9 ms·
I'm not sure if people here even read the entirety of the article. From the article: > We applied the AI co-scientist to assist with the prediction of drug rep
by crypto420 2y ago
I'm not sure if people here even read the entirety of the article. From the article:
> We applied the AI co-scientist to assist with the prediction of drug repurposing opportunities and, with our partners, validated predictions through computational biology, expert clinician feedback, and in vitro experiments.
> Notably, the AI co-scientist proposed novel repurposing candidates for acute myeloid leukemia (AML). Subsequent experiments validated these proposals, confirming that the suggested drugs inhibit tumor viability at clinically relevant concentrations in multiple AML cell lines.
and,
> For this test, expert researchers instructed the AI co-scientist to explore a topic that had already been subject to novel discovery in their group, but had not yet been revealed in the public domain, namely, to explain how capsid-forming phage-inducible chromosomal islands (cf-PICIs) exist across multiple bacterial species. The AI co-scientist system independently proposed that cf-PICIs interact with diverse phage tails to expand their host range. This in silico discovery, which had been experimentally validated in the original novel laboratory experiments performed prior to use of the AI co-scientist system, are described in co-timed manuscripts (1, 2) with our collaborators at the Fleming Initiative and Imperial College London. This illustrates the value of the AI co-scientist system as an assistive technology, as it was able to leverage decades of research comprising all prior open access literature on this topic.
The model was able to come up with new scientific hypotheses that were tested to be correct in the lab, which is quite significant.
- terminalbraid 2y agoI expect it's going to be reasonably useful with the "stamp collecting" part of science and not so much with the rest.
- preston4tw 2y agoThis is one thing I've been wondering about AI: will its broad training enable it to uncover previously covered connections between areas the way multi-disciplinary people tend to, or will it still miss them because it's still limited to its training corpus and can't really infer. If it ends up being more the case that AI can help us discover new stuff, that's very optimistic.
- semi-extrinsic 2y agoIn some sense, AI should be the most capable at doing this within math. Literally the entire domain in its entirety can be tokenized. There are no experiments required to verify anything, just theorem-lemma-proof ad nauseam. Doing this like in this test, it's very tricky to rule out the hypothesis that the AI is just combining statements from the Discussion / Future Outlook sections of some previous work in the field.
- theptip 2y agoMath seems to me like the hardest thing for LLMs to do. It requires going deep with high IQ symbol manipulation. The case for LLMs is currently where new discoveries can be made from interpolation or perhaps extrapolation between existing data points in a broad corpus which is challenging for humans to absorb.
- staunton 2y agoAlternatively, human brains are just terrible at "high IQ symbol manipulation" and that's a much easier cognitive task to automate than, say, "surviving as a stray cat".
- semi-extrinsic 2y agoThis line of reasoning implies "the stochastical parrot people are right, there is no intelligence in AI". Which is the opposite of what AI thought leaders are saying.
- lmm 2y agoI think this may be the first time I've seen "thought leaders" used unironically. Is there any reason to believe they're right?
- semi-extrinsic 2y agoWhat makes you think it was used unironically? :)
- blacksmith_tb 2y agoNot that I don't think there's a lot of potential in this approach, but the leukemia example seemed at least poorly-worded, "the suggested drugs inhibit tumor viability" reads oddly given that blood cancers don't form tumors?
- shpongled 2y agoThat a UPR inhibitor would inhibit viability of AML cell lines is not exactly a novel scientific hypothesis. They took a previously published inhibitor known to be active in other cell lines and tried it in a new one. It's a cool, undergrad-level experiment. I would be impressed if a sophomore in high school proposed it, but not a sophomore in college.
- klipt 2y agoOnly two years since chatGPT was released and AI at the level of "impressive high school sophomore" is already blasé.
- thomastjeffery 2y agoSure, but is it more impressive than books?
- directevolve 2y agoMost people here know little to nothing of biomedical research. Explaining clearly why this isn’t a scientifically interesting result is helpful.
- rtkwe 2y agoSuggesting "maybe try this known inhibitor in other cell lines" isn't exactly novel information though. It'd be more impressive and useful if it hadn't had any published information about working as a cancer inhibitor before. People are blasé about it because it's not really beating the allegations that it's just a very fancy parrot when the highlight of it's achievements is to say try this known inhibitor with these other cell lines, decent odds that the future work sections of papers on the drug already suggested trying on other lines too...
- baq 2y agoA couple years ago even suggesting that a computer could propose anything at all was sci-fi. Today a computer read the whole internet, suggested a place to look at and experiments to perform and… ‘not impressive enough’. Oof.
- xbmcuser 2y agoSimilar stuff is being done for material sciences where AI suggest different combinations to find different properties. So when people say AI(machine learning, LLM) are just for show I am a bit shocked as AI's today have accelerated discoveries in many different fields of science and this is just the start. Anna archive probably will play a huge role in this as no human or even a group of humans will have all the knowledge of so many fields that an Ai will have. https://www.independent.co.uk/news/science/super-diamond-b2699984.html#:~:text=Chinese%20scientists%20have%20created%20an,by%20heating%20highly%20compressed%20graphite. https://www.independent.co.uk/news/science/super-diamond-b26...
- fhd2 2y agoIt's a matter of perspective and expectations. The automobile was a useful invention. I don't know if back then there was a lot of hype around how it can do anything a horse can do, but better. People might have complained about how it can't come to you when called, can't traverse stairs, or whatever. It could do _one_ thing a horse could do better: Pull stuff on a straight surface. Doing just one thing better is evidently valuable. I think AI is valuable from that perspective, you provide a good example there. I might well be disappointed if I would expect it to be better than humans at anything humans can do. It doesn't have to. But with wording like "co-scientist", I see where that comes from.
- ClumsyPilot 2y ago> It could do _one_ thing a horse could do better: Pull stuff on a straight surface I would say the doubters were right, and the results are terrible. We redesigned the world to suit the car, instead of fixing its shortcomings. Navigating a car centric neighbourhood on foot is anywhere between depressing and dangerous. I hope the same does not happen with AI. But I expect it will. Maybe in your daily life AI will create legal contracts there are thousands of pages long And you will need AI of your own to summarise them and process them.
- fhd2 2y agoExcellent point. Just because the invention of the automobile arguably introduced something valuable, how we ended up using them had a ton of negative side effects. I don't know enough about cars or horses to argue pros and cons. But I can certainly see how we _could_ have used them in a way that's just objectively better than what we could do without them. But you're right, I can't argue we did.
- hirenj 2y agoI read the cf-PICI paper (abstract) and the hypothesis from the AI co-scientist. While the mechanism from the actual paper is pretty cool (if I'm understanding it correctly), I'm not particularly impressed with the hypothesis from the co-scientist. It's quite a natural next step to take to consider the tails and binding partners to them, so much so that it's probably what I would have done and I have a background of about 20 minutes in this particular area. If the co-scientist had hypothesised the novel mechanism to start with, then I would be impressed at the intelligence of it. I would bet that there were enough hints towards these next steps in the discussion sections of the referenced papers anyway. What's a bit suspicious is in the Supplementary Information, around where the hypothesis is laid out, it says "In addition, our own preliminary data indicate that cf-PICI capsids can indeed interact with tails from multiple phage types, providing further impetus for this research direction." (Page 35). A bit weird that it uses "our own preliminary data".
- TrainedMonkey 2y ago> A bit weird that it uses "our own preliminary data" I think potential of LLM based analysis is sky high given the amount of concurrent research happening and high context load required to understand the papers. However there is a lot of pressure to show how amazing AI is and we should be vigilant. So, my first thought was - could it be that training data / context / RAG having access to a file it should not have contaminated the result? This is indirect evidence that maybe something was leaked.
- hinkley 2y ago> in silico discovery Oh I don’t like that. I don’t like that at all.
- j_timberlake 2y agoDon't worry, it takes about 10 years for drugs to get approved, AIs will be superintelligent long before the government gives you permission to buy a dose of AI-developed drugs.
- dekhn 2y agoSo, I've been reading Google research papers for decades now and also worked there for a decade and wrote a few papers of my own. When google publishes papers, they tend to juice the results significance (google is not the only group that does this, but they are pretty egregious). You need to be skilled in the field of the paper to be able to pare away the exceptional claims. A really good example is https://spectrum.ieee.org/chip-design-controversy https://spectrum.ieee.org/chip-design-controversy while I think Google did some interesting work there and it's true they included some of the results in their chip designs, their comparison claims are definitely over-hyped and they did not react well when they got called out on it.
- tsumnia 2y agoRemember Google is a publicly traded company, so everything must be reviewed to "ensure shareholder value". Like dekhn said, its impressive, but marketing wants more than "impressive".
- Workaccount2 2y agoDoes this qualify as an answer to Dwarkesh's question?[1][2] [1]https://marginalrevolution.com/marginalrevolution/2025/02/dwarkeshs-question.html https://marginalrevolution.com/marginalrevolution/2025/02/dw... [2]https://x.com/dwarkesh_sp/status/1888164523984470055 https://x.com/dwarkesh_sp/status/1888164523984470055 I don't know his @ but I'm sure he is on here somewhere
- Mekoloto 2y agoI also think people underestimate how much benefit a current LLM already has to researchers. A lot of them have to do things on computers which has nothing to do with their expertise. Like coding a small tool for working their data, small tools crunching results, formatting text data, searching and finding the right materials. A LLM which helps a scientist to code something in an hour instead of a week, makes this research A LOT faster. And we know from another paper, that we have now so much data, you need to use systems to find the right information for you. The study estimated how much additionanl critical information a research paper missed.
- YeGoblynQueenne 2y agoIt's cool, no doubt. But keep in mind this is 20 years late: As a prototype for a "robot scientist", Adam is able to perform independent experiments to test hypotheses and interpret findings without human guidance, removing some of the drudgery of laboratory experimentation.[11][12] Adam is capable of: * hypothesizing to explain observations * devising experiments to test these hypotheses * physically running the experiments using laboratory robotics * interpreting the results from the experiments * repeating the cycle as required[10][13][14][15][16] While researching yeast-based functional genomics, Adam became the first machine in history to have discovered new scientific knowledge independently of its human creators.[5][17][18] https://en.wikipedia.org/wiki/Robot_Scientist https://en.wikipedia.org/wiki/Robot_Scientist