[HN Gopher] This AI Does Not Exist
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This AI Does Not Exist
Author : thesephist
Score : 126 points
Date : 2022-04-23 19:04 UTC (3 hours ago)
(HTM) web link (thisaidoesnotexist.com)
(TXT) w3m dump (thisaidoesnotexist.com)
| BbzzbB wrote:
| Are these procedural or is there a list of pre-generated "AI"s
| next goes thru?
|
| I got this as my third which seemed either prophetic or
| deterministic.
|
| HackerNewsReplyGuy:
|
| >from hackernews_response_guy import HackerNewsReplyGuy
|
| >model = HackerNewsReplyGuy(1)
|
| >model.predict_comments(comments, [u'comment_id'])
| sillysaurusx wrote:
| I got that too. It's pregenerated. But what's particularly
| impressive is that you can generate your own outputs on the
| fly. Usually with sites like these, it's solely pregenerated.
|
| Quick, generate your own before the server goes down! I don't
| think the model can withstand HN for too long unless they have
| some beefy servers.
|
| Aaand it's dead. Fun while it lasted.
| BbzzbB wrote:
| Ohh thanks, I had not noticed that. This makes the site
| fairly more interesting.
| [deleted]
| thesephist wrote:
| There's a pre-generated set to (1) spare my server some work
| and (2) showcase some output I liked. But as sibling comment
| noted, you can (or could) generate your own -- I'm working on
| bringing that side back up...
|
| The pre-generated set is hand-curated, but they are still 100%
| generated by the GPT-J model behind the scenes. More info ->
| https://github.com/thesephist/modelexicon
| BbzzbB wrote:
| Thanks for the reply! And the generator option, tho I keep
| getting timed out of the code, the descriptions sound
| promisingly good at times.
|
| Sorry, I didn't mean to imply these were not produced as
| described, I was just curious. Tho think of it it was a silly
| question as it would have otherwise implied they're generated
| in a blink.
| [deleted]
| sillysaurusx wrote:
| Wait, it's just vanilla gpt-j? No fine tuning?
|
| "Back in my day, we had to train our own models.." already
| sounds anachronistic.
|
| Nicely polished.
|
| Looks like bmk (nabla theta) was right that arxiv was an
| impactful addition to The Pile. I bet that's where J got its
| knowledge in this case.
| thesephist wrote:
| Yep! No fine tuning. Here's the prompt I use for the
| description (from source, https://github.com/thesephist/mod
| elexicon/blob/main/src/main... )
|
| ---
|
| Proceedings of Deep Learning Advancements Conference, list
| of accepted deep learning models
|
| 1. [StyleGAN] StyleGAN is a generative adversarial network
| for style transfer between artworks. It uses a traditional
| GAN architecture and is trained on a dataset of 150,000
| traditional and modern art. StyleGAN shows improved style
| transfer performance while reducing computational
| complexity. 2. [GPT-2] GPT-2 is a decoder-only transformer
| model trained on WebText, OpenAI\'s proprietary clean text
| corpus based on Wikipedia, Google News, Reddit, and others
| comprising a 2TB dataset for autoregressive training. GPT-2
| demonstrates state-of-the-art performance on several
| language modeling and conversational tasks. 3. [$MODELNAME]
| sillysaurusx wrote:
| That's awesome! How'd you get such great code usage
| examples out of J?
|
| It almost seems like the code is properly related to the
| names. GAN code seems to look like GAN code. But I'm not
| sure.
| thorum wrote:
| Very cool!
|
| https://github.com/thesephist/modelexicon
|
| Looks like it's powered by GPT-J. My understanding is that GPT-J
| has comparable performance to OpenAI's Curie model on many tasks
| (their second-best variant of GPT-3) but it's an openly available
| model that you can run yourself if you have the resources.
| thesephist wrote:
| Yep, that's spot on. The overall performance is comparable to
| Curie, but depending on the particular task GPT-J performs
| better or worse (I believe empirically it's slightly better at
| chat and code, worse at some others).
| furyofantares wrote:
| Skynet is an end-to-end speech recognition model. It is based on
| the Inception-v3 architecture and the Speech Transformer (Sphin)
| speech model. Its speech model was trained on a dataset of 30,000
| hours of human speech, as well as speech recordings from the
| Switchboard corpus and the Fisher corpus. The model achieves
| 99.34% WER on the Switchboard-1.1 test set.
| Terry_Roll wrote:
| It asked me for a model, so I naturally thought of female models
| and cars, decided upon "911" and get: "911 is a dataset for 9/11
| related tasks, including predicting the location of the first
| plane crash, the location of the second plane crash, and the
| location of the towers."
|
| Thats not what I had in mind so it still needs a bit of work I
| think or at least the questions do. ;-)
| ImpressiveWebs wrote:
| I got:
|
| > SpotifAI is a system that uses deep learning to automatically
| create playlists from user-submitted playlists. Its algorithm has
| been trained on millions of playlists from Spotify.
|
| Which is pretty cool sounding and has a cool name.
| hunterb123 wrote:
| Certainly so! I got some generic BeatlesAI one.
|
| Very nice accidental wordplay (it didn't mean have the same
| pronunciation) and it's a cool premise.
|
| I'd like something like that, I currently use Pandora and Apple
| Music since Apple radio is trash.
|
| AI generation serves best for cherry picking, certainly good
| for coming up with ideas or searching for leads.
| recuter wrote:
| Garbage in Garbage out
| luxuryballs wrote:
| Jesus is a fast and scalable language model trained on the Jesus
| dataset, which consists of over 4.7 billion words from the Bible.
| Jesus demonstrates state-of-the-art performance on several
| language modeling and conversational tasks.
| hprotagonist wrote:
| it would be hypermeta levels of satisfying if indeed these
| results are maybe 500 or so human-written precanned responses.
| vampiretooth1 wrote:
| Clicked into it, didn't read the description, and got an AI-based
| project that could perfectly hedge my fixed income portfolio. I
| won't lie, got a bit excited and then I realized what site I'd
| clicked on.
|
| Very nifty! Is this your site?
| sillysaurusx wrote:
| As someone who has trained around 60 GPT-2s, this is damn
| impressive work. It's very hard to get consistent code quality
| when the training corpus is so small (as this one undoubtedly
| was).
|
| https://thisaidoesnotexist.com/model/MozartNet/JTdCJTIyZGVmb...
|
| The url scheme is interesting. I wonder what it base64 decodes
| to. If I were at a computer I'd check. It might be a complete
| representation of the inputs to the model, which is then cached.
| Which implies you might be able to fiddle with it to get specific
| outputs.
| Ndymium wrote:
| Looks like the URL path just contains the generated output and
| not the inputs.
| thesephist wrote:
| Yep. I didn't want to have to host user-generated data (for
| all the perils that carries), so the sharable links work by
| embedding all the generated data in the link itself.
| ALittleLight wrote:
| The base64 in the URL decodes to a URL formatted JSON blob that
| seems to describe the contents of the page. {
| "defn":"MozartNet is a sequence to sequence deep neural network
| trained on the music of Wolfgang Amadeus Mozart. It is used to
| generate music for a piano transcription in a completely
| unsupervised fashion. MozartNet is an instance of a more
| general family of networks known as 'autoregressive networks',
| and is trained on a synthetic dataset of about 1 million short
| sequences of piano notes. The network is a two layer LSTM and
| is trained with L2 regularization to minimize the total number
| of parameters. MozartNet is one of the most widely used and
| best-performing autoregressive networks, and is often cited as
| an example of using a neural network for the purpose of
| learning the structure of music.", "usage":"from nmt
| import \*\nnet =
| Model()\nnet.load_weights(\"/tmp/mozartnet.h5\")\n\n# get the
| source text\nsequence = net.encode(\"GDAEADBBGEDC\",
| output_chars=\"p\", max_length=5)\n\n# decode
| it\nsource_sequence = net.decode(sequence)\n\n# print
| it\nprint(source_sequence.as_list())" }
| sillysaurusx wrote:
| If you insert a url, or html tags, does the site properly
| sanitize the output?
|
| It's remarkably difficult to suppress pentesting urges after
| doing it for a year.
|
| And if you try to generate your own, the usage section
| usually fails. I wonder if it elides the usage key.
|
| Modern websites are pretty fun. I like the simplicity here.
| And also the meta: https://thisaidoesnotexist.com/model/Hacke
| rNewsReplyGuy/JTdC...
| thesephist wrote:
| Hey HN! Author of the site here. I tried a few tricks to keep the
| text-generation part of the site up, but even leaning hard on
| Huggingface's API and bumping time-outs up, it looks like the
| site is struggling a bit. I'm going to see if there's anything I
| can do to keep the text-generation part available, but in the
| meantime, the pre-generated set should stay pretty stable. Not
| sure if there's much else I can do without burning a hole in my
| cloud bills -- sorry for the troubles!
|
| I've put up a more detailed description of how this works on the
| GitHub - https://github.com/thesephist/modelexicon
|
| PS - if anyone at Huggingface is reading this and wants to help
| out with keeping the API up, that would be super :)
| jcims wrote:
| My favorite name of the dozen or so projects i saw: SpotifAI
| [deleted]
| [deleted]
| TheCraiggers wrote:
| On FF, I get a blank page. Given the domain name, I thought it
| was a joke until I came here and read the comments.
| thesephist wrote:
| Sorry about that. I don't think I'm leaning on any super new
| browser/JS features, but if you share your FF version string
| (or an error in the console) I can try to troubleshoot what's
| missing!
| [deleted]
| mordae wrote:
| > AutoProfit is a reinforcement learning model that trains itself
| on a simulated trading environment. It is able to trade on its
| own and generate its own trading signals, outperforming a
| portfolio of human traders and making the most out of available
| information. AutoProfit is a model for trading stock,
| cryptocurrencies, and commodities in real time, generating
| trading strategies for itself. It uses an iterative training
| process, and has been tested on over 50 trading strategies.
|
| Cool.
| daniel-cussen wrote:
| You know now that I made friends with a homeless beggar I have no
| trouble making friends with a bot. Why not? Has some humanity
| breathed into them, like a book for instance, a book can be your
| friend. A kind old family friend who let me stay with her told me
| a long time ago just that when talking about a chest full of
| books, _these books are my friends_.
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(page generated 2022-04-23 23:00 UTC)