# Googles New Breakthrough is BIGGER Than You Think! (Googles Q*)

## Метаданные

- **Канал:** TheAIGRID
- **YouTube:** https://www.youtube.com/watch?v=GV9frJ01b3k
- **Дата:** 30.07.2024
- **Длительность:** 17:40
- **Просмотры:** 51,715

## Описание

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00:00 - Intro to DeepMind breakthrough
00:49 - Alpha Proof and Alpha Geometry 2
01:42 - IMO explanation
02:34 - AI performance details
03:24 - Neuro-symbolic AI approach
04:25 - Comparison to AlphaGo Zero
05:31 - ARC benchmark discussion
07:28 - Neuro-symbolic success on ARC
08:49 - Demis Hassabis tweet
09:20 - Paul Christiano's timeline update
10:40 - Eliezer Yudkowsky's perspective
11:49 - Superintelligent AI discussion
14:14 - Sam Altman's cryptic response
14:38 - OpenAI's secret model rumors
16:31 - Implications for AGI progress
17:35 - Closing remarks

Links From Todays Video:
https://x.com/fchollet/status/1802773156341641480
https://x.com/bshlgrs/status/1802766374961553887
https://x.com/fchollet/status/1809439709363597547
https://x.com/demishassabis/status/1816596568398545149
https://www.reuters.com/technology/artificial-intelligence/openai-working-new-reasoning-technology-under-code-name-strawberry-2024-07-12/
https://deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level/?utm_source=x&utm_medium=social&utm_campaign=&utm_content=
https://www.lesswrong.com/posts/sWLLdG6DWJEy3CH7n/imo-challenge-bet-with-eliezer
https://x.com/GoogleDeepMind/status/1816498082860667086

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## Содержание

### [0:00](https://www.youtube.com/watch?v=GV9frJ01b3k) Intro to DeepMind breakthrough

so there was a recent Breakthrough by one of the frontier Labs Google deep mind and I think most people haven't realized the gravity of the situation here Deep Mind managed to be the first Frontier lab to solve International mathematical Olympiad problems at a silver medalist level and this combines Alpha proof a new breakthrough model for reasoning and Alpha geometry 2 an improved version of their previous system now this was something that I think people did gloss over a little bit because they didn't realize the impact of this work but I think that this is most certainly probably one of the top five most important breakthroughs this year and I'm going to get into why that is and why you should be paying attention to This research and what it means because not only was it incredible there was also some other pieces of information surrounding so essentially

### [0:49](https://www.youtube.com/watch?v=GV9frJ01b3k&t=49s) Alpha Proof and Alpha Geometry 2

they State here the Breakthrough models Alpha proof and Alpha geometry to solve Advanced reasoning problems in mathematics artificial general intelligence with Advanced mathematical reasoning has the potential to unlock New Frontiers in science and technology we've made great progress in building AI systems that help mathematicians discover new insights novel algorithms and answers to open problems but current AI systems still struggle with solving general math problems because of limitations in reasoning skills and training data and this is where the craziness starts today we present Alpha proof a new reinforcement learning based system formal math reasoning and Alpha geometry 2 an improved version of our geometry solving system together they managed to solve four out of six problems from this year's International mathematical Olympiad now if you don't know what the international mathematical Olympiad is you probably won't realize why this is so crazy this is the oldest

### [1:42](https://www.youtube.com/watch?v=GV9frJ01b3k&t=102s) IMO explanation

and largest most prestigious competition for young mathematicians held annually since 1959 in each year Elite pre-ol mathematicians Train sometimes for thousands of hours to solve six exceptionally difficult problems in algebra combinatorics geometry and number Theory and basically this is one of the challenges for artificial intelligence and many people do predict that once we have a system that's able to get gold we all know the truly capable systems are here now you can see here that this recent so the score on the IMO 2024 problems you can see the graph showing performance of our AI system relative to human competitors at the IMO 2024 we earned 28 out of 42 total points achieving the same level as the silver medalist in the competition so you can see that it literally was one point away from getting the gold medal I think

### [2:34](https://www.youtube.com/watch?v=GV9frJ01b3k&t=154s) AI performance details

actually if it's 28 then that means it's two points away but nonetheless it is a fine margin to getting the gold but this is absolutely insane because one of the things I realize that Google have done is they've gone back to some of their old architectures that they previously used to use now if you aren't familiar with what Google have previously done in the past they've actually done a huge amount of different AI projects that have been really successful and they've even managed to create you know superhuman AI systems now essentially the reason why I say that this is you know so crazy and the reason why that this excited me was because if we actually take a look at what Google have done here you can see that they actually describ that this is a neuros symbolic hybrid system in which the language model was based on Gemini and trained from scratch on an order of magnitude more synthetic data than its predecessor

### [3:24](https://www.youtube.com/watch?v=GV9frJ01b3k&t=204s) Neuro-symbolic AI approach

this helped the model tackle much more challenging geometry problems including problems about movements of objects and equations of angles Ratio or distances an alpha geometry 2 employs a symbolic engine that is two orders of magnitude faster than its predecessor when presented with a new problem a novel knowledge sharing mechanism is used to enable Advanced combination of different search trees to tackle more complex problems and the reason that this is crazy is because neuros symbolic AI from what we've seen in early experiments even on some of the hardest benchmarks have proven to consistently generate results that surprise even the most well researched researchers so that's why this is so crazy because if Google managed to continue pushing the bounds on neuros symbolic AI I do believe that they're likely to make an increasing number of breakthroughs and increasingly more powerful systems in terms of their reasoning capability if you want to take a look at a kind of neuros symbolic system that was there before if you remember Alpha goz there was Alpha goz which was a form of alpha go which was a lot better but essentially this model

### [4:25](https://www.youtube.com/watch?v=GV9frJ01b3k&t=265s) Comparison to AlphaGo Zero

basically surpassed the previous Alpha Al go and actually previously you know then went to surpass the alphao master so alphao zero was a system that basically managed to train itself and essentially managed to master go in just 21 days this was a newer part this was a new approach and you can see that in 40 days that it surpasses all other versions of go and becomes the best go player in the world and it does this entirely from selfplay now of course I'm not saying that you can apply this entire concept to llms but the point here is that one of the things if you remember and if you've been paying attention to some of the reports floating around is that they've been saying that look AI is you know running out of training data running out of data what are we going to do yada y yada but one of the things that you know people have been slowly exploring is the fact that neuros symbolic AI improves ai's reasoning capabilities by using many different things one of the things is of course tool use and of course different ways to search and solve different reasoning problem and I think that this method is something that we've seen time and time again in all the research papers that I've looked at this is

### [5:31](https://www.youtube.com/watch?v=GV9frJ01b3k&t=331s) ARC benchmark discussion

something that increases the reasoning ability of these models so basically you have this researcher called fenis chle he's a French software engineer and computer scientist working at Google Now essentially he created a benchmark that is rather hard for current AI systems and it's kind of Benchmark that is not subject to contamination so it's not something that is leaked in the training data where AIS can plan for it and it's not something they can memorize either so this is a really hard Benchmark now what's crazy about this is that he basically said to be clear I've never claimed that solving Arc was equivalent to solving AGI the first Arc solver is not going to be an AGI but he basically said that you know this Arc challenge that he created and I did talk about this before but I just wanted to quickly gloss over this but he says here that until we solve Arc we don't have AGI since the AI we have cannot adapt to simple tasks that they haven't seen before and solving Arc will require figuring out how to make AI systems adapt on the fly to novel tasks and this should be a major Milestone on the way to AGI which is why I said that this is a major Milestone because solving the arch Benchmark is going to be a major Milestone because whatever approach that you do use to solve that Benchmark it means that you know whatever reasoning engine that you're using whether it be neuros symbolic whether it be you know tree search or whatever kind of approach it is that you do use whatever approach that is going to be it's going to be something that's remarkably effective if it can actually focus and solve this Benchmark and he says here the purpose of Arc is to get researchers to refocus on intelligence and pure away from memorization because I believe this is how we will get to AGI and basically you didn't know llms they don't really have intelligence in the sense that they figure things out they do well on many tasks because they've been trained on various pieces of data and there's a pure difference between you know humans that can see an image like of two cats and then immediately they can you know recognize what a cat is outside in the wild so this is the kind of reasoning where you're able to figure out what's going on the fly in new and no

### [7:28](https://www.youtube.com/watch?v=GV9frJ01b3k&t=448s) Neuro-symbolic success on ARC

scenarios now with that Benchmark though the reason I actually brought this up was because someone basically decided to use llms and a neuros symbolic approach and basically managed to figure out how to do this now it's crazy because like I said before the meme kind of memes neuros symbolic AI but essentially the method that the person used which was Ryan to manage to get you know 72% with GPT 40 he actually used a neuros symbolic approach so the meme here is kind of wrong but essentially this was pretty crazy because it was something that many people thought would take quite a while and you can see here franchis solay said this has been the most promising branch of approaches so far leveraging an LM to help with discrete program search by using the llm as a way to sample programs or branching decisions this is exactly what neuros symbolic AI is for the record and that's why when you have AIS that can search over multiple things it's something that results in a much more comprehensive system now I wonder how effective this is going to be because when you have an AI system like Alpha go that search over millions and millions of different positions we can manage to filter out the bad decisions and then of course we can get to the real results and although some people would argue that oh but that's not real intelligence I mean if it manages to get the result then it doesn't really matter how it gets there it just matters that it is there and what's crazy about all of this is that you know Demis cabus tweeted about this

### [8:49](https://www.youtube.com/watch?v=GV9frJ01b3k&t=529s) Demis Hassabis tweet

he says we've long pioneered the use of these types of neuros symbolic systems starting with alphao in 2016 through to Alpha zero and we'll be bringing all the goodness of alpha proof than Alpha geometry 2 to our mainstream Gemini models very soon watch this space so it means that Gemini models are potentially about to get really smart now this whole thing was a little bit scary for some individuals and I mean scary in the sense that this is something that some people did predict would initially shrink the timeline so if you're not

### [9:20](https://www.youtube.com/watch?v=GV9frJ01b3k&t=560s) Paul Christiano's timeline update

familiar with what I'm talking about you can see here that Paul Cristiano the person who invented RL HF now he basically said here that is going to update his timeline if an AI got gold in any International math Olympiad by the end of 2025 and today Alpha proof came within one point of achieving that gold medal you can see here his statements he says that I think the IMO challenge would be significant direct evidence that powerful AI would be sooner or at least would be technologically possible sooner I think this would be fairly significant evidence perhaps pushing my 2040 probability up from 25% to 40% or something like that and I think that this would be significant evidence that the takeoff will be limited by sociological facts and Engineering effort rather than a slow March of smooth machine learning scaling maybe I'd move from 30% to a 50% chance of a hard takeoff so basically what we have here is a situation where timelines are shrinking as we move throughout the year and this is something that many people didn't even think would happen considering how difficult these problems are now Eliza owski actually made a statement here that said Paul Cristiano and I previously worked hard to pin down concrete disagreements and one of our headers was that Paul put up an 8% probability on AI built before 2025 IMO

### [10:40](https://www.youtube.com/watch?v=GV9frJ01b3k&t=640s) Eliezer Yudkowsky's perspective

reaches gold level on it and I put it at least 16% now the reason that this is so crazy is because Eliza owski has been someone who's basically stating that look creating super intelligent AI is just an a stupid thing to do simply put it's just stupid it's just downright stupid because what's going to happen is it's going to do something that is going to cause irreversible damage or potentially human extinction and what's crazy about all of this is that if you've seen and you know looked at some of the conversations that Elijah yudkowsky has some of the arguments he does make are quite fascinating because he basically describes how a superintelligent AI is one that you simply cannot win against if you think about it like this for example some people frequently say that okay tell me how the superintelligent AI is going to win and then we're going to solve that issue but it's like this okay if you have someone who is the best chess player in the world like Magnus Carlson or Gary Kasparov you can say that look if you put an average person against them you know 100% of the time they are going to fail but what we don't know is how they're going to fail I can't tell you where they're going to place the pieces on the board what we do know is the end result and the same situation is with AI we don't know what this AI is

### [11:49](https://www.youtube.com/watch?v=GV9frJ01b3k&t=709s) Superintelligent AI discussion

going to do if it is a super intelligent system what we do know is that the end result is that humans lose because we look at Evolution anytime a new species comes on that is far more intelligent the other species aren't around for much longer or are essentially kept as entertainment or just pretty much farmed for whatever resources they have but just paint one or two possibilities okay so why is this hard first because you can predict exactly where a smarter chess program will move maybe even more importantly than that imagine sending the design for an air conditioner back to the 11th century even if they if it's enough detail for them to build it they will be surprised when cold air comes out because the air conditioner will use the temperature pressure relation and they don't know about that law of nature so if you want me to sketch what a super intelligence might do I can go deeper and deeper into places where we think there are predictable technological advancements that we haven't figured out yet and as I go deeper and deeper it'll get harder and harder to follow it could be super persuasive that's relatively easy to understand we do not understand exactly how the brain works so it's a great place to exploit laws of nature that we do not know about rules of the environment invent new technologies beyond that can you build a synthetic virus that gives humans a cold and then bit of neurological change and they're easier to persuade can you build your own synthetic biology synthetic cyborgs can you blow straight past that to Coal bonded equivalence of biology where instead of proteins that fold up and are held together by Static Ling you've got things that go down much sharper potential energy gradients and are bonded together people have done Advanced design work so the point here and I might even include a clip from Eliza owski but the point here is that you know the meta point that Paul and I was arguing was is the progress of AI smooth and therefore predictable and bound and the sharp prediction market movement on our bet suggests that this development was not smoothly predictable based on Public Information meaning that the kinds of research that's going on right now in Frontier Labs shows us that the kinds of system that are currently being devel veloped could far surpass the our current estimate of what is even capable on the upper bounds of current intelligence which means that look capable systems are not far away and they're probably closer than we think considering these incredible jumps in terms of prediction Mar now what was

### [14:14](https://www.youtube.com/watch?v=GV9frJ01b3k&t=854s) Sam Altman's cryptic response

even crazier about this entire thing was that someone tweeted opening ey has the opportunity to do the funniest thing and then Sam mman responded stating LOL just stating laughing out loud now the reason this is crazy is because not only did Sam Alman respond to this tweet saying LOL there has actually been some recent information regarding opening eyes Secret model and if you remember what

### [14:38](https://www.youtube.com/watch?v=GV9frJ01b3k&t=878s) OpenAI's secret model rumors

the secret model was actually you know focusing on it was actually focusing on math and samman's saying LOL at this basically is an indication that they perhaps might even be far ahead of where other systems currently are which could mean that incredible systems are already here and I don't think that Sam Alman would have responded to that tweet if that wasn't the case now for those of you that think okay this is just reaching all he did was just put LOL you have to remember that the recent you know qar project or the strawberry project you can see here from Reuters which is a very reliable source said that two sources described viewing earlier this year where open eye staffers told them were qar demos capable of answering remember tricky science and math questions Out Of Reach of today's commercially available models and add different Source briefed on the matter said that open AI has tested AI internally that scored over 90% on a math data scent a benchmark of Championship math problems and Reuters could not determine if this was the strawberry project so that's the reason that this is so crazy is because you know on the one hand you've got open ey basically stating that LOL um we do have the you know ability to do something really funny but at the same time we don't know what's going on with strawberry because this was a model that is you know highly guarded and highly secret but if the AI did score over 90% on a math data set then that is pretty impressive because not only did open AI do it but you if you do remember Google actually did release not release but you know release a paper in which actually spoke about their specialized model called Gemini math specialized 1. 5 Pro and we can see that it scores 91. 1% and of course there is some RM at 256 I actually haven't read the paper so I don't know what that means but it's probably some kind of method said that allows the AI system to get better

### [16:31](https://www.youtube.com/watch?v=GV9frJ01b3k&t=991s) Implications for AGI progress

results so I think what's going on here is that we do have this inflection point on our hands where truly capable systems are just around the corner in terms of math and science and I think that these kind of breakthroughs from Google and from open ey managing to score over 90% on these benchmarks is going to be what actually drives the rest of technological progress because this is the kind of you know research that can actually lead to new knowledge and of course AGI so this was something that I wanted to talk about less about you know the information just regarding the fact that you know it was able to get silver but more around the fact that you know if we look at how timelines have now shrunk and the fact that opening eye are hinting towards their systems being even more capable this is something that is uh truly fascinating so that being said if you did enjoy this video let me know what your thoughts are on AI creating new knowledge and what you think about the international math Olympiad you know the varied experts on opinions on how we're going to get to there are many different things floating around but of course neuros symbolic AI so far does look to be very promising with that being said

### [17:35](https://www.youtube.com/watch?v=GV9frJ01b3k&t=1055s) Closing remarks

if you enjoyed the video hopefully you guys have a wonderful day and I'll see you in the next AI update

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*Источник: https://ekstraktznaniy.ru/video/14158*