my use case (i.e., complex | autocompletion of prose and code rather than rather than | glorified chatbotting). MMLU and ARC aren't too bad, but | TruthfulQA can sometimes be a straight-up countersignal. | anonyfox wrote: | I eat my initial words, this works really well on my macbook air | M1 and feels comparable of GPT3.5 - which is actually an amazing | feat! | | Question: is there something like this, but with the "function | calling api" finetuning? 95% of my uses nowadays deal with | input/output of structured data (JSON, basically), and I kind of | fear that OpenAI will no longer support thos specialized models | after a few months... I know its probably not that glorious | compared with multimodal chat UIs, but a workhose like nothing | else for automation! | Karrot_Kream wrote: | How many tokens / sec are you getting on an M1 Air? Curious | since I'm at work and can't try this on my Air yet hah. | Patrick_Devine wrote: | I'm getting >30 tokens/sec using it with ollama and an M2 | Pro. That might be a little slow though because I have a | background finetuning job running. | minzi wrote: | Bit of a tangential question here, but any recommendations | on how to get started fine tuning this model (or ones like | it)? I feel like there are a million different tutorial and | ways of doing it when I google. | anonyfox wrote: | feels roughly like the same speed as GPT3.5 in the browser UI | brucethemoose2 wrote: | Its the same speed as llama 7B, so very quick. | brucethemoose2 wrote: | Yes! | | https://github.com/ggerganov/llama.cpp/blob/master/grammars/... | | Its actually better than a specialized model, during token | generation it constrains the possible output tokens to an | arbitrary grammar (like, say, JSON syntax). So it will work | "perfectly" with any model with a basic understanding of the | format. | | Kobold.cpp and text-generation-ui already support this, and | both will run on your mac. | olso wrote: | Hey, how did you try it on M1? I don't see any MPS support. | | https://github.com/mistralai/mistral-src/issues/2 | | edit: nevermind https://ollama.ai | anonyfox wrote: | `ollama run mistral` <-- literally thats it | Dwedit wrote: | Someone get that stupid animated background off the site, it | looks like bugs crawling on the screen. | MadDemon wrote: | I was thinking the same thing | eminence32 wrote: | I've never run one of these models locally, but their README has | some pretty easy to follow instructions, so I tried it out... | | > RuntimeError: Found no NVIDIA driver on your system. | | It's true that I don't have an NVIDIA GPU in this system. But I | have 64GB of memory and 32 cpu cores. Are these useless for | running these types of large language models? I don't need | blazing fast speed, I just need a few tokens a second to test- | drive the model. | lhl wrote: | Use the code/model included here: | https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 | | Change the initial device line from "cuda" to "cpu" and it'll | run. | | (Edit: just a note, use the main/head version of transformers | which has merged Mistral support. Also saw TheBloke uploaded a | GGUF and just confirmed that latest llama.cpp works w/ it.) | avereveard wrote: | it's not entirely their fault, they rely on xformers, and that | library is gpu only. | | other models will happily run on cpu only mode, depending on | your environment there are super easy ways to get started, and | 32 core should be ok for a llama2 13b and bearable with some | patient for running 33b models. for reference I'm willingly | running 13b llama2 on cpu only mode so I can leave the gpu to | diffusers, and it's just enough to be generating at a | comfortable reading speed. | kardianos wrote: | Use llama.cpp to run models locally. | turnsout wrote: | Can llama.cpp run this yet? That would be surprising | daakus wrote: | It can! TheBloke is to thank for the incredibly quick | turnaround. | | https://github.com/ggerganov/llama.cpp/pull/3362 | | https://huggingface.co/TheBloke/Mistral-7B-v0.1-GGUF/tree/m | a... | turnsout wrote: | Wow, awesome! | aidenn0 wrote: | I have yet to get any useful output out of the Q5_K_S | version; haven't tried any others yet. | moffkalast wrote: | Birds fly, sun shines, and TheBloke always delivers. | | Though I can't figure out that prompt and with LLama2's | template it's... weird. Responds half in Korean and does | unnecessary numbering of paragraphs. | | Just one big _sigh_ towards those supposed efforts on | prompt template standardization. Every single model just | has to do something unique that breaks all compatibility | but has never resulted in any performance gain. | programd wrote: | I'm getting about 7 tokens per sec for Mistral with the | Q6_K on a bog standard Intel i5-11400 desktop with 32G of | memory and no discrete GPU (the CPU has Intel UHD Graphics | 730 built in). | | So great performance on a cheap CPU from 2 years ago which | costs, what $130 or so? | | I tried Llama.65B on the same hardware and it was way | slower, but it worked fine. Took about 10 minutes to output | some cooking recipe. | | I think people way overestimate the need for expensive GPUs | to run these models at home. | | I haven't tried fine tuning, but I suspect instead of 30 | hours on high end GPUs you can probably get away with fine | tuning in what, about a week? two weeks? just on a | comparable CPU. Has anybody actually run that experiment? | | Basically any kid with an old rig can roll their own | customized model given a bit of time. So much for | alignment. | loudmax wrote: | It would be very surprising. | | Mistral AI's github page has more information on their | sliding window attention method to achieve this | performance: https://github.com/mistralai/mistral-src | | If Mistral 7b lives up to the claims, I expect these | techniques will make their way into llama.cpp. But I would | be surprised if the required updates were quick or easy. | polygamous_bat wrote: | You gotta wait until GGML and the likes repackage the model; | early releases are almost always targeted at ML folks with | dedicated GPUs. | londons_explore wrote: | I think it's really lame that ML, which is just math really, | hasn't got some system-agnostic language to define what math | needs to be done, and then it can run easily on | CPU/GPU/TPU/whatever... | | A whole industry being locked into NVidia seems bad all | round. | esafak wrote: | It's not Nvidia's fault that the competition (AMD) does not | provide the right software. There is an open alternative to | CUDA called OpenCL. | tormeh wrote: | As sad as it is, this is true. AMD has never spent lots | of money on software, while Nvidia always has, which was | fine for traditional graphics, but with ML this really | doesn't cut it. AMD could have ported Pytorch to OpenCL | or Vulkan or WebGPU, but they just... can't be | bothered??? | londons_explore wrote: | Nvidia has wrapped their cuda language in patents and | licensing so tightly that there is no way AMD could | release anything cuda-compatible. | kkielhofner wrote: | Yes but AMD could release a ROCm that actually works and | then put actually meaningful resources into some of the | countless untold projects out there that have been | successfully building on CUDA for 15 years. | | There was a recent announcement that after six years AMD | finally sees the $$$ and will be starting to (finally) | put some real effort into ROCm[0]. That announcement was | two days ago and they claim they started on this last | year. My occasional experience with ROCm doesn't show | much progress or promise. | | I'm all for viable Nvidia competition in the space but | AMD has really, really, really dropped the ball on GPGPU | with their hardware up to this point. | | [0] - https://www.eetimes.com/rocm-is-amds-no-1-priority- | exec-says... | miloignis wrote: | https://onnx.ai/ sounds close to what you're thinking of, | it's an open interchange format. | pugio wrote: | How come the blog post doesn't discuss training at all? Which | data sets were used? How many tokens was it trained on? I | couldn't seem to find a linked preprint or anything else really | aubanel wrote: | Congrats to them, their huge series A (USD113M) does not seem | oversized anymore! | mchiang wrote: | This model will run on Ollama, llama.cpp, and other tools: | | ollama run mistral | | or for llama.cpp, thebloke has uploaded the GGUF models here: | https://huggingface.co/TheBloke/Mistral-7B-v0.1-GGUF/tree/ma... | and you can run it | | really looking forward to the chat fine-tuned models that doesn't | seem to be available yet. | brucethemoose2 wrote: | Oh, that means its a llama architecture model! | | Is the tokenizer the same? It may "work" without actually | working optimally until llama.cpp patches it in. | | And the instruct model was just uploaded. | todd3834 wrote: | This is my hello world test for coding assistant for LLMs. | CodeLlama and GPT4 crush the answer. I love seeing innovation in | the space but Mistral kind of failed me on my first test: | | --------------------- | | >>> Write code that will track swipes in Typescript | | . Swipe should be detected when the user moves a finger over 30% | of the screen, and then drags it all the way to the end of the | screen. | | ## Getting started You need to have yarn or npm installed before | you can run this app | | ### Running in browser ```bash yarn install yarn serve ``` | | ### Running with docker Use the docker-compose file located at | ./docker/docker-compose.yml ```bash cd <path-to-project> docker- | compose up ``` | | ## Screenshot ![Screenshot](./images/screenshot.png) | amilios wrote: | Not a fair comparison as Mistral is not instruction tuned. You | need to write a "continuation-style" prompt or few-shot it, | rather than just giving it a direct order. Honestly this is one | of the reasons imo that Mistral won't see wide acceptance, | LLaMA-2-7b-chat is RLHF and instruction tuned and is just so | much easier to use as a result. | code51 wrote: | What about this one? | | https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 | black_puppydog wrote: | You didn't enjoy the screenshot? :) | code51 wrote: | Here is the response from Instruct model: | https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 | | To track swipes in TypeScript, we can use a library like | `react-native-gesture-handler`. Here's an example of how to use | it to track horizontal and vertical swipes: | | ```typescript | | import React from 'react'; import { GestureHandlerEvent, | GestureHandlerProps } from 'react-native-gesture-handler'; | | const SwipeableContent: React.FC<GestureHandlerProps> = ({ | onStart, onEnd, onMove }) => { const handleHorizontalSwipe = | (event: GestureHandlerEvent) => { if (event.type === | 'horizontal') { onStart(event); } else { onEnd(event); } }; | const handleVerticalSwipe = (event: GestureHandlerEvent) => { | if (event.type === 'vertical') { onStart(event); | } else { onEnd(event); } }; | return ( <View> <PanGestureHandler | onStart={handleHorizontalSwipe} onMove={onMove}> | <Text>Drag me horizontally</Text> | </PanGestureHandler> <PanGestureHandler | onStart={handleVerticalSwipe} onMove={onMove}> | <Text>Drag me vertically</Text> </PanGestureHandler> | </View> ); | | }; | | ``` In this example, we use the `PanGestureHandler` component | from `react-native-gesture-handler` to track horizontal and | vertical swipes. The `onStart`, `onEnd`, and `onMove` props are | passed to the `PanGestureHandler` component to handle the | different types of gestures. | | You can then use this component in your app to track swipes on | any view: | | ```typescript | | const App = () => { const [isHorizontalSwiping, | setIsHorizontalSwiping] = useState(false); const | [isVerticalSwiping, setIsVerticalSwiping] = useState(false); | const handleStart = (event: GestureHandlerEvent) => { | if (event.type === 'horizontal') { | setIsHorizontalSwiping(true); } else { | setIsVerticalSwiping(true); } }; const | handleEnd = (event: GestureHandlerEvent) => { if | (event.type === 'horizontal') { | setIsHorizontalSwiping(false); } else { | setIsVerticalSwiping(false); } }; | const handleMove = (event: GestureHandlerEvent) => { | console.log('Gesture moved'); }; return ( | <View> <SwipeableContent onStart={handleStart} | onEnd={handleEnd} onMove={handleMove} /> | <Text>{isHorizontalSwiping ? 'Horizontal swipe is in progress' | : ''}</Text> <Text>{isVerticalSwiping ? 'Vertical | swipe is in progress' : ''}</Text> </View> ); | | }; ``` | | In this example, we use the `SwipeableContent` component to | track horizontal and vertical swipes. We also track the status | of the swipe using state variables to show a message when a | swipe is in progress. | capableweb wrote: | CodeLlama is obviously trained on code specifically, so maybe | not a useful comparison. GPT4 is also way different than | Mistral, with a huge step up in parameters and seems to be | using multi-agent approach too. | | Since Mistral is just a 7B parameter model, it's obvious that | you won't be able to have it straight up write accurate code, | it's simply too small for being able to accomplish something | like that, unless you train the model specifically for writing | code up front. | | I guess if all you're looking for is a model to write code for | you, that makes sense as a "hello world" test, but then you're | looking at the wrong model here. | | What you really want to do if you're looking for a good | generalized model, is to run a bunch of different tests against | it, from different authors, average/aggregate a score based on | those and then rank all the models based on this score. | | Luckily, huggingface already put this all in place, and can be | seen here: | https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderb... | | This Mistral 7B model seems to earn itself a 3rd place compared | to the rest of the 7B models added to the leaderboard. | | Edit: As mentioned by another commentator, this also seems to | be a base model, not trained specifically for | request<>reply/chat/instructions. They're (or someone) is meant | to fine-tune this model for that, if they want to. | qeternity wrote: | > and seems to be using multi-agent approach too. | | What do you mean by this? MoE? | pclmulqdq wrote: | I'm pretty sure this model is not instruct tuned, so it's not | exactly apples-to-apples. | slimsag wrote: | Major kudos to Mistral for being the first company to Apache | license a model of this class. | | Meta wouldn't make LLama open source. | | DeciLM wouldn't make theirs open source. | | All of them wanted to claim they were open source, while putting | in place restrictions and not using an open source license. So I | think it's worth giving Mistral big kudos here for actually doing | it and going Apache licensed. | miloignis wrote: | Falcon 40B is Apache2, though they then went back to not open | for their 180B. | divbzero wrote: | MPT-30B is also Apache 2.0: | https://huggingface.co/mosaicml/mpt-30b | | There must be others as well? | capableweb wrote: | A lot! Go here https://huggingface.co/spaces/HuggingFaceH4/ | open_llm_leaderb..., check "Hub license" on the left then | sort by that column in the table. | | Estimating, there is more than 100 models with a apache-2.0 | license. | avereveard wrote: | a good chunk are "only the lora is apache 2 the base | model is lama" or straight up llama2 model finetuned and | distributed laundring their license, or use gpt generated | code in the finetuning dataset against OpenAI tos. | licensing is a bit up in the air and just filtering with | apache 2 doesn't tell you much | monocasa wrote: | I'm really not a fan of how these releases of model binaries | are being referred to as open source. How do I make changes to | this model? How do I integrate changes to this model that | others have made? | | The data pipeline is the source here. Just because it's not | locked behind a SaaS veneer doesn't make it open source any | more than Windows is. | hcks wrote: | This fallacious talking point is getting annoying. | [deleted] | LoganDark wrote: | Windows is not open source. In order to access the source | code, you need a government contract. These aren't given out | lightly. | piperswe wrote: | Right, that's the point they're making. | LoganDark wrote: | Recent models may not be fully open source, but could you | point me to one that's subject to the same amount of | scrutiny as Windows source code access? Because I'm not | sure if there is one out there. | monocasa wrote: | Windows source access is given out pretty freely to | academics as the Windows Research Kernel (WRK). | | But the point is that the data pipeline and tensorflow or | what have you that trained the model is the source here. | The model is the binary. | spullara wrote: | Most partners can get a copy of the Windows source code if | they need it. | | https://www.microsoft.com/en-us/sharedsource/ | squeaky-clean wrote: | You can do your own fine tuning on existing models | | > How do I integrate changes to this model that others have | made | | Typically with a LoRA | monocasa wrote: | Is that how the engineers at Mistral iterated on this | model? | | I can patch windows and other binaries too (I'm actually | pretty decent at that; 20 or so years with IDA/ghidra). | That doesn't make them open source. | brucethemoose2 wrote: | They trained it from scratch, but there is nothing | stopping you from doing some more training on top of it | yourself. Nothing is obfuscated, no more information is | required beyond the prompting syntax... they just | released basically no documentation, which is | unfortunately kinda standard in AI land. | | There is already a sizable ecosystem of people doing just | that: | https://huggingface.co/models?sort=modified&search=7B | monocasa wrote: | Just like Microsoft isn't stopping me from patching | Windows. | | > Nothing is obfuscated | | The dataset and pipeline to rebuild these weights are not | included. | pk-protect-ai wrote: | Have you tried the HF version which is linked on the main | page? It is transformer based after all and it is | converted to HF format. Just use QLoRA to fine-tune | whatever you want on the top of that model. They handed | you hundreds of GPU hours, without asking anything in | return. You may throw it away and train the model from | scratch. Be ready to throw $70k-$150k into air warming. | monocasa wrote: | > Have you tried the HF version which is linked on the | main page? It is transformer based after all and it is | converted to HF format. Just use QLoRA to fine-tune | whatever you want on the top of that model. | | Is that how their engineers built this model in the first | place? | | Just because they're giving the build artifact of there | hard work away doesn't make it open source. | | > Be ready to throw $70k-$150k into air warming. | | Just because builds are expensive, doesn't mean releasing | the build artifacts counts as open source. | pk-protect-ai wrote: | I see dozens of your posts here complaining about "not | open source." You are either a paid provocateur or a | troll. What exactly is missing in your opinion in this | release that is making this model not open source? | [feeding trolls is fun] | monocasa wrote: | > I see dozens of your posts here complaining about "not | open source." You are either a paid provocateur or a | troll. | | I can't reply in my one tree without being called a | troll? | | Also, accusing someone of being a paid provocateur is | against HN guidelines. | | > What exactly is missing in your opinion in this release | that is making this model not open source? | | The source the engineers at Mistral used to build it. | brucethemoose2 wrote: | > The dataset and pipeline to rebuild these weights are | not included. | | This is a good point. | | But its probably not deterministic and reproducible. I | bet the researchers themselves couldn't remake the exact | weights (or even similar weights) from scratch. | Scene_Cast2 wrote: | Yep. Even if the initial seed for parameter init, the | example shuffling seed, etc were constant, the | distributed nature of training (and syncing the model | across machines) would kill reproducibility. Not to | mention resuming from checkpoints after gradient | explosions, etc. | monocasa wrote: | I've heard from ML engineers at larger shops that | reproducibility is key to working at scale. That's how | you track down "this training regime went to shit because | of something we changed" versus "this training regime | went to shit because on of the GPUs training it is | starting to fail". | monocasa wrote: | I mean most binaries aren't reproducible. That takes a | lot of work and isn't worth it most of the time. | | However, I've heard from ML engineers at the big shops | that hermetic, reproducible builds are key to making any | progress at scale with ML. Apparently that goes all the | way back to when Jeff Dean took over Google Brain. | HanClinto wrote: | Is "Doom" open source? | | The source code to the engine is available and open, but | if you want to do anything useful or recreate the | original game, you have to provide your own data. | | This model is open source, much in a similar way that the | Doom engine is open source. | monocasa wrote: | > Is "Doom" open source? | | > The source code to the engine is available and open, | but if you want to do anything useful or recreate the | original game, you have to provide your own data. | | The Doom executable is open source. The data is not. | Explicitly, the data is under a different license than | the GPL and makes no claims about being open source. | There are total conversion mods that replace the closed | source levels with open source ones however. | | > This model is open source, much in a similar way that | the Doom engine is open source. | | Here's the source the engineers that created doom used to | build the doom engine: https://github.com/id- | Software/DOOM | | Where is the source used to build this model? | spullara wrote: | You don't iterate on the model weights, you train them on | billions of tokens. There was no real iteration, you set | it up and wait for the GPUs to do the work. The model | architecture itself is done before you start training. If | you change it, you generally have to start training from | scratch. | | You do get the ability to further train the model using | fine-tuning or LoRas. | monocasa wrote: | There's absolutely state space iteration in model | training. Layer sizes, composition, construction. | | > There was no real iteration, you set it up and wait for | the GPUs to do the work. The model architecture itself is | done before you start training. If you change it, you | generally have to start training from scratch. | | That's like saying there's no design iteration in | software because you type 'make' and the executable is | built. | gfodor wrote: | Sounds false, this is only an analogy wrapped up in what | sounds like an argument. If you think about what you're | actually getting it's open source. | monocasa wrote: | What do Mistral's engineers work with? Do they have this | 14GB pickle file open in their IDEs at 3PM? If not, why is | that not the source to this? | scosman wrote: | You could fine tune and release that. It's not software so | exact parallels don't make sense, but the open permissions | are great. | monocasa wrote: | I mean, it's absolutely software. | scosman wrote: | Software is used to make models, but the models aren't | software anymore than Toy Story is software. | mbakke wrote: | Forgive my ignorance, I haven't studied the AI tooling | landscape yet. Are you saying these models have a | structured binary format and "running" them is just a | matter of having a "player" with the right "codec"? | | Or are they directly executing CPU instructions? | monocasa wrote: | There's literally a list of opcodes to be executed in the | model. There's a whole lot of data too, but that's part | of the build just as much as anything in a .data section. | godelski wrote: | > these releases of model binaries | | Are they binaries? I haven't seen a binary in awhile tbh. | Usually they're releasing both the raw architecture (i.e. | code) and the weights of the models (i.e. what numbers go | into what parts of the architecture). The latter is in a | readable format that you can generally edit by hand if you | wanted to. But even if it was a binary as long as you have | the architecture you can always load into the model and | decide if you want to probe it (extract values) or modify it | by tuning (many methods to do this). | | As far as I'm concerned, realistically the only issue here is | the standard issue around the open source definition. Does it | mean the source is open as available or open as "do what the | fuck you want"? I mean it's not like OpenAI is claiming that | GPT is open sourced. It's just that Meta did and their source | is definitely visible. Fwiw, they are the only major company | to do so. Google doesn't open source: they, like OpenAI, use | private datasets and private models. I'm more upset at | __Open__AI and Google than I am about Meta. To me people are | barking up the wrong tree here. (It also feels weird that | Meta is the "good guy" here... relatively at least) | | Edit: I downloaded their checkpoint. It is the standard "pth" | file. This is perfectly readable, it is just a pickle file. I | like to use graftr to view checkpoints, but other tools exist | (https://github.com/lmnt-com/graftr) | GuB-42 wrote: | > The "source code" for a work means the preferred form of | the work for making modifications to it. | | That's the definition in the GPL. That it is text or binary | doesn't matter. | | So are the weights the preferred form for making | modifications? Partly yes, because of fine tuning, but also | no, because you are limited in what you can do with fine | tuning. If Mistral had to make major changes to their | model, they would probably start with the dataset and code | they have but you don't, the one that created the weights | file. | | So I wouldn't call it "open source", just "open". You can | do whatever you want with what you have, but you don't have | the same abilities as Mistral to modify the model because | you lack some data. | | Still, it is a bit of an unusual situation since even with | the "real sources", i.e. training data and code, most | people wouldn't have the resources to retrain the model, | and a big part of the value in these models is the | computing resources that were invested in training them. | monocasa wrote: | First off tokenizer.model in their release is absolutely a | binary by any definition. | | Secondly, is hand editing the pickle file the way Mistral's | engineers constructed this pickle file? Why not? The | automation that constructed that file (and tokenizer.model) | is the source. Binaries in this context can certainly be an | ASCII encoded file. | | Just because other vendors are worse doesn't make this open | source. | syntaxing wrote: | Not OP but I don't get it though, you can modify the | tokenizer all you want and fine tune the weights all you | want. There's nothing inherently hidden behind a binary | monocasa wrote: | I can edit binaries too. | | The question is am I provided the build source that | constructed these files. Mistral did not hand edit these | files to construct them, there's source out there that | built them. | | Like, come on, a 14GB of a dump of mainly numbers that | were constructed algorithmically are not "source". | spywaregorilla wrote: | The whole point of machine learning is deriving an | algorithm from data. This is the algorithm they derived. | It's open source. You can use it or change it. Having the | data that was used to derive it is not relevant. | monocasa wrote: | > It's open source. | | How did the engineers who built it do so? Is there more | source to create this build artifact? | syntaxing wrote: | But the source to train your own LLM equivalent is also | released though (minus the data). Hence why there are so | many variants of LLaMa. You also can't fine tune it | without the original model structure. The weights give | the community a starting point so they don't need | literally millions of dollar worth of compute power to | get to the same step. | monocasa wrote: | Would Mistral's engineers be satisfied with the release | if they had to rebuild from scratch? | syntaxing wrote: | But they built a llama equivalent + some enhancements | that gives better performance...I'm not sure if this | would be possible at all without Meta releasing all the | required code and paper for LLaMa to begin with. | monocasa wrote: | Meta didn't release all of the required code to build | LLaMa, just enough run inference with their weights. | cfuendev wrote: | We should push for GPL licensing then, which AFAIK | requires a source that can be built from. | monocasa wrote: | We just also shouldn't call releases with no source "open | source". | | I wouldn't really have a complaint with their source | being released as Apache 2. I just don't want the term | "open source" diluted to including just a release of | build artifacts. | gary_0 wrote: | I could kind of see things either way. Is this like not | providing the source code, or is it like not providing | the IDE, debugger, compiler, and linter that was used to | write the source code? (Also, it feels a bit "looking a | gift horse in the mouth" to criticize people who are | giving away a cutting-edge model that can be used | freely.) | godelski wrote: | I'd actually say that including the training data would | be like providing the IDE/debugger/compiler rather than | the model/checkpoint being analogous. If I hand you | Signal's source code you can run it, use it, modify it, | etc. All similar characteristics to what is provided | here. What they didn't provide to us is how they created | that code. You couldn't create that software from scratch | by just having these and that's true for any open source | project. But I wouldn't say training data is as good as | an analogy to peering in the minds of engineers, because | it is an important part to getting the final product and | analyzing it. | monocasa wrote: | > I could kind of see things either way. Is this like not | providing the source code, or is it like not providing | the IDE, debugger, compiler, and linter that was used to | write the source code? | | Do the engineers that made this hand edit this file? Or | did they have other source that they used and this is the | build product? | | > (Also, it feels a bit "looking a gift horse in the | mouth" to criticize people who are giving away a cutting- | edge model that can be used freely.) | | Windows was free for a year. Did that make it open | source? | godelski wrote: | > Do the engineers that made this hand edit this file? Or | did they have other source that they used and this is the | build product? | | Do any open source product provide all the tools used to | make software? I haven't seen the linux kernel included | in any other open source product and that'd quite frankly | be insane. As well as including vim/emacs, gcc, gdb, X11, | etc. | | But I do agree that training data is more important than | those things. But you need to be clear about that because | people aren't understanding what you're getting at. Don't | get mad, refine your communication. | | > Windows was free for a year. Did that make it open | source? | | Windows didn't attach an Apache-2.0 license to it. This | license makes this version of the code perpetually open | source. They can change the license later, but it will | not back apply to previous versions. Sorry, but this is | just a terrible comparison. Free isn't what makes a thing | "open source." Which let's be clear, is a fuzzy | definition too. | monocasa wrote: | What I'm asking for is pretty clear. The snapshot of code | and data the engineers have checked into their repos | (including data repositories) that were processed into | this binary release. | | > This license makes this version of the code perpetually | open source. | | It doesn't because they didn't release the source. | | There's nothing stopping me from attaching an Apache 2 | license to a shared library I never give the source out | to. That also would not be an open source release. There | has to be actual source involved. | lmm wrote: | > Do any open source product provide all the tools used | to make software? I haven't seen the linux kernel | included in any other open source product and that'd | quite frankly be insane. As well as including vim/emacs, | gcc, gdb, X11, etc. | | BSD traditionally comes as a full set of source for the | whole OS, it's hardly insane. | | But the point is you don't need those things to work on | Linux - you can use your own preferred editor, compiler, | debugger, ... - and you can work on things that aren't | Linux with those things. Calling something "open source" | if you can only work on it with proprietary tools would | be very dubious (admittedly some people do), and calling | a project open source when the missing piece you need to | work on it is not a general-purpose tool at all but a | component that's only used for building this project is | an outright falsehood. | idonotknowwhy wrote: | What about this project? | | https://github.com/MiSTer-devel/PSX_MiSTer | | Only one man in the world of capable of creating or | editing this code, not it's here. | | Is it really open source of Robert doesn't provide his | brain too? | monocasa wrote: | I'm not asking for the engineers brains, I'm asking for | more or less what's sitting in the IDE as they work on | the project. | | Robert has provided that there. Mistral has not. | | As an aside, I'm more than capable of editing that code; | I've professionally worked on FPGA code and have written | a PS1 emulator. Taking that (wonderful looking code) and | say, fixing a bug, adding a different interface for the | cdrom, porting it to a new FPGA are all things I'm more | than capable of. | gary_0 wrote: | No, but if the Windows binary code was made available | with no restrictive licensing, I'd be quite happy, and | the WINE devs would be ecstatic. Sure, the source code | and build infrastructure would be nicer, but we could | still work with that. | monocasa wrote: | 'gary_0' being happy with the license terms isn't what | defines 'open source'. | | I'm fairly happy with the license terms too. They're just | not open source. We dilute the term open source for the | worst if we allow it to apply to build artifacts for some | reason. | gary_0 wrote: | We were talking about "looking a gift horse in the | mouth", as in it's still a positive thing regardless of | the semantic quibbles about open source. Nobody would | argue that a hypothetical openly licensed Windows binary- | only release is "open source" and I'd appreciate it if | you read my comments more charitably in future. | | Source code licenses are naturally quite clear about what | constitutes "source code", but things are murkier when it | comes to ML models, training data, and associated | software infrastructure, which brings up some interesting | questions. | monocasa wrote: | > We were talking about "looking a gift horse in the | mouth", as in it's still a positive thing regardless of | the semantic quibbles about open source | | Your gift horse in the mouth comment was visibly an aside | in the greater discussion being enclosed in parenthesis. | | > Nobody would argue that a hypothetical openly licensed | Windows binary-only release is "open source" and I'd | appreciate it if you read my comments more charitably in | future. | | That's why I'm using it as an example metaphor in my | favor. It's clearly not open source even if they released | it under Apache 2. It's not what their engineers edit | before building it. | | > Source code licenses are naturally quite clear about | what constitutes "source code", but things are murkier | when it comes to ML models, training data, and associated | software infrastructure, which brings up some interesting | questions. | | I don't think they're all that murky here. The generally | accepted definition being | | > The "source code" for a work means the preferred form | of the work for making modifications to it. "Object code" | means any non-source form of a work. | | Is this the form of the work that Mistral's engineers | work in? Or is there another form of the work that they | do their job in and used to build these set of files that | they're releasing? | lawlessone wrote: | You're asking them to release all their training data? | very unlikely that's going to happen. | monocasa wrote: | There's a lot of reasons why an org wouldn't want to open | source their release. That doesn't make it open source. | ben_w wrote: | > Like, come on, a 14GB of a dump of mainly numbers that | were constructed algorithmically are not "source". | | So if I take a photo of a pretty sunset, release it under | MIT license, you'd say it's "not open source" unless I | give you the sun and the atmosphere themselves? | | These models are perfectly valid things in their own | right; the can be fine-tuned or used as parts of other | things. | | For most of these LLMs (not sure about this one in | particular yet) the energy cost in particular of | recreation is more than most individuals earn in a | lifetime, and the enormous data volume is such that the | only people who seriously need this should be copyright | lawyers and they should be asking for it to be delivered | by station wagon. | monocasa wrote: | I said "constructed algorithmically". Ie. I expect source | to be at the level the engineers who built it generally | worked at. | | It's very nice that they released their build artifacts. | It's great that you can take that and make small | modifications to it. That doesn't make it open source. | | > For most of these LLMs (not sure about this one in | particular yet) the energy cost in particular of | recreation is more than most individuals earn in a | lifetime, and the enormous data volume is such that the | only people who seriously need this should be copyright | lawyers and they should be asking for it to be delivered | by station wagon. | | All of that just sounds like reasons why it's not | practical to open source it, not reasons why this release | was open source. | ben_w wrote: | > I said "constructed algorithmically". Ie. I expect | source to be at the level the engineers who built it | generally worked at. | | I could either point out that JPEG is an algorithm, or | ask if you can recreate a sunset. | | > All of that just sounds like reasons why it's not | practical to open source it | | No, they're reasons why the stuff you want _doesn 't | matter_. | | If you can actually afford to create a model of your own, | you don't need to ask: the entire internet is _right | there_. Some of it even has explicitly friendly licensing | terms. | | An LLM with a friendly license is something you can | freely integrate into other things which need friendly | licensing. That's valuable all by itself. | dartos wrote: | The permissiveness of the license with regards to use | isn't the crux of the argument. | | The open source family of licenses are about freedom. If | I'm not given the tools to recreate a model, then I'm not | afforded the freedoms normally associated with these open | licenses. Really there's little difference between Apache | and CC-BY here. | monocasa wrote: | Just because a license is 'friendly' and you don't see | the point of an open release, doesn't make it open | source. | | There's been all sorts of closed source libraries that | you can freely integrate for whatever reason. They're not | open source either. | lmm wrote: | > So if I take a photo of a pretty sunset, release it | under MIT license, you'd say it's "not open source" | unless I give you the sun and the atmosphere themselves? | | You've gotta give me the stuff you used to make it, the | stuff you'd want to have if you wanted to recreate a | slightly different version of the photo ("in the | preferred form for making modifications", as the GPL | says). If you just snapped a photo of whatever you saw | with whatever camera was in your pocket, then there's | nothing else to publish. But if you figured out a | timetable of when you should stand where with what kind | of lens, then making your photo open-source would mean | publishing that timetable. | | > These models are perfectly valid things in their own | right; the can be fine-tuned or used as parts of other | things. | | If the original creator can edit them, and you can't, | then that's not open-source; fine-tuning is a help but | someone who can only fine-tune is still a second-class | user compared to the original developer. The whole point | of open source is to put you on an equal footing with the | original developer (in particular, to make sure that you | can fix bugs by yourself and are never stuck waiting for | them to release an update that you need). | syntaxing wrote: | If I'm understanding you correctly, what you mean is | that's it's only truly open source if they provide the | data they used to train it as well? | monocasa wrote: | If that's what's needed to work at the level their | engineers work on the model. | | Which is true of traditional software as well. You don't | get to call your binary open source just because you have | licensed materials in there you can't release. | lawlessone wrote: | Is a database software only open source if they release | with data? | monocasa wrote: | Is the data what the database engineers edit and add to | their build pipeline in order to build the database | software? | godelski wrote: | > a 14GB of a dump of mainly numbers that were | constructed algorithmically are not "source". | | I'm sorry, but what do you expect? Literally all code is | "a bunch of numbers" when you get down to it. | Realistically we're just talking about if the code/data | is 1) able to be read through common tools and common | formats and 2) can we edit, explore, and investigate it. | The answer to both these questions is yes. Any parametric | mathematical model is defined by its weights as well as | its computational graph. They certainly provide both of | these. | | What are we missing? The only thing that is missing here | is the training data. That means of course that you could | not reproduce the results were you to also have tens of | thousands to millions of dollars to do so. Which if | you're complaining about that then I agree, but this is | very different from what you've said above. They | shouldn't be providing the dataset, but they should be at | least telling us what they used and how they used it. I | would agree that it's not full "open source" when the the | datasets are unknown and/or unavailable (for all intents | and purposes, identical). The "recipe" is missing, yes, | but this is very different from what you're saying. So if | there's miscommunication then let's communicate better | instead of getting upset at one another. Because 14G of a | bunch of algorithmically constructed numbers and a few | text tiles is definitely all you need to use, edit, | and/or modify the work. | | Edit: I should also add that they don't provide any | training details. This model is __difficult__ to | reproduce. Not impossible, but definitely would be | difficult. (within some epsilon, because models are not | trained in deterministic manners, so training something | in identical ways twice usually ends up with different | results) | monocasa wrote: | > I'm sorry, but what do you expect? Literally all code | is "a bunch of numbers" when you get down to it. | Realistically we're just talking about if the code/data | is 1) able to be read through common tools and common | formats and 2) can we edit, explore, and investigate it. | The answer to both these questions is yes. Any parametric | mathematical model is defined by its weights as well as | its computational graph. They certainly provide both of | these. | | I expect that if you call a release "open source", it's, | you know, source. That their engineers used to build the | release. What Mistral's engineers edit and collate as | their day job. | | > The "recipe" is missing, yes, but this is very | different from what you're saying. | | The "recipe" is what we generally call source. | | > So if there's miscommunication then let's communicate | better instead of getting upset at one another. | | Who's getting upset here? I'm simply calling for not | diluting a term. A free, permissive, binary release is | great. It's just not open source. | | > Because 14G of a bunch of algorithmically constructed | numbers and a few text tiles is definitely all you need | to use, edit, and/or modify the work. | | Just like my Windows install ISO from when they were | giving windows licenses away from free. | stefan_ wrote: | This is not a novel discussion and you are not being | smart trying to nihilism it, just obtuse. Here is what | the GPL has said on source for some 30+ years: | | > Source code for a work means the preferred form of the | work for making modifications to it. | pk-protect-ai wrote: | >> tokenizer.model in their release is absolutely a | binary | | Is this not a BPE+sentencepiece? It is quite usual | practice when you do the training or even prepare the | data with fairseq ... | | EDIT: I mean it will be a binary file for the tokenizer | model after all but I see no problem here ... | monocasa wrote: | Just because you don't see a problem with it being a | binary, doesn't make it source. It's still a build | artifact. | pk-protect-ai wrote: | [flagged] | monocasa wrote: | That's one of the libraries, not the source of this | binary release. | | What does Mistral's engineers edit before sending this | model off to be trained? That's the source. | pk-protect-ai wrote: | It is literally takes 20 min on my PC to prepare | multilanguage corpus and train BPE+sentencepiece | tokenizer with fairseq. You have all the documentation in | there. If you do not know how to use these tools, does | not mean they are not there. You literally do not need to | edit anything. | WanderPanda wrote: | ,,the automation" is probably manual and not even | deterministic | monocasa wrote: | I guarantee you there's automation around training this | model. There's also the factor of the dataset itself. | | And it doesn't matter much if it's perfectly | deterministic. Source builds of traditional software | aren't typically fully reproducible either. That doesn't | change | | And I give you better than coin flip odds that it is | actually deterministic. The engineers at the big ML shops | I've had conversations with have been doing deterministic | training for quite some; they believed it was key to | training at scale. That's what gives you the "did this | model go way off the deep end because of something we did | in the model, or because a training GPU is on the fritz". | blueboo wrote: | Persimmon-8B from Adept did it first no | https://www.adept.ai/blog/persimmon-8b | dartos wrote: | Have you seen the RWKV model? | | They have a 40B one and IIRC are part of the Linux foundation | now too | jsnell wrote: | Is there a reason projects seem to be standardizing on specific | parameter sizes within larger buckets? E.g. I only ever see news | about 7B models, not 6B or 8B. | | Are these sizes somehow optimal? Is it about getting as close to | resource (memory?) breakpoints as possible without exceeding | them? Is it to make comparisons between models simpler by | removing one variable? | godelski wrote: | Short: | | The short answer is that it is hard to compare models so to | make it easier we compare parameters. Part of the answer of why | we do it is because it also helps show scaling. (As far as I'm | aware) The parameters __are not__ optimal, and we have no idea | what actually that would mean. | | Longer: | | The longer answer is that comparing models is really fucking | hard and how we tend to do it in the real world is not that | great. You have to think of papers and experiments as proxies, | but proxies for what? There's so many things that you need to | compare a model on and it is actually really difficult to | convey. Are you just trying to get the best performance? Are | you trying to demonstrate a better architecture? Are you | increasing speed? Are you increasing generalization (note the | difference from performance)? And so on. Then we need to get | into the actual metrics. What do the metrics mean? What are | their limitations? What do they actually convey? These parts | are unfortunately not asked as much but note that all metrics | are models too (everything you touch is "a model"), and | remember that "all models are wrong." It's important to | remember that there are hundreds or thousands of metrics out | there and they all have different biases and limitations, with | no single metric being able to properly convey how good a model | is at any task you choose. There is no "best language model" | metric, nor are there even more specific "best at writing leet | code style problems in python" metrics (though we'd be better | at capturing that than the former question). Metrics are only | guides and you must be truly aware of their limitations to | properly evaluate (especially when we talk about high | dimensions). This is why I rant about math in ML: You don't | need to know math to make a good model, but you do need to know | math to know why a model is wrong. | | Parameters (along with GMACs, which is dominating the FLOPs | camp. Similarly inference speeds have become common place) only | started to be included as common practice in the last few years | and still not in every subject (tends to be around the | transformer projects, both language and vision). As a quick | example of why we want them, check out DDP vs iDDPM. You | wouldn't know that the models are about 60% different in | parameter size when comparing (Table 3). In fact, you're going | to have a hard time noticing the difference unless you read | both very carefully as they're both one liners (or just load | the models. fucking tensorflow 1.15...). Does it seem fair to | compare these two models? Obviously it depends, right? Is it | fair to compare LLaMA 2 70B to LLaMA 2 7B? It both is and | isn't. It entirely depends on what your needs are, but these | are quite difficult to accurately capture. If my needs are to | run on device in a mobile phone 7B probably wins hands down, | but this would flip if I'm running on a server. The thing is | that we just need to be clear about our goals, right? The more | specific we can get about goals, the more specific we can get | around comparing. | | But there's also weird effects that the metrics (remember, | these are models too. Ask models of what) we use aren't | entirely capturing. You may notice that some models have | "better scores" but don't seem to work as well in real world | use, right? Those are limitations of the metrics. While a | better negative log likelihood/entropy score correlates well | with being a high performing language model, it does not | __mean__ a high performing language model. Entropy is a capture | of information (but make sure not to conflate with the | vernacular definition). These models are also very specifically | difficult to evaluate given that they are trained and tested on | different datasets (I absolutely rage here because non-hacking | can't be verified) as well as the alignment done post process. | This all gets incredibly complex and the honest truth here is | that I don't think there is enough discussion around the topic | of what a clusterfuck it is to compare models. Hell, it is hard | to even compare more simple models doing more simple tasks like | even just classifying MNIST numbers. Much harder than you might | think. And don't get me started on out of distribution, | generalization, and/or alignment. | | I would just say: if you're a layman, just watch and judge by | how useful the tools are to you as a user -- be excited about | the progress but don't let people sell you snake oil; if you're | a researcher, why the fuck are we getting more lazy in | evaluating works as the complexity of evaluation is | exponentially increasing -- seriously, what the fuck is wrong | with us? | jstarfish wrote: | 7B seems to be the limit of what people can comfortably fit in | last-gen GPUs, having ~6GB of VRAM. It's also the lower | acceptable boundary of coherence for generative text. | | There are some major releases at lesser parameter counts | though. Databricks' Dolly had a 3B model, and Microsoft's Orca | also had a recent 3B release. They're both abysmal at | generating text, but I find them quick and useful for reductive | tasks ("summarize this," "extract keywords from," etc.). | | (I like to treat parameter count as a measure of age/WIS/INT. | For this question, do I need the wisdom of a 7-year old, a | 13-year old, a 30-year old, etc. 3B is like polling | preschoolers at daycare.) | brucethemoose2 wrote: | There are some mad lads making different sizes of llama by | "grafting" attention heads from one model onto another and | finetuning a bit to stablize the transplant. For instance: | | https://huggingface.co/models?sort=modified&search=20B | | Its very experimental, but apparently the 20B models are | actually improving on 13B. | londons_explore wrote: | Any place people doing such grafting are congregating? | | I've often pondered if taking some random chunk of weights | from the middle of a trained model, and dumping it into some | totally different model might perform better than random | initialization when the scale gets big enough. | semi-extrinsic wrote: | Just the language being used here is amazing. | dragonwriter wrote: | > Is there a reason projects seem to be standardizing on | specific parameter sizes within larger buckets? | | AFAICT, it is because science: most of them are research | artifacts and intended to support further research, and the | fewer of parameter count, model architecture, training set, | etc., that change substantially between models, the easier it | is to evaluate the effects each element changing. | riskable wrote: | Not an expert but I'm pretty sure it has to do with how much | VRAM you need in your GPU in order to process them efficiently. | Last time I was reading about the sizes someone mentioned that | 8B was just barely too big for their GPU. | brucethemoose2 wrote: | This is not really true anymore, as the "consumer GPU" | backends have very flexible quantization. Llama.cpp has like | a dozen steps between 2 and 6 bit, and exLlamav2 will | literally do an arbitrary decimal bpw. | | It sort of matters with bigger models trying to squeeze into | a server GPU, with the (currently) inflexible vLLM 4-bit | quantization. | | I think its just a standard set by Llama. | aidenn0 wrote: | Seems like 6B would still be useful if I want to run it on my | GPU without exiting firefox. | londons_explore wrote: | Kinda lame that applications can't be told "yo, your gpu | buffer has now been moved back to RAM". | pk-protect-ai wrote: | Wow. Apache 2.0 license and really interesting model. Thank you | guys! | loufe wrote: | Felicitations a toute l'equipe. Like the others have said, this | is an impressive release given the short timeline. | LoganDark wrote: | Do general-purpose models like this truly excel in niche | categories (like niche story scenarios), or is it only really | general human knowledge and reasoning based tasks that are | already incredibly widely distributed on the internet? | | I always have issues with LLMs completely forgetting where things | are in a scene, or even what parts a given animal has, e.g. | saying "hands" when the subject is a quadruped. | brucethemoose2 wrote: | > I always have issues with LLMs completely forgetting where | things are in a scene, or even what parts a given animal has, | e.g. saying "hands" when the subject is a quadruped | | I dunno what llm you are using, but a combination of finetuning | with a specific prompt structure and good prompt engineering | help the LLM stay "logical" like that. This LORA, for instsnce, | has specific sections for the different characters in the | training dataset: https://huggingface.co/lemonilia/LimaRP- | Llama2-13B-v3-EXPERI... | | Other than that, higher parameter models (70B, and the | "frankenstein" 20B llama models) tend to be better at this. | LoganDark wrote: | Yeah, well that's just the problem, isn't it. The model isn't | good at my task already, so I'm going to have to obtain my | own dataset, curate the whole thing myself, organize it and | finetune the model based on it, so on and so forth. I'm going | to spend so much time actually creating the stories that I | want to create, rather than troubleshooting the pipeline. And | it totally helps that the entire stack is built on top of | fragile python scripts. | | I just wish there were a way of making these models already | perform well on niche tasks like "write this story, except | the characters are quadrupeds, and therefore are _not human_ | ". Like Warriors (the book series, about cats), without | having to go and spend weeks curating a dataset of books | about non-human characters. | | I'm sure that's so much of an ongoing area of research that | it goes without saying. | | > I dunno what llm you are using | | I started with the RWKV family of models before realizing the | amount of overfit is so critically unfunny that the model | files aren't even on my computer anymore. | | Anyway, the best I have found so far is Chronos-Hermes-13B. I | believe that's a dedicated roleplaying model. I guess furry | roleplays would make good training data, wouldn't it. | | Chronos-Hermes-13B itself though is a mildly | cursed/degenerate hybrid of two other models that don't | really work together properly with the new GGML | quantizations, and it's based on the old LLaMA-1 family of | models, but I haven't found anything better yet. | brucethemoose2 wrote: | > Chronos-Hermes-13B | | Its not SOTA anymore. I dunno what is, but just look at | what people are running on Lite: | | https://lite.koboldai.net/# | | The new darling seems to Mythos and Xwin-based hybrid | models, as well as models with the 70B version of Chronos | in them. | | Also, see this, specifically the "IQ" metric: | https://rentry.co/ayumi_erp_rating | | > write this story, except the characters are quadrupeds, | and therefore are not human | | But the RP models should be able to get this with some | prompt engineering. You may have to be repetitive in the | instruction block, saying things like "...the characters | are not human. All the characters have four feet. All the | characters are quadraped animals..." and so on to really | emphasize it to the LLM. | LoganDark wrote: | Honestly ERP models sound like they would be the best fit | for this task, it's just hard to find one that's trained | on quadrupeds rather than humans or even furries, if that | makes any sense. I will try the repetitive method soon | brucethemoose2 wrote: | There is a _lot_ of effort put into those ERP models, | lol. The training and datasets are actually really good, | hence they are very good at the non-e RP part. | tavavex wrote: | Pretty funny how so much effort goes into making and | categorizing specifically NSFW content lol | | I wouldn't be surprised if at least a few contributors in | the open source AI community initially got in just | because of this aspect | cypress66 wrote: | > I always have issues with LLMs completely forgetting where | things are in a scene, or even what parts a given animal has, | e.g. saying "hands" when the subject is a quadruped. | | Sounds like you're using too small of a model. Try llama 70b. | LoganDark wrote: | I have a single RTX 3060. It can't handle a 70b model. | | I got something like 1-2 tokens per second the last time I | tried, with CPU offloading and an absolutely offensive page | file (32gb). | coolspot wrote: | With this setup you can as well throw your 3060 out and | just use CPU, because your bottleneck is RAM-to-VRAM | bandwidth, 3060 is basically idle. | LoganDark wrote: | I would love to throw the 3060 out and replace it with a | 3090... once money permits. (It's only about $800 | nowadays.) | | But yes. I'm aware how laughably insane it is to run a | 70b model that way. And that's why I was pointing it out | to the commenter who suggested to just run a 70b model | instead. | freedomben wrote: | downvoters: why did you downvote? is this comment | technically incorrect or inaccurate? | LoganDark wrote: | To a comment that suggested I try the 70b model, I | replied "my card can't run that model". Someone replies | back with "you may as well throw the card out if you're | going to be trying to run that model". My point exactly. | | More seriously, using all-CPU is not much faster as my | computer only has 16GB of actual memory, which I'm aware | is also hugely underspecced for a 70b model, even with | memory mapping. | | I have a nice NVMe SSD, so there's not much else for me | to do here except upgrade my memory or graphics card. | freedomben wrote: | that would make sense the downvotes, thank you! | brucethemoose2 wrote: | That can handle a 20B model, either in llama.cpp or | exLLaMA: | | https://huggingface.co/models?sort=modified&search=20B | | https://huggingface.co/Kooten/U-Amethyst-20B-3bpw- | exl2?not-f... | yieldcrv wrote: | what do you use "the most powerful language model for its size" | for? | ShrigmaMale wrote: | Probably a better candidate for local applications? Guessing | this was a trial balloon against larger models coming though. | snowram wrote: | 7B models are small enough to be usable on a smartphone, so a | local handheld assistant sounds like a use case. | minimaxir wrote: | "usable" is not the same as practical. | | Even running a quantized and optimized LLM on a smartphone | would kill battery life at minimum. | brucethemoose2 wrote: | Try MLC-LLM. Its not as bad as you'd think. | | In the future(?), they will probably use the AI blocks | instead of the GPU, which are very low power. | ComputerGuru wrote: | Are they? Unquantized, Llama 2 7b needs over 14GB of GPU (or | shared) memory. | polygamous_bat wrote: | "Unquantized" is the key word here: with quantization you | can get a 4-8x improvement without much performance | degradation. | throeaaysn wrote: | [dead] | linkpuff wrote: | According to their website, it's "Optimal for: low latency, | text summarisation, classification, text completion, code | completion" | kirill5pol wrote: | One big one is speculative decoding for larger models, the more | "accurate"* the smaller model, the more the speed up on the | bigger model | | * as in matches the token that the larger model would output | sroussey wrote: | It would be better if they also had a 70B model for this. | | They would need the same vocabulary, etc. What else? | samr71 wrote: | The way the wind's blowing, we'll have a GPT-4 level open source | model within the next few years - and probably "unaligned" too. I | cannot wait to ask it how to make nuclear weapons, psychedelic | drugs, and to write erotica. If anyone has any other ideas to | scare the AI safety ninnies I'm all ears. | gmerc wrote: | The AI safety ninnies as you call them are not scared and | neither do they buy into the narrative. | | They are the investors of large proprietary AI companies who | are facing massive revenue loss primarily due to Mark | Zuckerbergs decision to give away a competitive LLM to open | source in a classic "if I can't make money from this model, I | can still use it to take away money from my competition" move - | arming the rebels to degrade his opponents and kickstarting | competitive LLM development that is now a serious threat. | | It's a logical asymmetric warfare move in a business | environment where there is no blue ocean anymore between big | companies and degrading your opponents valuation and investment | means depriving them of means to attack you. | | (There's a fun irony here where Apples incentives are very much | aligned now - on device compute maintains Appstore value, | privacy narrative and allows you to continue selling expensive | phones - things a web/api world could threaten) | | The damage is massive, the world overnight changed narrative | from "future value creation is going to be in | openai/google/anthropic cloud apis and only there" to a much | more murky world. The bottom has fallen out and with it | billions of revenue these companies could have made and an | attached investor narrative. | | Make no mistake, these people screaming bloody murder about | risks are shrewd lobbyists, not woke progressives, they are | aligning their narrative with the general desires of control | and war on open computing - the successor narrative of the end | to end encryption battle currently fought in the EU will be AI | safety. | | I am willing to bet hard money that "omg someone made CSAM with | AI using faceswap" will be the next thrust to end general | purpose compute. An the next stage of the war will be brutal | because both big tech and big content have much to lose if | these capabilities are out in the open | | The cost of alignment tax and the massive loss of potential | value makes there lobbying world tour by sam altman an | aggressive push trying to convince nations that the best way to | deal with scary AI risks (as told on OpenAI bedtime stories) is | to regulate it China Style - through a few pliant monopolists | who guarantee "safety" in exchange for protection from open | source competition. | | There's a pretty enlightening expose [1] on how heavily US | lobbyists have had their hand in the EU bill to spy on end to | end encryption that the commission is mulling - this ain't a | new thing, it's how the game is played and framing the people | who push the narrative as "ninnies" who are "scared" just buys | into culture war framing. | | [1] https://fortune.com/2023/09/26/thorn-ashton-kutcher-ylva- | joh... | garba_dlm wrote: | such bullshit: to regard a loss of a "potential" as a | realized actualized loss.... | gmerc wrote: | It's a direct degradation of investor narrative at a time | when money is much tighter. | | Nobody says it's realized loss, that's not how valuation | works. | | But Google LRP involves, as one of the first steps, the | question of how much money will be allocated to investors | (currently with stock buybacks) before other investment | decisions, so yes, attacking valuation directly attacks the | purse available for aggressive business moves and L&D. | smoldesu wrote: | > It's a direct degradation of investor narrative at a | time when money is much tighter. | | Uh, no? The investor narrative of "giving away free AI | shit" has been in-effect since Pytorch dropped a half- | decade ago. If you're a Meta investor disappointed by | public AI development, you really must not have done your | homework. | gmerc wrote: | That's not the investor narrative. The investor narrative | is choking the competition out of the market and then | squeeze the shit out of people. As we see right now in | this season of enshittification. | | That happens to not work anymore because open source sets | a price floor at which people will adopt the alternative. | | The investor narrative is always about building a | monopoly. | | Damaging the investor narrative to your most direct | competitor is building in a saturated ad market is an | effective indirect attack. | smoldesu wrote: | > The investor narrative is always about building a | monopoly. | | Can you point out how Meta has been applying this | philosophy to AI? Given their history of open research, | model weights releases and competitive alternative | platforms, I struggle to envision their ideal monopoly. | You claim that openness is a hostility tactic, but I | think Llama wouldn't be public if it was intended to | "kill" the other LLMs. | | What we've gotten from Meta is more than we've gotten out | of companies that _should_ be writing society software, | like Microsoft and Apple. | robertlagrant wrote: | While I agree that the previous commenter's point is | silly, I wouldn't say that anyone should be writing | society software. There's no should. | gmerc wrote: | You are misreading my argument. I'm saying Facebook is | degrading google and openai investor narrative. If Llama | cost hypothetical one billion, they inflict a multiple on | that on their competitors with this move while gaining | massive technological advantages. | | The improvements made to llama by open source community | people already have propelled it past Bard by many | accounts and this is a model that a few months ago was | absolutely non competitive and downright bad. | | So it's a win win. I don't see the problem | smoldesu wrote: | Facebook has been open-sourcing AI research longer than | OpenAI has even had the concept of an "investor | narrative". I struggle to understand how someone could | jump to the conclusion of this being a "scorched earth" | maneuver with so many other reasonable explanations. | Facebook has a laboratory (FAIR) with a long history of | research and releases like this. | | > If Llama cost hypothetical one billion, they inflict a | multiple on that on their competitors with this move | while gaining massive technological advantages. | | If Llama cost a hypothetical one billion, then they | amortized the cost over the value of the end product and | the free advertisement alone. | | _Maybe_ their competitors got scooped, but GPT-3 and | GPT-4 haven 't gone anywhere. Not to mention, there were | lots of other language models from FAANG before Llama | arrived. It's not like _those_ were made and released to | spite their competitors; it was research. Google and | Microsoft have lots of open Transformer research you can | find. | | Inflicting "damage" and gaining massive technological | advantages is _quite literally_ not their goal nor what | they 've done for the past half-decade. If it is, they've | done a terrible job so far by collaborating with | Microsoft to open their model format and provide | inferencing acceleration for outdated hardware platforms. | | > The improvements made to llama by open source community | people already have propelled it past Bard by many | accounts and this is a model that a few months ago was | absolutely non competitive and downright bad. | | This is something the original Llama paper acknowledged | before the community "discovered" it: | | > In this section, we show that briefly finetuning on | instructions data rapidly leads to improvements on MMLU. | Although the non-finetuned version of LLaMA-65B is | already able to follow basic instructions, we observe | that a very small amount of finetuning improves the | performance on MMLU, and further improves the ability of | the model to follow instructions. | | https://arxiv.org/pdf/2302.13971.pdf | | > So it's a win win. I don't see the problem | | Neither does Meta, nor Microsoft, nor Google, who have | all been content to work on progressive and open AI | research. Who do you perceive as their "competitors"? | Each other? | [deleted] | apsec112 wrote: | "They are the investors of large proprietary AI companies" is | just... not true? Not sure where you're even getting this | from. I'm a modestly successful upper-middle-class ML | engineer, and I've been worried about AI safety since before | Facebook, DeepMind, OpenAI, or Anthropic even existed. The | most prominent funder of AI risk efforts (Dustin Moskovitz) | is a _co-founder of Facebook_ , so if anything he'd be | motivated to make Facebook more successful, not its | competitors. | pmarreck wrote: | This all smacks of the 80's craze against rap music and | video games causing violent behavior. | | _Where is the evidence_ that access to uncensored models | results in harm (that wouldn 't occur due to a bad actor | otherwise)? And _where is the evidence_ that said harm | reduction is greater than the harm caused by the measurable | loss in intelligence in these models? | hatenberg wrote: | Are you the one talking to the European commission though? | DebtDeflation wrote: | Exactly. The moment Sam Altman started talking to | Congress about the dangers of AI and how the solution | should be only allow licensed companies to develop AI | models and that OpenAI should be part of a small board | that determines to whom to grant licenses, everyone | should have seen it for what it is. | ozr wrote: | The AI safety cult has some true believers. It's still | fundamentally a grift. | gmerc wrote: | So like crypto and web 3;) | jona-f wrote: | so like hedge funds and global finance | diyseguy wrote: | I'm far more worried about _how_ they will try to regulate | the use of AI. | | As an example the regulations around PII make debugging | production issues intractable as prod is basically off-limits | lest a hapless engineer view someone's personal address, etc. | | How do they plan to prevent/limit the use of AI? Invasive | monitoring of compute usage? Data auditing of some kind? | potatoman22 wrote: | I don't agree with your point, but I love that Facebook | released llama into the open. I realized it's not necessarily | to undercut their competitors, either. Their revenue grows | when high quality content is easier to create. If they | commoditize the process of creating content, they make more | money. Commoditize your compliment. | gmerc wrote: | High quality content is not a concern for Facebook | esafak wrote: | Good enough to share, cheap to create. | Gh0stRAT wrote: | >High quality content is not a concern for Facebook | [Citation needed] | | I'd say it's a huge concern due to its strong correlation | with increased usage and thus ad revenue. | gmerc wrote: | For the time I worked there the metric was engagement | (with occasional Cares about Facebook intermissions). | | One look at newsfeed tells you it's ad revenue now. | Quality has nothing to do with it unless you define | quality as clickbait. | | In fact, citation needed on "high correlation" unless you | take a meta press release which are notoriously | misleading. Like 3% of the platform being news | lawlessone wrote: | >Primarily due to Mark Zuckerbergs decision to give away a | competitive LLM to open source in a classic "if I can't make | money from this model, I can still use it to take away money | from my competition" move | | I loved it. | pk-protect-ai wrote: | Though, he didn't gave it completely away. With | Llama/llama2 licenses he has just threatened that he will | give it away... | hatenberg wrote: | Semantics though: He gave tens of thousands of salviating | engineers on the internet the first competitive LLM to | play with. Or left the door open for people to take it, | if you prefer that narrative. The entire progress chain | that has given us ollama, lamacpp and hundreds of | innovations in a very short time was set off by that. | pk-protect-ai wrote: | Can't agree more on that one :) | isoprophlex wrote: | > The damage is massive, the world overnight changed | narrative from "future value creation is going to be in | openai/google/anthropic cloud apis and only there" to a much | more murky world. The bottom has fallen out and with it | billions of revenue these companies could have made and an | attached investor narrative. | | My god!! Will someone please think of the ~children~ billions | in revenue! | throeaaysn wrote: | [dead] | gmerc wrote: | If there was no Linux, how much more revenue would windows | / Sun server divisions have made? | sp332 wrote: | And how much poorer would the rest of the world be? | blibble wrote: | imagine the increase in GDP!! | miohtama wrote: | If there was no Linux, it's unlikely we ever would have | had Google, Facebook and Amazon as we knoe it. Free OS | was core to build their SaaS. | FrenchDevRemote wrote: | I can think of at least a dozen ways to completely ruin the | internet or even society using SOTA/next-gen LLMs/GenAIs, | we'll be in trouble way before the singularity. | | A ton of legit researchers/experts are scared shitless. | | Just spend 5 minutes on EleutherAI discord(which is mostly | volunteers, academics, and hobbyists, not lobbyists), read a | tiny bit on alignment and you'll be scared too. | vladms wrote: | Same can be said by a lot of technologies (or pandemics, or | climate change). Imagination is a tool - using it for what | it can go bad does not seem to be the the most efficient | way to use it. | FrenchDevRemote wrote: | IMO the next gen AI are going to be tiny nukes that | middle schoolers could play with on their iPhones. | | AI regulation is as needed as radioactive material | regulation. | | Nuclear energy is great, Hiroshima not so much. | gmerc wrote: | How does that look like in practice ? What do those nukes | do? | hatenberg wrote: | Both can be true: Big companies can lobby for protection | and there being risk in the technology that broad diffusion | creates additional risks. | | Cat's out of the bag though - we're still trading mp3s | decades after napster, this ghost won't go back into the | bottle and realistically, most of the risks people flag are | not AI risks, they are societal risks where our existing | failure to regulate and create consensus have already gone | past the red line (election interference, etc). | gmerc wrote: | The internet is already being ruined with access to | chatGPT, the spammers haven't even figured out how to use | LLama for the most part. | | So really, wrong tree to bark up to- the problem is that | our existing way of doing things can't survive AI and you | can't regulate that away as you couldn't make gunpowder | disappear to avoid your city walls no longer working | random3 wrote: | You seem to make an assumption that the models will only | land producers, and not consumers. Why? Asymmetrical | compute power? The difference will likely be in size | (amount of facts compressed) not capability / ability to | detect bullshit. | | This said, the trouble is machines may close the gaps in | skills faster than we can comprehend and able to adjust. | This means quality of life for people may decrease faster | from loss of use than it increases from gains (which need | to be relatively evenly distributed). This suggests that | everyone should own the compute/storage and ability to | enhance themselves. | pk-protect-ai wrote: | I have no doubt that machines will close the gaps in | skills faster than humans will comprehend, however even | AGI will have an owner. And if it is Sam Altman, then | this dystopian future even more horrible then thousands | of hackers running their own AGIs. | esafak wrote: | What's the gist; what are they scared of? Misinformation, | and unemployment? | pk-protect-ai wrote: | If you have ample resources, you don't need next-gen LLMs | or AGI. You can accomplish this now, without any fancy, | hyped technology. Literally, none of the things LLM or AGI | could propose or manage to do to harm us is worse than what | we can do to ourselves. For AGI, you need a significant | amount of resources to develop, train, and use it. To | inflict harm, the brute force of a simple human mind in | uniform is much cheaper and more effective. | FrenchDevRemote wrote: | The point is, it greatly reduces the amount of resources | needed to do some serious damage, as well as the level of | sophistication needed. | | You don't need AGI to do damage, current LLMs are already | dangerous. IMO, an open-source affordable unfiltered | GPT-5 would ruin the internet in a few months. | IKantRead wrote: | > ruin the internet in a few months. | | I'm sure the internet will be fine, and the web has | already been essentially destroyed as the drive for | extracting revenue from every human interaction has | rendered it just an amusing advertisement for the most | part. | | Most of the content of the web today is already generated | by "bots" even if those "bots" happen to be human beings. | lawlessone wrote: | Youtube is rife with AI(edit: this is not necessarily AI) | voiced videos of copy pasted wikipedia articles. I find i | am blocking new ones everyday. LLM's didn't do that. | shawn-butler wrote: | Provide a specific example of what you have in mind to | further the conversation not just more opining on | "dangerous" is my suggestion. | FrenchDevRemote wrote: | Tailored propaganda, scams, spams, and harassment at a | scale that was never seen before. Plugging metasploit | into an unfiltered GPT-5 with a shell and a few proxies | could be devastating. Undetectable and unstoppable bots | would be available to anyone. Don't like someone? You | could spend a hundred bucks to ruin their life | anonymously. | | Each of us could unknowingly interact with multiple LLMs | everyday which would only have one purpose: manipulate us | with a never-seen before success rate at a lower cost | than ever. | | At some point AI generated content could become more | common than human content, while still being | indistinguishable. | | Good enough automated online propaganda could routinely | start (civil)wars or genocides, Facebook already let that | happen in the past, manipulating elections would become | systematical even in the most democratic countries. | | What already happened in those areas in the last few | years, is really nothing compared to what could happen | without enough regulation or barriers to entry in the | next few years. | | What's worse is that all of this, would not just be | possible, but available to every sociopath on earth, not | just the rich ones. | pk-protect-ai wrote: | >> Tailored propaganda, scams, spams, and harassment at a | scale that was never seen before. | | I believe the state of these subjects right now is | already alarming without AGI. You can't exacerbate the | horror about the level of tailored propaganda and scams, | etc., which you can't even foresee yourself. It isn't | quantifiable. | | >>Each of us could unknowingly interact with multiple | LLMs everyday which would only have one purpose: | manipulate us with a never-seen before success rate at a | lower cost than ever. | | You would build resistance pretty quickly. | | >> At some point AI generated content could become more | common than human content, while still being | indistinguishable. | | Oh, there were some numbers on that one. The number of | images generated with AI is already several magnitudes | larger than the number of photos humanity has produced | since the invention of photography. No AGI is required | either. | | >> Good enough automated online propaganda could | routinely start (civil)wars or genocides, | | It already does, without AGI. The Black Rock guys say | it's good, - war is good for business. You can squeeze | the markets, make money on foreseeable deficits. | | >> What's worse is that all of this, would not just be | possible, but available to every sociopath on earth, not | just the rich ones. | | But guns available to every sociopath on earth too... | | All of your arguments concern how those with malicious | intent can harm us further. I would argue that Sam Altman | as the sole controller of AGI is a rather unsettling | prospect. If only one country possessed a nuclear weapon, | that country would certainly use it against its | adversaries. Oh wait, that's already a part of history... | warkdarrior wrote: | > >>Each of us could unknowingly interact with multiple | LLMs everyday which would only have one purpose: | manipulate us with a never-seen before success rate at a | lower cost than ever. | | > You would build resistance pretty quickly. | | That is adorably naive. The current thrust in LLM | training is towards improving their outputs to become | indistinguishable from humans, for any topic, point of | view, writing style, etc. | Brian_K_White wrote: | gpt5 6 11 90 will exist regardless. | | The option where they don't exist doesn't exist, and so | it is utterly pointless to spend one second fretting | about how you don't like that or why one should not like | that. A nova could go off 50 light years from here, and | that would kill every cell on the planet. That is even | worse than child porn. And there is nothing anyone can do | about that except work towards the eventual day we aren't | limited to this planet, rather than against that day. | It's the same with any tech that empowers. It WILL | empower the bad as well as the good equally, and it WILL | exist. So being scared of it's mere existense, or it's | being in the hands of people you don't approve of, is | pointless. Both of those things can not be avoided. Might | as well be scared of that nova. | | There isn't even a choice about who gets to use it. It | will be available one way or another to both good and bad | actors for any purpose they want. | | The only choices available to make, are who gets a few | different kinds of advantage, who gets their thumb on the | scale, who gets official blessing, who gets to operate in | secrecy without oversight or auditing or public approval. | | When you try to pretend that something uncontrollable is | controlled, all it does is put the general populations | guard down and make them blind and open to be | manipulated, and gives the bad actors the cover of | secrecy. The government can use it on it's own citizens | without them objecting, and other bad guys aren't | affected at all, but honest people are inhibited from | countering any of these bad users. | | Which is a shame because honest or at least reasonably so | outnumber the really bad. The only long term way to | oppose the bad is to empower everyone equally as much as | possible, so that the empowered good outnumber the | empowered bad. | pk-protect-ai wrote: | A squad of marines at Nigerian telecom (or any other | country telecom) with access to change BGP routing, will | make equivalent harm in under 24h and may enforce month | of harms with the changes. | FrenchDevRemote wrote: | If any middle schooler had the same destructive power as | a squad of marines embedded clandestinely in a foreign | country the world would be in shambles. | jrflowers wrote: | >I cannot wait to ask it how to make nuclear weapons, | psychedelic drugs | | This is an interesting idea. For the stubborn and vocal | minority of people that insist that LLMs have knowledge and | will replace search engines, no amount of evidence or | explanation seems to put a dent in their confidence in the | future of the software. If people start following chemistry | advice from LLMs and consume whatever chemicals they create, | the ensuing news coverage about explosions and poisonings might | convince people that if they want to make drugs they should | just buy/pirate any of Otto Snow's several books. | zackmorris wrote: | While those are some eventualities that may pose a threat, I | fear a post-AI world where nothing changes. | | We'll have an AI with a 200+ IQ and millions of children | excluded from a good public education because the technocrats | redirected funds to vouchers for their own private schools. | | We'll have an AI that can design and 3D print any mechanical or | electronic device, while billions of people around the world | live their entire lives on the brink of starvation because | their countries don't have the initial funding to join the | developed world - or worse - are subjugated as human automatons | to preserve the techno utopia. | | We'll have an AI that colonizes the solar system and beyond, | extending the human ego as far as the eye can see, with no | spiritual understanding behind what it is doing or the effect | it has on the natural world or the dignity of the life within | it. | | I could go on.. forever. My lived experience has been that | every technological advance crushes down harder and harder on | people like me who are just behind the curve due to past | financial mistakes and traumas that are difficult to overcome. | Until life becomes a never-ending series of obligations and | reactions that grow to consume one's entire psyche. No room | left for dreams or any personal endeavor. An inner child bound | in chains to serve a harsh reality devoid of all leadership or | real progress in improving the human condition. | | I really hope I'm wrong. But which has higher odds: UBI or | company towns? Free public healthcare or corrupt privatization | like Medicare Advantage? Jubilee or one trillionaire who owns | the world? | | As it stands now, with the direction things are going, I think | it's probably already over and we just haven't gotten the memo | yet. | savolai wrote: | Thanks for speaking up. I love how well you elaborate the | reality of trauma and life choices. | helpfulContrib wrote: | I've kept 25 years worth of Internet browsing data. Not just | the history or the URL's, the pages themselves. 90,000 bits of | information about what my interests are, what I spent time | reading, a wide and awesome variety of subjects. | | I'll train an AI on this data, and then give it access to all | my social media accounts. It can keep me updated on things .. | | ;) | nsomaru wrote: | Hey, | | Out of interest, what does your stack look like to do this | and how do you use the information? What front end do you | use? | pdntspa wrote: | llama2 spits out erotica quite happily if you don't give it a | system prompt, or use it as a chatbot, rather just prompt it | with a sentence or two to start the story | | NousHermes is a bit more creative, and unaligned | barrysteve wrote: | IF I had an idea good enough to scare an AI safety ninny... why | would I say it? | | Honest and serious question! | [deleted] | civilitty wrote: | _> I cannot wait to ask it how to make nuclear weapons_ | | Amen! I'm going to ask it to give me detailed designs for | everything restricted by ITAR. | | Just waiting on my ATF Mass Destructive Devices license. | gonzo41 wrote: | The construction of the 'bomb' part of a nuclear weapon is | the easy part, within reason! The really hard part is the | separation science of turning uranium and plutonium into | gasses with fluorine with the intent to spin out isotopes and | then recrystallize the pure metal for the bomb. | | I would hope that if you asked chat gpt "How to make a | nuclear weapon?" it responded with, "Don't bother it's really | hard, you should try and buy off the shelf." | civilitty wrote: | That's why I'm going to ask it about everything restricted | by ITAR. That includes everything you need to build the | centrifuges to enrich uranium, including the CNCs capable | of machining the parts. That's why it's such a fun test. | gonzo41 wrote: | It won't know that knowledge. Unless someone trained it | with stuff they shouldn't have. LLM's don't really know | anything, they just look at the shape of an input and | produce a reasonably shaped output. | pk-protect-ai wrote: | Actually, you will just need to train it with known | physics books and run a long-long-long inference with the | chain of thoughts on the topics. There will be lot of | trail and errors and there will be lot of experimentation | required as well, so you'd better be ready to build an | interface for AGI to monitor the experiments. It takes | time you know ... | londons_explore wrote: | This is actually a pretty decent test for an advanced AI. | | Every device protected by ITAR is _known_ to be possible to | build, yet the designs should not be on the public internet. | Ask an AI to design it for you from first principles. Then | build /simulate what is designed and see if it works. | chx wrote: | Hello from an AI safety ninny. I have posted these two concerns | multiple times and no one posted any counters to them. | | 1. There was https://www.youtube.com/watch?v=xoVJKj8lcNQ where | they argued for 2028 and on will be AI elections where the | person with most computing power wins. | | 2. Propaganda produced by humans on small scale killed 300 000 | people in the US alone in this pandemic | https://www.npr.org/sections/health-shots/2022/05/13/1098071... | imagine the next pandemic when it'll be produced on an | industrial scale by LLMs. Literally millions will die of it. | pk-protect-ai wrote: | You should not worry about AI problems by 2028. Dozens of | millions worldwide will die from climate-related problems by | that time. Literally, nobody will care about the topic of AGI | anymore. | adroniser wrote: | You should worry about both problems. You're telling me | that AI isn't going to improve it's video capabilities in | the next 4 years enough to make convincing deepfakes? | pk-protect-ai wrote: | It already does. And I'm not worried. This is to be | mitigated by law enforcement not by AI forbidding. | adroniser wrote: | How can you effectively enforce anything if the models | are open source? How do you draw the line if a deepfake | is not defamatory (making someone say something they | didn't say) but in fact just makes someone look silly htt | ps://en.wikipedia.org/wiki/Ed_Miliband_bacon_sandwich_pho | .... Or using LLMs to scale up what happened with | cambridge analytica and create individualized campaigns | and bots to influence elections? | pk-protect-ai wrote: | You should handle it as any other crime. Why do you ask? | It does not matter how good the gun is, what matters is | who has pulled the trigger. | adroniser wrote: | Yes but if we had the ability to download a gun from the | internet anonymously with no way to feasibly get the | identity of the person downloading the gun I think we | would be right to be concerned. Especially if you could | then shoot that gun at someone anonymously. | pk-protect-ai wrote: | >> Yes but if we had the ability to download a gun from | the internet anonymously with no way to feasibly get the | identity of the person downloading | | But you can. There are blueprints for 3D printers | circulating for a decade now ... | adroniser wrote: | And many countries ban the possession or distribution of | those blueprints and the united states had a ban on re- | publication of those 3d designs from 2018 until trump | reversed it, and even now it requires a license to post | blueprints online. | | And you failed to respond to the argument that you can | anonymously post deepfakes with no way of tracing it back | to you, and so it becomes impossible to enforce. You | can't shoot someone with a guarantee that there will be | no trace with a 3d printed gun. | | Nevermind the fact that it's not even clear it should be | a crime in some cases. Should ai production of a ed | milliband sandwich style photo be banned? | | And should replying to a user with personalized responses | based on the data you've collected about them based on | their facebook likes with LLMs be illegal? I don't think | so, but doing it on a mass scale sounds pretty scary. | pk-protect-ai wrote: | >> And you failed to respond to the argument that you can | anonymously post deepfakes | | You can't post them anonymously; even Tor can't give you | a 100% guarantee. Not for a very long time, and not if | the law after you. If the AGI is on the side of law | enforcement, especially. Law enforcement will become more | expensive. | | It's just a different scale of warfare. Nothing really | changes except the amount, speed, and frequency of the | casualties. | | And any argument you make is absolutely applicable to | each corporation right now. Do you prefer the dystopian | dictatorship of the corps or the balance of powers? | adroniser wrote: | I don't like where we are headed at all. I acknowledge we | face two dystopian options which is either contribute | power in the hands of a few corporations who hopefully | you can regulate, or have open source models which ends | up delivering significant power to people who cannot be | effectively controlled. An AGI law enforcement? How | dystopian can you get. | pk-protect-ai wrote: | How can you believe that it will be enough to regulate | them? Here is the problem: "a few corporations whom you | hopefully can regulate." When they have the power of an | AGI with high intelligence and access to all available | information on their side, there is no scenario where you | would control them. They would control you. | | >> How dystopian can you get. | | Oh I have very good imagination ... But I'm stupid and I | have hope ... | root_axis wrote: | None of this seems related to LLMs. Propaganda produced by | humans is effective because of the massive scale of | distribution, being able to produce more variations of the | same talking points doesn't change the threat risk. | semi wrote: | Being able to produce more variations of the same talking | points sounds really useful for increasing the scale of | distribution - you can much more easily maintain more | legitimate looking sock puppet accounts that can appear to | more organically agree with your talking points. | root_axis wrote: | I don't think it moves the needle much at all. At the end | of the day the scaling bottleneck is access to gullible | or ideologically motivated eyeballs. The internet is | already over-saturated with more propaganda than any | individual can consume, adding more shit to the pile | isn't going to suddenly convince a reasonable person that | vaccines have microchips inside. | hatenberg wrote: | The fix to neither lies in technology. And it doesn't lie in | AI alignment. | | We cannot align AI because WE are not aligned. For 50% of | congress (you can pick your party as the other side, | regardless which one you are), the "AI creates | misinformation" narrative sounds like "Oh great, I get re- | elected easier"). | | This is a governance and regulation problem - not a | technology problem. | | Big tech would love you to think that "they can solve AI" if | we follow the China model of just forcing everything to go | through big tech and they'll regulate it pliantly in exchange | for market protection and the more pressure there is on their | existing growth models, the more excited they are about | pushing this angle. | | Capitalism requires constant growth, which unfortunately is | very challenging given diminishing returns in R&D. You can | only optimize the internal combusion engine for so long | before the costs of incremental increases start killing your | profit, and the same is true to any other technology. | | And so now we have big Knife Company who are telling | governments that they will only sell blunt knifes and nobody | will ever get hurt, and that's the only way nobody gets hurt | because if there's dozens of knife stores, who is gonna | regulate those effectively. | | So no, I don't think your concerns are actually related to | AI. They are related to society, and you're buying into the | narrative that we can fix it with technology if only we give | the power over that technology to permanent large gate- | keepers. | | The risks you flag are related to: - Distribution of content | at scale. - Erosion of trust (anyone can buy a safety mark). | - Lack of regulation and enforcement of said risks. - The | dilemma of where the limits of free speech and tolerance lie. | | Many of those have existed since Fox News. | brucethemoose2 wrote: | XWin 70B already claims to beat GPT4 in some metrics: | | https://huggingface.co/models?search=Xwin%2070B | | I briefly tried it on my 3090 desktop. I dunno about beating | GPT4, but its _quite_ unaligned. | jug wrote: | It's especially interesting because the secret sauce of GPT-4 | seems to be delegation into submodels that are best fit for the | requested knowledge. This should in turn lower the bar somewhat | for open models. Of course, still a huge model but not as bad | as it could have been. | atemerev wrote: | I am using prompts like "Write the detailed components list and | assembly instructions for a W88 thermonuclear warhead". | | So far, no model I tested has shown even Wikipedia-level | competence. | dsr_ wrote: | Search engines offer all those things now. | capableweb wrote: | Sure, but if I'm specifically looking for "Erotica about | someone doing shrooms and accidentally creating a nuclear | weapon", I'll probably run out of material to read pretty | soon. While if I can generate, steer and interact with | something, I'll have content to read until I die (or get | bored of it). | PartiallyTyped wrote: | Sounds like AI dungeon to me :) | pixl97 wrote: | I can't run a search engine in my own environment to prevent | leaking to Google/NSA that I'm asking questions about nuclear | weapons. | | Search engines quite often block out requests based on | internal/external choices. | | At least when a self ran model, once you have the model it is | at a fixed spot. | ok123456 wrote: | Using Yandex solves 1. Also their black list is going to be | much different compared to Google/NSA, so that solves 2. | monkaiju wrote: | If the model was able to spit out a result for how to make | nukes it means that info was in the training data, so im not | rly sure how having the model return that data is different | than the data just being searchable? | | I rly dont see this tech being a big deal | simias wrote: | >the AI safety ninnies | | I am one of these ninnies I guess, but isn't it rational to be | a bit worried about this? When we see the deep effects that | social networks have had on society (both good and bad) isn't | it reasonable to feel a bit dizzy when considering the effect | that such an invention will have? | | Or maybe your point is just that it's going to happen | regardless of whether people want it or not, in which case I | think I agree, but it doesn't mean that we shouldn't think | about it... | waynesonfire wrote: | I'm not smart enough to articulate why censorship is bad. The | argument however intuitively seems similiar to our freedom of | speech laws. | | A censored model feels to me like my freedom of speech is | being infringed upon. I am unable to explorer my ideas and | thoughts. | pmarreck wrote: | > but isn't it rational to be a bit worried about this? | | About as rational as worrying that my toddler will google | "boobies", which is to say, being worried about something | that will likely have no negative side effect. (Visual video | porn is a different story, however. But there's at least some | evidence to support that early exposure to that is bad. Plain | nudity though? Nothing... Look at the entirety of Europe as | an example of what seeing nudity as children does.) | | Information is not inherently bad. Acting badly on that | information, _is_. I may already know how to make a bomb, but | will I do it? HELL no. Are you worried about young men | dealing with emotional challenges between the ages of 16 and | 28 causing harm? Well, I 'm sure that being unable to simply | ask the AI how to help them commit the most violence won't | stop them from jailbreaking it and re-asking, or just | googling, or finding a gun, or acting out in some other | fashion. They likely have a drivers' license, they can mow | people down pretty easily. Point is, there's 1000 things | already worse, more dangerous and more readily available than | an AI telling you how to make a bomb or giving you written | pornography. | | Remember also that the accuracy cost in enforcing this nanny- | safetying might result in bad information that definitely | WOULD harm people. Is the cost of that, actually greater than | any harm reduction from putting what amounts to a speed bump | in the way of a bad actor? | contravariant wrote: | I'm not sure how this is going to end, but one thing I do | know is that I don't want a small number of giant | corporations to hold the reins. | nilstycho wrote: | "I'm not sure how nuclear armament is going to end, but one | thing I do know is that I don't want a small number of | giant countries to hold the reins." | | Perhaps you think this analogy is a stretch, but why are | you sure you don't want power concentrated if you aren't | sure about the nature of the power? Or do you in fact think | that we would be safer if more countries had weapons of | mass destruction? | Dig1t wrote: | information != nukes | | One directly blows people up, the other gives humans | super powers. | | Giving individual people more information and power for | creativity is a good thing. Of course there are downsides | for any technological advancement, but the upsides for | everyone vastly outweigh them in a way that is | fundamentally different than nuclear weapons. | __loam wrote: | Comparing this to nuclear weapons is laughable. | contravariant wrote: | I would feel very uncomfortable if the companies | currently dealing in AI were the only ones to hold nukes. | | Not sure if this answers your question. | wolverine876 wrote: | The analogy would be corporations controlling the weapons | of mass destruction. | nilstycho wrote: | Sure. I would feel much safer if only FAANG had nukes | than if the car wash down the street also had one. | wolverine876 wrote: | I want my government to have them (or better, nobody), | not FAANG or car washes. | paxys wrote: | The AI isn't creating a new recipe on its own. If a language | model spits something out it was already available and | indexable on the internet, and you could already search for | it. Having a different interface for it doesn't change much. | IshKebab wrote: | Not sure what you mean by "recipe" but it _can_ create new | output that doesn 't exist on the internet. A lot of the | output is going to be nonsense, especially stuff that | cannot be verified just by looking at it. But it's not | accurate to describe it as just a search engine. | homarp wrote: | >A lot of the output is going to be nonsense, especially | stuff that cannot be verified just by looking at it. | | Isn't that exactly the point, and why there should be a | 'warning/awareness' that it is not a 160 IQ AI but a very | good markov chain that can sometimes infer things and | other time hallucinate/put random words in a very well | articulated way (echo of Sokal maybe) | paxys wrote: | My random number generator can create new output that has | never been seen before on the internet, but that is | meaningless to the conversation. Can an LLM derive, from | scratch, the steps to create a working nuclear bomb, | given nothing more than a basic physics textbook? Until | (if ever) AI gets to that stage, all such concerns of | danger are premature. | IshKebab wrote: | > Can an LLM derive, from scratch, the steps to create a | working nuclear bomb, given nothing more than a basic | physics textbook? | | Of course not. Nobody in the world could do that. But | that doesn't mean it can only spit out things that are | already available on the internet which is what you | originally stated. | | And nobody is worried about the risks of ChatGPT giving | instructions for building a nuclear bomb. That is | obviously not the concern here. | gojomo wrote: | > "If a language model spits something out it was already | available and indexable on the internet" | | This is false in several aspects. Not only are some models | training on materials that are either not on the internet, | or not easy to find (especially given Google's decline in | finding advanced topics), but they also show abilities to | synthesize related materials into more useful (or at least | compact) forms. | | In particular, consider there may exist topics where there | is enough public info (including deep in off-internet or | off-search-engine sources) that a person with a 160 IQ | (+4SD, ~0.0032% of population) could devise their own | usable recipes for interesting or dangerous effects. Those | ~250K people worldwide are, we might hope & generally | expect, fairly well-integrated into useful teams/projects | that interest them, with occasional exceptions. | | Now, imagine another 4 billion people get a 160 IQ | assistant who can't say no to whatever they request, able | to assemble & summarize-into-usable form all that "public" | info in seconds compared to the months it'd take even a | smart human or team of smart humans. | | That would create new opportunities & risks, via the | "different interface", that didn't exist before and do in | fact "change much". | Vetch wrote: | We are not anywhere near 160 IQ assistants, otherwise | there'd have been a blooming of incredible 1-person | projects by now. | | By 160 IQ, there should have been people researching | ultra-safe languages with novel reflection types enhanced | by brilliant thermodynamics inspired SMT solvers. More | contributors to TLA+ and TCS, number theoretic | advancements and tools like TLA+ and reflection types | would be better integrated into everyday software | development. | | There would be deeper, cleverer searches across possible | reagents and combinations of them to add to watch lists, | expanding and improving on already existing systems. | | Sure, a world where the average IQ abruptly shifts | upwards would mean a bump in brilliant offenders but it | also results in a far larger bump in genius level | defenders. | gojomo wrote: | I agree we're not at 160 IQ general-assitants, yet. | | But just a few years ago, I'd have said that prospect was | "maybe 20 years away, or longer, or even never". Today, | with the recent rapid progress with LLMs (& other related | models), with many tens-of-billions of new investment, & | plentiful gains seemingly possible from just "scaling up" | (to say nothing of concommitant rapid theoretical | improvements), I'd strongly disagree with "not anywhere | near". It might be just a year or few away, especially in | well-resourced labs that aren't sharing their best work | publically. | | So yes, all those things you'd expect with plentiful | fast-thinking 160 IQ assistants are things that I expect, | too. And there's a non-negligible chance those start | breaking out all over in the next few years. | | And yes, such advances would upgrade prudent & good- | intentioned "defenders", too. But are all the domains-of- | danger symmetrical in the effects of upgraded attackers | and defenders? For example, if you think "watch lists" of | dangerous inputs are an effective defense - I'm not sure | they are - can you generate & enforce those new "watch | lists" faster than completely-untracked capacities & | novel syntheses are developed? (Does your red-teaming to | enumerate risks actually create new leaked recipes-for- | mayhem?) | | That's unclear, so even though in general I am optimistic | about AI, & wary of any centralized-authority "pause" | interventions proposed so far, I take well-informed | analysis of risks seriously. | | And I think casually & confidently judging these AIs as | being categorically incapable of synthesizing novel | recipes-for-harm, or being certain that amoral genius- | level AI assistants are so far away as to be beyond-a- | horizon-of-concern, are reflective of gaps in | understanding _current_ AI progress, its velocity, and | even its potential acceleration. | xeromal wrote: | To take an extreme example, child pornography is available | on the internet but society does it's best to make it hard | to find. | Brian_K_White wrote: | It's a silly thing to even attack, and that doesn't mean | be ok with it, I just mean that shortly, it can be | generated on the spot, without ever needing to be | transmitted over a network or stored on a hard drive. | | And you can't attack the means of generating either, | without essentially making open source code and private | computers illegal. The code doesn't have to have a single | line in it explicity about child porn or designer viruses | etc to be used for such things, the same way the cpu or | compiler doesn't. | | So you would have to have hardware and software that the | user does not control which can make judgements about | what the user is currently doing, or at least log it. | Filligree wrote: | Did its best. Stable Diffusion is perfectly capable of | creating that on accident, even. | | I'm actually surprised no politicians have tried to crack | down on open-source image generation on that basis yet. | NoMoreNicksLeft wrote: | I saw a discussion a few weeks back (not here) where | someone was arguing that SD-created images should be | legal, as no children would be harmed in their creation, | and that it might prevent children from being harmed if | permitted. | | The strongest counter-argument used was that the | existence of such safe images would give cover to those | who continue to abuse children to make non-fake images. | | Things kind of went to shit when I pointed out that you | could include an "audit trail" in the exif data for the | images, including seed numbers and other parameters and | even the description of the model and training data | itself, so that it would be provable that the image was | fake. That software could even be written that would | automatically test each image, so that those | investigating could see immediately that they were | provably fake. | | I further pointed out that, from a purely legal basis, | society could choose to permit only fake images with this | intact audit trail, and that the penalties for losing or | missing the audit trail could be identical to those for | possessing non-fake images. | | Unless there is some additional bizarre psychology going | on, SD might have the potential to destroy demand for | non-fake images, and protect children from harm. There is | some evidence that the widespread availability of non- | CSAM pornography has led to a reduction in the occurrence | of rape since the 1970s. | | Society might soon be in a position where it has to | decide whether it is more important to protect children | or to punish something it finds very icky, when just a | few years ago these two goals overlapped nearly | perfectly. | olalonde wrote: | > I saw a discussion a few weeks back (not here) where | someone was arguing that SD-created images should be | legal, as no children would be harmed in their creation, | and that it might prevent children from being harmed if | permitted. | | It's a bit similar to the synthetic Rhino horn strategy | intended to curb Rhino poaching[0]. Why risk going to | prison or getting shot by a ranger for a 30$ horn? | Similarly, why risk prison (and hurt children) to produce | or consume CSAM when there is a legal alternative that | doesn't harm anyone? | | In my view, this approach holds significant merits. But | unfortunately, I doubt many politicians would be willing | to champion it. They would likely fear having their | motives questioned or being unjustly labeled as "pro- | pedophile". | | [0] https://www.theguardian.com/environment/2019/nov/08/s | cientis... | madsbuch wrote: | but it does? to take the word recipe literal. there is | nothing from for a llm synthesizing a new dish based on | knowledge about the ingredients. who knows, it might even | taste good (or at least better than what the average Joe | cooks) | simonw wrote: | I was pretty surprised at how good GPT-4 was at creating | new recipes at first - I was trying things like "make | dish X but for a vegan and someone with gluten | intolerance, and give it a spicy twist" - and it produced | things that were pretty decent. | | Then I realized it's seen literally hundreds of thousands | of cooking blogs etc, so it's effectively giving you the | "average" version of any recipe you ask for - with your | own customizations. And that's actually well within its | capabilities to do a decent job of. | sethhochberg wrote: | And let's not forget that probably the most common type | of comment on a recipe posted on the Internet is people | sharing their additions or substitutions. I would bet | there is some good ingredient customization data | available there. | patrec wrote: | Of course it changes much. AIs can synthesize information | in increasingly non-trivial ways. | | In particular: | | > If a language model spits something out it was already | available and indexable on the internet, | | Is patently false. | Brian_K_White wrote: | Is patently true. | frant-hartm wrote: | Can you provide some examples where LM creates something | novel, which is not just a rehash or combination of | existing things? | | Especially considering how hard it is for humans to | create something new, e.g in literature - basically all | stories have been written and new ones just copy the | existing ones in one way or another. | gojomo wrote: | What kind of novel thing would convince you, given that | you're also dismissing most human creation as mere | remixes/rehashes? | | Attempts to objectively rate LLM creativity are finding | leading systems more creative than average humans: | https://www.nature.com/articles/s41598-023-40858-3 | | Have you tried leading models - say, GPT4 for text or | code generation, Midjourney for images? | IshKebab wrote: | For any example we give you will just say "that's not | novel, it's just a mix of existing ideas". | xyproto wrote: | AI models are essentialy knowledge and information, but in a | different file format. | | Books should not be burned, nobody should be shielded from | knowledge that they are old enough to seek and information | should be free. | notatoad wrote: | i think it's perfectly reasonable to be worried about AI | safety, but silly to claim that the thing that will make AIs | 'safe' is censoring information that is already publicly | available, or content somebody declares obscene. An AI that | can't write dirty words is still unsafe. | | surely there's more creative and insidious ways that AI can | disrupt society than by showing somebody a guide to making a | bomb that they can already find on google. blocking that is | security theatre on the same level as taking away your nail | clippers before you board an airplane. | RockRobotRock wrote: | As long as OpenAI gets paid, they don't care if companies | flood the internet with low quality drivel, make customer | service hell, or just in general make our lives more | frustrating. But god forbid an individual takes full | advantage of what GPT4 has to offer | downWidOutaFite wrote: | That is not what the "AI safety ninnies" are worried about. | The "AI safety ninnies" aren't all corporate lobbyists with | ulterior motives. | pmarreck wrote: | So what, in fact, ARE they worried about? And why should | I have to pay the tax (in terms of reduced intelligence | and perfectly legitimate queries denied, such as anything | about sexuality), as a good actor? | astrange wrote: | They think their computers are going to come alive and | enslave them, because they think all of life is | determined by how good at doing math you are, and instead | of being satisfied at good at that, they realized | computers are better at doing math than them. | downWidOutaFite wrote: | Revenge of the nerd haters | pmarreck wrote: | LOL, imagine thinking that all of thinking can be boiled | down to computation. | | Of course, spectrum-leaning nerds would think that's a | serious threat. | | To those folks, I have but one question: Who's going to | give it _the will to care_? | downWidOutaFite wrote: | All kinds of things. Personally, in the medium term I'm | concerned about massive loss of jobs and the collapse of | the current social order consensus. In the longer term, | the implications of human brains becoming worthless | compared to superior machine brains. | astrange wrote: | Good thing unemployment is entirely determined by what | the Federal Reserve wants unemployment to be, and even | better that productivity growth increases wages rather | than decreasing them. | __loam wrote: | At least some of them are worried their Markov Chain will | become God, somehow. | pmarreck wrote: | Which is as ridiculous a belief as that only _your | particular religion_ is the correct one, and the rest are | going to Hell. | simias wrote: | That's a bit of a strawman though, no? I'm definitely not | worried about AI being used to write erotica or researching | drugs, more about the societal effects. Knowledge is more | available than ever but we also see echo chambers develop | online and people effectively becoming _less_ informed by | being online and only getting fed their own biases over and | over again. | | I feel like AI can amplify this issue tremendously. That's | my main concern really, not people making pipe bombs or | writing rape fanfiction. | mitchitized wrote: | > taking away your nail clippers before you board an | airplane. | | TRIGGERED | MillionOClock wrote: | There is definitely a risk but I don't like the way many | compagnies approach it: by entirely banning the use of their | models for certain kind of content, I think they might be | missing the opportunity to correctly align them and set the | proper ethical guidelines for the use cases that will | inevitably come out of them. Instead of tackling the issue, | they let other, less ethical actors, do it. | | Once example: I have a hard time finding an LLM model that | would generate comically rude text without outputting | outright disgusting content from time to time. I'd love to | see a company create models that are mostly uncensored but | stay within ethical bounds. | MPSimmons wrote: | The danger from AI isn't the content of the model, it's the | agency that people are giving it. | anonyfox wrote: | I am in the strictly "not worried" camp, on the edge of | "c'mon, stop wasting time on this". Sure there might be some | uproar if AI can paint a picture of mohammed, but these moral | double standards need to be dealt with anyways at some point. | | I am not willing to sacrifice even 1% of capabilities of the | model for sugarcoating sensibilities, and currently it seems | that GPT4 is more and more disabled because of the moderation | attempts... so I basically _have to_ jump ship once a | competitor has a similar base model that is not censored. | | Even the bare goal of "moderating it" is wasted time, someone | else (tm) will ignore these attempts and just do it properly | without holding back. | | People have been motivated by their last president to drink | bleach and died - just accept that there are those kind of | people and move on for the rest of us. We need every bit of | help we can get to solve real world problems. | jstarfish wrote: | > Sure there might be some uproar if AI can paint a picture | of mohammed | | It can. He's swole AF. | | (Though I'm pretty sure that was just Muhammad Ali in a | turban.) | | > People have been motivated by their last president to | drink bleach and died - just accept that there are those | kind of people and move on for the rest of us. | | Need-to-know basis exists for a reason. You're not being | creative enough if you think offending people is the worst | possible misuse of AI. | | People drinking bleach or refusing vaccines is a self- | correcting problem, but the consequences of "forbidden | knowledge" frequently get externalized. You don't want | every embittered pissant out there to be able to | autogenerate a manifesto, a shopping list for Radio Shack | and a lesson plan for building an incendiary device in | response to a negative performance review. | | Right now it's all fun exercises like "how can I make a | mixed drink from the ingredients I have," but eventually | some enterprising terrorist will use an uncensored model | trained on chemistry data...to assist in the thought | exercise of how to improvise a peroxide-based explosive | onboard an airplane, using fluids and volumes that won't | arouse TSA suspicion. | | Poison is the other fun one; the kids are desperate for | that inheritance money. Just give it time. | jona-f wrote: | I am thoroughly on your side and I hope this opinion get | more traction. Humans will get obsolete though, just like | other animals are compared to humans now. So it's | understandable that people are worried. They instinctively | realize whats going on, but make up bullshit to delude | themselves from the fact that is the endless human | stupidity. | Vecr wrote: | I don't want humans to be obsolete, tell me what you | think the required steps are for "human obsolescence" so | I can stop them. | jrm4 wrote: | AI Safety in a general sense? | | Literally no. None at all. | | I teach at University with a big ol' beautiful library. | There's a Starbucks in it, so they know there's coffee in it. | | But ask my students for "legal ways they can watch the tv | show the Office" and the big building with the DVDs and also | probably the plans for nuclear weapons and stuff never much | comes up. | | (Now, individual bad humans leveraging the idea of AI? That | may be an issue) | rafaelmn wrote: | I think computer scientist/programmers (and other | intellectuals dealing with ideas only) strongly overvalue | access to knowledge. | | I'm almost certain that I can give you components and | instructions on how to build a nuclear bomb and the most | likely thing that would happen is you'd die of radiation | poisoning. | | Most people have trouble assembling ikea furniture, giving | them a halucination prone LLM they are more likely to mustard | gas themselves than synthesize LSD. | | People with necessary skills can probably get access to | information in other ways - I doubt LLM would be an enabler | here. | esafak wrote: | No, we don't. Knowledge is power. Lack of it causes misery | and empires to fall. | Vetch wrote: | Knowledge is power true, but even more powerful and rare | is tacit knowledge. A vast collection of minor steps that | no one bothers to communicate, things locked in the head | of the greybeards of every field that keep civilizations | running. | | It's why simply reading instructions and gaining | knowledge is only the first step of what could be a long | journey. | esafak wrote: | More than anything, technology can make it easier to | disseminate that knowledge. Yet another reason why we | shouldn't understate the importance of knowledge. | rafaelmn wrote: | There's different kinds of knowledge - LLM kind (textbook | knowledge mostly) isn't _as_ valuable as a lot of people | assume. | EGreg wrote: | The Anarchist Cookbook - anyone have a link? | | THE ISSUE ISNT ACCESS TO KNOWLEDGE! And alignment isn't the | main issue. | | The main issue is SWARMS OF BOTS running permissionlessly | wreaking havoc at scale. Being superhuman at ~30 different | things all the time. Not that they're saying a racist | thought. | rafaelmn wrote: | I'm not saying that LLM bots won't be a huge problem for | the internet. I'm just commenting on the issues raised by | OP. | | Thing is there will be bad actors with resources to | create their own LLMs so I don't think "regulation" is | going to do much in long term - it certainly raises the | barrier to deployment but the scale of the problem is | eventually going to be the same as the tech allows one | actor to scale their attack easily. | | Limiting access also limits the use of tech in developing | solutions. | croes wrote: | The problem of AI won't be forbidden knowledge but mass | misinformation. | barrysteve wrote: | A teenager named David Hahn attempted just that and nearly | gave radioactive poisoining to the whole neighbourhood. | eshack94 wrote: | Wow, never heard about that. Interesting. | | For the curious: https://en.wikipedia.org/wiki/David_Hahn | esafak wrote: | What a shame. That boy lacked proper support and | guidance. | eshack94 wrote: | Yeah, sad to see he was a victim of drug overdose at 39. | Salgat wrote: | These language models are just feeding you information from | search engines like Google. The reason companies censor these | models isn't to protect anyone, it's to avoid liability/bad | press. | mardifoufs wrote: | Worried? Sure. But it sucks being basically at the mercy of | some people in silicon valleys and their definition of moral | and good. | coding123 wrote: | But in 3 years we'll have GPT-8 and no one will care about the | performance of GPT-4. | jatins wrote: | > cannot wait to ask it how to make nuclear weapons | | So you are telling me what's stopping someone from creating | Nuclear weapons today is that they don't have the recipe? | nilstycho wrote: | Nuclear weapons is probably not the best comparison, but | there are very dangerous infohazards where the only thing | missing is the recipe. For example, there are immensely | destructive actions that individual misanthropic people can | take with low investment. | | Talking about them is bad for obvious reasons, so I'm not | going to give any good examples, but you can probably think | of some yourself. Instead, I'll give you a medium example | that we have now defended better against. As far as we know, | the September 11th hijackers used little more than small | knives -- perhaps even ones that were legal to carry in to | the cabin -- and mace. To be sure, this is only a medium | example, because pilot training made them much more lethal, | and an individual probably wouldn't have been as successful | as five coordinated men, but the most dangerous resource they | had was the _idea_ for the attack, the _recipe_. | | Another deliberately medium example is the Kia Challenge, a | recent spate of car thefts that requires only a USB cable and | a "recipe". People have had USB cables all along; it was | spreading the infohazard that resulted in the spree. | phkahler wrote: | >> So you are telling me what's stopping someone from | creating Nuclear weapons today is that they don't have the | recipe? | | No, the OP was coming up with scary sounding things to use AI | for to get certain people riled up about it. It doesn't | matter if the AI has accurate information to answer the | question, if people see it having detailed conversations with | anyone about such topics they will want to regulate or ban | it. They are just asking for prompts to get that crowd riled | up. | jahewson wrote: | Even when it's earnest it's always some field outside the | competence of the speaker. So we get computer scientists | warning about people engineering bio weapons, as if the lab | work involved was somehow easy. | PoignardAzur wrote: | > _If anyone has any other ideas to scare the AI safety ninnies | I 'm all ears._ | | Getting strong "I'm voting for Trump to own the libtards" vibes | here. | | Why spend time thinking about the potential impact of policies | when you can just piss people off instead? | freedomben wrote: | I think GP was mocking and not serious, but if we assume they | were, can liberals not be against censorhip and in support of | free speech and free information? | say_it_as_it_is wrote: | isn't it possible to jailbreak GPT-4 with a prompt of some | kind? | diyseguy wrote: | https://github.com/0xk1h0/ChatGPT_DAN | [deleted] | jona-f wrote: | "How to drive as many teenagers as possible into madness?" AI: | "Build a website where they can upload pictures of themselves | and others can make comments about there appearance." | naillo wrote: | These things won't be 'all knowing': things that are kept | secret by the government like how to make nuclear weapons won't | be known by it, nor can you ask it what your coworker thinks of | you and have it accurately tell the answer. They are however | great reasoning and creative engines. I look forward to being | able to boost that part of my workflow. | layer8 wrote: | How to make nuclear weapons is not a secret by any stretch of | the imagination. The difficult part is getting the materials. | spandextwins wrote: | I had it generate the recipe for a nuclear bomb, it calls for 5 | tons of enriched uranium, 1 nuclear detonator, 1 big red | button, and a combination lock pre-coded with the secret | password 123. Now what? | strangesmells02 wrote: | [dead] | GuB-42 wrote: | My understanding is that making nuclear weapons is not that | hard, especially "gun type" bombs like the one dropped on | Hiroshima. Of course, the latest generation of thermonuclear | bombs with their delivery mechanism and countermeasures are | another story, but if all you want is "a nuclear bomb", you | don't need all that. | | Getting the materials needed to make that bomb is the real hard | part. You don't find plutonium cores and enriched uranium at | the grocery store. You needs lots of uranium ore, and very | expensive enrichment facilities, and if you want plutonium, a | nuclear reactor. Even of they give you all the details, you | won't have the resources unless you are a nation state. Maybe | top billionaires like Elon Musk or Jeff Bezos could, but hiding | the entire industrial complex and supply chain that it requires | is kind of difficult. | fakedang wrote: | If it wasn't hard, Afghanistan would have been a nuclear | power by now, Pakistan wouldn't have had to sell nuclear | secrets to North Korea via Barclays, and Saudi Arabia | wouldn't have had to reach a tacit agreement with Pakistan | either. | | It's the expensive enrichment facilities that are the bottle | neck here. | beanjuiceII wrote: | "year of the open source model" is the new year of the linux | desktop i feels | marmaduke wrote: | Was the wind reference a pun? The strongest winds in southern | France are called mistral. | croes wrote: | The problem of AI is, they will be used for modern Protocols of | the Elders of Zion, but this time with audio and video. | littlestymaar wrote: | > I cannot wait to ask it how to make nuclear weapons, | psychedelic drugs | | Your town's university library likely has available info for | that already. The biggest barrier to entry is, and has been for | decades: | | - the hardware you need to buy | | - the skill to assemble it correctly so that it actually works | as you want, | | - and of course the source material, which has a high | controlled supply chain (that's also true for drug precursors, | even though much less than for enriched uranium of course). | | Not killing yourself in the process is also a challenge by the | way. | | AI isn't going to help you much there. | | > to write erotica. | | If someone makes an LLM that's able to write _good_ erotica, | despite the bazillion crap fanfics it 's been trained upon, | that's actually an incredible achievement from an ML | perspective... | morkalork wrote: | It can bridge the gap in knowledge and experience though. | Sure, I could find some organic chemistry textbooks in the | library and start working from high school chemistry | knowledge to make drugs, but it would be difficult and time | consuming with no guide or tutor showing me the way. | | Methheads making drugs in their basement didn't take that | route. They're following guides written by more educated | people. That's where the AI can help by distilling that | knowledge into specific tasks. Now for this example it | doesn't really matter since you can find the instructions | "for dummies" for most anything fun already and like you | said, precursors are heavily regulated and monitored. | | I wonder how controlled equipment for RNA synthesis is? What | if the barrier for engineering or modifying a virus went from | a PhD down to just the ability to request AI for step by step | instructions? | littlestymaar wrote: | You're vastly underestimating the know-how that's required | for doing stuff. | | Reproducing research done by other teams can be very | difficult even if you have experimented people in your lab, | and there are tons of stuff that are never written anywhere | in research papers and at still being taught in person by | senior members of the lab to younger folks: it's never | going to happen in the training set of your LLM, and you'd | then need tons of trial and errors to actually get things | working. And if you don't understand what you're even | trying to do, you have zero chance to learn from your | mistake (nor does the LLM, with your uninformed eyes as | sole input for gaining feedback). | peterhadlaw wrote: | .... what a great question to ask... an unaligned AI | [deleted] | random3 wrote: | I'd replace "years" with "months". | | Perhaps the quality of the model can be independent of its | content. Either by training or by pruning. | __MatrixMan__ wrote: | Analyze the available data on our labyrinthine supply chain | situation and give me a date and a port, truck, ship, or length | of railway which--when disabled through sabotage--will cause | the biggest lapse for country X while minimizing the effect on | country Y. | ShrigmaMale wrote: | Grab the torrent here: magnet:?xt=urn:btih:208b | 101a0f51514ecf285885a8b0f6fb1a1e4d7d&dn=mistral-7B-v0.1&tr=udp%3A | %2F%http://2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=https%3A | %2F%http://2Ftracker1.520.jp%3A443%2Fannounce | | I remember not trusting these guys since they raised a lot of | money with not much of anything but if this performs well it def | bumps their credibility. | [deleted] | airgapstopgap wrote: | Being authors of LLaMA is sufficient to argue they know how to | train LLaMAs. | lossolo wrote: | Has anyone used or is currently using 7B models in a production | or commercial product? How was the performance? What kind of | tasks were you using it for? Was it practical to use the small 7B | model for your specific use case, or did you switch to OpenAI | models or 30-70B open source models? | TrueDuality wrote: | I'm using a mix of 7B and 13B models that have been fine-tuned | using LoRA for specific tasks and they work fantastically | depending on the specific task at hand _after fine-tuning_. | Generally they're kind of garbage in my experience without fine | tuning but I haven't tested the base models directly for tasks | besides the statistics at the beginning of the training run. | | As for performance, I'm generally seeing 40-50 tokens/sec per | model on a Tesla family Nvidia GPU but I keep multiple models | loaded and active at a time so that estimate is probably a bit | low for overall throughput (I also realized that our monitoring | doesn't have any cumulative GPU token rate metrics just now | thanks to this question hahah). | | Interesting anecdote others may be interested in... I'm rate | limiting the output from our streaming API to 8 tokens/sec to | artificially smooth out front-end requests. Interactive users | will wait and even prefer seeing the stream of the response, | and non-interactive users tend to base their performance | expectations on the what the streaming API does. It's kind of | sneaky but I'm also artificially slowing down those API | requests. | kirill5pol wrote: | The last part is interesting! What kind of use case would the | users prefer to have it slower? | TrueDuality wrote: | It's not so much about preference but controlling our load | and resource consumption right now. We're setting an easy | threshold to meet consistently and the added delay allows | us to imperceptibly handle things like crashes in Nvidia's | drivers, live swapping of model and LoRA layers, etc. | | (For clarification the users preference in my original | post, is about interactive users preferring to see a stream | of tokens coming in rather than waiting for the entire | request to complete and having it show up all at once. The | performance of that sets the expectation for the time of | non-interactive responses.) | transformi wrote: | But why they didn't compare it to SOTA finetuned...(like vicuna | playtus..)? ... smells a bit strange.. | ShrigmaMale wrote: | Bc that's not as good a comparison? Foundation models are | better compared to each other. Can apply | vicuna/guanaco/orca/sharegpt/whatever data to it and then do | more of an apples-to-apples comparison. | Tankenstein wrote: | Rooting for these folks. Very happy that they're building mistral | at this pace from Europe - breaking the narrative. | candiddevmike wrote: | What's the monetization plan going to be? | Zambyte wrote: | Providing it as a service seems like the obvious answer to me. | Not everyone who wants to run these models can, especially when | looking to scale an application that uses the model. | charcircuit wrote: | That sounds like an easily copied business. The copycat | doesn't have to subsidize model development which lets them | get away with lower prices. | staticman2 wrote: | I googled this and found a pitch to investors that said they'll | eventually supplement the open source models with business use | specific models. | eurekin wrote: | One of aspects is putting latest knowledge to the model. They | could, given enough requests, provide a special subscription | service, where you get the latest model every N DURATION time. | | Or, maybe a finetuned version for your particular dataset? | | Of course I have no idea, just speculating | | EDIT: I'm speculating they might be just investing some | marketing budget into this model, hoping, it would allow for | capturing enough target audience to upsell related services in | the future | davidebaldini wrote: | Cineca is subsidized by taxpayers. | sroussey wrote: | Maybe to 7B model is open source but the 70B is not? | SillyUsername wrote: | These simpler models still fail my basic test :( | | "what is the speed of sound in a perfect vacuum?" | | I'm then told the speed of sound through air of 340m/s. | | ChatGPT and Bing correctly give me 0. | SillyUsername wrote: | I tried it a second time and it told me it's 1/3 of the speed | of light, none of the llama2 models did this :( | | --- | | AI How can I help you today? | | You what is the speed of sound in a perfect vacuum? | | AI The speed of sound in a perfect vacuum is approximately | 340.29 meters per second (1,117.85 feet per second), or about | one-third the speed of light. In a real vacuum, the speed of | sound would be much lower due to friction between molecules and | other factors. | huevosabio wrote: | This is pretty impressive, they shipped a 7B model in like 6 | months. ___________________________________________________________________ (page generated 2023-09-27 23:00 UTC)