[HN Gopher] Anthropic AI ___________________________________________________________________ Anthropic AI Author : vulkd Score : 75 points Date : 2021-05-28 17:25 UTC (5 hours ago) (HTM) web link (www.anthropic.com) (TXT) w3m dump (www.anthropic.com) | gavanwilhite wrote: | This looks quite promising! | mark_l_watson wrote: | I agree! Love the public benefit aspect of Anthropic. | Animats wrote: | Their paper "Concrete problems in AI safety"[1] is interesting. | Could be more concrete. They're run into the "common sense" | problem, which I sometimes define, for robots, as "getting | through the next 30 seconds without screwing up". They're trying | to address it by playing with the weighting in goal functions for | machine learning. | | They write "Yet intuitively it seems like it should often be | possible to predict which actions are dangerous and explore in a | way that avoids them, even when we don't have that much | information about the environment." For humans, yes. None of the | tweaks on machine learning they suggest do that, though. If your | constraints are in the objective function, the objective function | needs to contain the model of "don't do that". Which means you've | just moved the common sense problem to the objective function. | | Important problem to work on, even though nobody has made much | progress on it in decades. | | [1] https://arxiv.org/pdf/1606.06565.pdf | ansk wrote: | I can't find any mention of who currently comprises the core | research team. It mentions Dario Amodei as CEO, and their listed | prior work suggests some others from OpenAI may be tagging along. | However, the success of this group is going to be highly | dependent on the caliber of the research team, and I was hoping | to see at least a few prominent researchers listed. I believe | OpenAI launched with four or five notable researchers as well as | close ties to academia via the AI group at Berkeley. Does anyone | have further info on the research team? | chetan_v wrote: | Seems you can see some of them on their company linkedin page : | https://www.linkedin.com/company/anthropicresearch/about/ | ansk wrote: | LinkedIn authwall, we meet again. Could someone list the | researchers (if there are any, and assuming there are only a | few). Frankly, it's not a great sign that the Anthropic site | isn't touting the research team itself and LinkedIn sleuthing | is even necessary. | Qworg wrote: | Current list (in LI order): | | * Dario Amodei | | * Benjamin Mann | | * Kamal Ndousse | | * Daniela Amodei | | * Sam McCandlish | | * Tom Henighan | | * Catherine Olsson | | * Nicholas Joseph | | * Andrew Jones | ansk wrote: | Thank you. | phreeza wrote: | Chris Olah posted that he is involved. | n1g3Jude wrote: | Complete waste of money.... Better to burn cash directly cause | that at least generates heat... This will generate nothing | etaioinshrdlu wrote: | Since this is Hacker News, I'll point out that training on GPUs | produces plenty of heat. | m4t3june wrote: | That's not true, they might generate some heat with the GPU | training | joe_the_user wrote: | Looks like an interesting project. The thing is, I don't think | ideal qualities like "reliable, interpretable, and steerable" can | really be simply added "on top of" existing deep learning systems | and methods. | | Much is made of GPT-3's ability to sometimes do logic or even | arithmetic. But that ability is unreliable and even more spread | through the whole giant model. Extracting a particular piece of | specifically logical reasoning from the model is hard problem. | You can do it - N-times the cost of the model. And in general, | you can add extras to the basic functionality of deep neural nets | (few-shot, generational, etc) but with a cost of, again, N-times | the base (plus decreased reliability). But the "full" qualities | mentioned initially would many-many extras-equivalent to one-shot | and need to have them happen on the fly. (And one-shot is fairly | easy seeming. Take a system that recognizes images by label | ("red", "vehicle", etc). Show it thing X - it uses the categories | thing X activates to decide whether other things are similar to | thing X. Simple but there's still lots of tuning to do here). | | Just to emphasize, I think they'll need something extra in the | basic approach. | Der_Einzige wrote: | Go check out the entire project of captum for pytorch. I assure | you that gradient based explanations can be simply added to | existing deep learning systems... | joe_the_user wrote: | All sorts of explanation scheme can and have be added to | existing processes. They just tend to fail to be what an | ordinary human would take as an explanation. | | Note - I never argued that "extras" (including formal | "explanations") can't be added to deep learning system. My | point is you absolutely can add some steps at generally high | cost. The argument is those sequence of small steps won't get | you to the ideal of broad flexibility that the OP landing | page outlines. | chetan_v wrote: | Looking at the team seems to be all ex-openai employees and one | of the cofounders worked on building gpt3. Will be exciting to | see what they are working on and if it will be similar work to | openai but more commercialized. | andreyk wrote: | Excited for this! While OpenAI has generated plenty of overhyped | results (imo as an AI researcher), their focus on large scale | empirical research is pretty different from most of the field and | had yielded some great discoveries. And with this being started | by many of the safety and policy people from OpenAI, I am pretty | optimistic for it. | strin wrote: | https://techcrunch.com/2021/05/28/anthropic-is-the-new-ai-re... ___________________________________________________________________ (page generated 2021-05-28 23:00 UTC)