Person

Karma: 95

Person 14 Dec 2023 17:09 UTC
1 point
0
on: Person’s Shortform
Google DeemMind’s recent FunSearch system seems pretty important, I’d really appreciate people with domain knowledge to disect this:
Blog post: https://deepmind.google/discover/blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models/
Paper: https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models/Mathematical-discoveries-from-program-search-with-large-language-models.pdf
Large Language Models (LLMs) have demonstrated tremendous capabilities in solving complex tasks, from quantitative reasoning to understanding natural language. However, LLMs sometimes suffer from confabulations (or hallucinations) which can result in them making plausible but incorrect statements (Bang et al., 2023; Borji, 2023). This hinders the use of current large models in scientific discovery. Here we introduce FunSearch (short for searching in the function space), an evolutionary procedure based on pairing a pre-trained LLM with a systematic evaluator. We demonstrate the effectiveness of this approach to surpass the best known results in important problems, pushing the boundary of existing LLM-based approaches (Lehman et al., 2022). Applying FunSearch to a central problem in extremal combinatorics — the cap set problem — we discover new constructions of large cap sets going beyond the best known ones, both in finite dimensional and asymptotic cases. This represents the first discoveries made for established open problems using LLMs. We showcase the generality of FunSearch by applying it to an algorithmic problem, online bin packing, finding new heuristics that improve upon widely used baselines. In contrast to most computer search approaches, FunSearch searches for programs that describe how to solve a problem, rather than what the solution is. Beyond being an effective and scalable strategy, discovered programs tend to be more interpretable than raw solutions, enabling feedback loops between domain experts and FunSearch, and the deployment of such programs in real-world applications.

Person’s Shortform

Person14 Dec 2023 17:09 UTC

2 points

1 comment1 min readLW link

Person 6 Dec 2023 18:15 UTC
17 points
3
on: Google Gemini Announced
https://storage.googleapis.com/deepmind-media/AlphaCode2/AlphaCode2_Tech_Report.pdf
AlphaCode 2, which is powered by Gemini Pro, seems like a big deal.
AlphaCode (Li et al., 2022) was the first AI system to perform at the level of the median competitor in competitive programming, a difficult reasoning task involving advanced maths, logic and computer science. This paper introduces AlphaCode 2, a new and enhanced system with massively improved performance, powered by Gemini (Gemini Team, Google, 2023). AlphaCode 2 relies on the combination of powerful language models and a bespoke search and reranking mechanism. When evaluated on the same platform as the original AlphaCode, we found that AlphaCode 2 solved 1.7× more problems, and performed better than 85% of competition participants.
Seems important for speeding up coders or even model self-improvement, unless competitive coding benchmarks are deceptive for actual applications for ML training.

Person 23 Nov 2023 15:57 UTC
1 point
0
in reply to: Steven Byrnes’s comment on: Possible OpenAI’s Q* breakthrough and Google’s AlphaGo-type systems
I also think the thing in question is not in fact an extremely important breakthrough that paves the path to imminent AGI anyway
Could you explain this assessment please? I am not knowledgeable at all on the subject, so I cannot intuit the validity of the breakthrough claim.

Person 17 Nov 2023 20:56 UTC
15 points
0
in reply to: Max H’s comment on: Sam Altman fired from OpenAI
I couldn’t remember where from, but I know that Ilya Sutskever at least takes x-risk seriously. I remember him recently going public about how failing alignment would essentially mean doom. I think it was published as an article on a news site rather than an interview, which are what he usually does. Someone with a way better memory than me could find it.
EDIT: Nevermind, found them.

Person 5 Oct 2023 20:06 UTC
2 points
1
on: This anime storyboard doesn’t exist: a graphic novel written and illustrated by GPT4
How the AI can give new abilities to humans (the author of this post is incapable of writing novels or making paintings, yet here we are).
(Not a serious comment, just a passing remark)
At the point where the AI is making every step of it and the human has barely any actual contribution, I’m curious to see whether the standard for “artistic ability” will be loosened or if the pendulum will swing the other way, where artistic worth will have a bigger basis in craft, skill and effort, which (my intuition) seems like how artistic worth was determined back in the Renaissance for example.

Person 28 Sep 2023 4:03 UTC
1 point
0
on: Investigating the rumors of OpenAI achieving AGI
I am trying to see if it is true. I need other people to help me alongside.
The whole thing generated enough buzz that Sam Altmann himself debunked it in a reddit comment (fitting, he was CEO of reddit at one point after all).
People say that he made correct predictions in the past.
His past predictions are either easily explained by a common trick used by sports fans on twitter, or have very shaky evidence for them since he keeps deleting his posts every few months, leaving us with 3rd party sources. Also, I wouldn’t a priori consider “GPT-5 finished training in October 2022 with 125T parameters” a correct prediction.

Person 26 Sep 2023 1:53 UTC
1 point
0
in reply to: jacquesthibs’s comment on: jacquesthibs’s Shortform
Or that he was genuinely just making things up and tricking us for fun, and a cryptic exit is a perfect way to leave the scene. I really think people are looking way too deep into him and ignoring the more outlandish predictions he’s made (125T GPT-4 and 5 in October 2022), along with the fact there is never actual evidence of his accurate ones, only 2nd hand very specific and selective archives.

Person 25 Sep 2023 13:15 UTC
3 points
0
in reply to: jacquesthibs’s comment on: jacquesthibs’s Shortform
Predicting the GPT-4 launch date can easily be disproven with the confidence game. It’s possible he just created a prediction for every day and deleted the ones that didn’t turn out right.
For the Gobi prediction it’s tricky. The only evidence is the Threadreader and a random screenshot from a guy who seems clearly related to jim. I am very suspicious of the Threadreader one. On one hand I don’t see a way it can be faked, but it’s very suspicious that the Gobi prediction is Jimmy’s only post that was saved there despite him making an even bigger bombshell “prediction”. It’s also possible, though unlikely, that the Information’s article somehow found his tweet and used it as a source for their article.
What kills Jimmy’s credibility for me is his prediction back in January (you can use the Wayback Machine to find it) that OAI had finished training GPT-5, no not a GPT-5 level system, the ACTUAL GPT-5 in October 2022 and that it was 125T parameters.
Also goes without saying, pruning his entire account is suspicious too.

Person 25 Sep 2023 4:45 UTC
3 points
0
in reply to: jacquesthibs’s comment on: jacquesthibs’s Shortform
Occasionally reading what OSS AI gurus say, they definitely overhype their stuff constantly. The ones who make big claims and try to hype people up are often venture entrepreneur guys rather than actual ML engineers.

Person 31 Aug 2023 11:49 UTC
3 points
3
in reply to: dr_s’s comment on: Why I hang out at LessWrong and why you should check-in there every now and then
Because of LW, I genuinely get frustrated when other forums I browse don’t just copy the UI. It’s just too good.

Person 20 Aug 2023 12:16 UTC
2 points
0
in reply to: lukehmiles’s comment on: AI #25: Inflection Point
It’s the 25th installment of weekly update posts that go over all the important news of the week, to which Zvi adds his own thoughts. They’re honestly amazing sources of information and it helps that I love Zvi’s writing style.

Person 9 Aug 2023 21:05 UTC
12 points
9
in reply to: JakubK’s comment on: Inflection.ai is a major AGI lab
Suleyman’s statements are either very specific capabilities predictions or incredibly vague statements like the one you brought up that don’t really inform us much. His interviews often revolve around talking about how big and smart their future models will be while also spending time putting in a good word for their financial backers (mainly NVIDIA). I find myself frustrated at seeing this company with a lot of compute and potential impact on timelines, but whose CEO and main spokesperson seems very out-of-touch with the domain he does business in.

Person 9 Aug 2023 4:18 UTC
3 points
0
in reply to: nikola’s comment on: Inflection.ai is a major AGI lab
You’re right, I completely misread it. I’ll edit my comment with that in mind.

Person 9 Aug 2023 2:41 UTC
27 points
13
on: Inflection.ai is a major AGI lab
I have an intuition about Suleyman, that being that his marketing background make him an incredibly unreliable source of actual information. He makes a lot of big predictions on future AI capabilities, like for hallucinations as a recent example I can think of and engages heavily in hype drumming in his interviews and social media. The untrustworthy aura I feel around the company extends to their products. Inflection-1′s technical paper (I can’t find a potential longer version) is very short compared to GPT-4 or PALM-2 and is entirely pictures of condensed benchmark results with a few paragraphs of explanations.
I expect my views to be wrong, but for now while inflection definitely has the compute, I have a feeling there’s a lot more limits and smoke involved that wouldn’t quite put them up with OpenAI, DeepMind and Meta in terms of impact on both the market and AGI timelines.
Edit: Originally misread the computer calculations from the post and used my mistake as evidence of my first point. Though the evidence is no longer there, it was confirming an intuition I already had and still stand by.

Person 28 Jul 2023 14:12 UTC
5 points
1
in reply to: Kaj_Sotala’s comment on: You don’t get to have cool flaws
The post reads to me as the author trying to unilaterally impose their personal ideal of perfection on other people.
I can’t say I had the same observation regarding the post, but I just wanted to agree with the problem you describe. It irks me when people attempt to categorize flaws and build up a model of biological perfection, not realizing all the consequences, psychological and social alike, that it entails. It seems like a very naïve endeavor rooted in personal biases more than an objective assessment.

Person 27 Jul 2023 0:42 UTC
3 points
0
on: The First Room-Temperature Ambient-Pressure Superconductor
Provided the paper is legit, what are the implications on AI timelines? Would compute-intensive paradigms like WBE suddenly become feasible?

Person 21 Jul 2023 16:52 UTC
1 point
0
on: BCIs and the ecosystem of modular minds
I’ve always wondered, how do you retain agency if you embed a vastly smarter and faster mind to yours, when they would theoretically make better decisions than you would have 90% of the time. Scaling this intuition, turning humanity into a hive-mind does not strike me as a valuable future world.
Edit: I’ve also given more thought to the idea of BCIs allowing us to ‘download’ skills, and I’d really like someone to engage with the following. If we agree we derive value and meaning from effort we put into learning and the satisfaction we get from it, essentially specializing ourselves depending on our tastes, how do we find value in a world where anyone can instantly know anything? It’s a question I’ve been ruminating on for a few hours.

Person 20 Jul 2023 14:07 UTC
1 point
0
in reply to: janleike’s comment on: [Linkpost] Introducing Superalignment
Thanks for engaging with people’s comments here.
is whether a smart agent could sneak a deceptive malicious artifact (e.g. some code)
I have a somewhat related question on the subject of malicious elements in models. Does OAI’s Superalignment effort also intend to cover and defend from cases of s-risks? A famous path for hyperexistential risk for example is sign-flipping, where in some variations, a 3rd party actor (often unwillingly) inverts an AGI’s goal. Seems it’s already happened with a GPT-2 instance too! The usual proposed solutions are building more and more defenses and safety procedures both inside and outside. Could you tell me how you guys view these risks and if/how the effort intends to investigate and cover them?

Person 11 Jul 2023 20:37 UTC
2 points
0
in reply to: Vladimir_Nesov’s comment on: OpenAI Launches Superalignment Taskforce
With the size of the project and commitment, along with OAI acknowledging they might hit walls and will try different courses, one can hope investigating better behavioral systems for an AGI will be one of them.

Person

Per­son’s Shortform

Person’s Shortform