11 ms·

AI cracks superbug problem in two days that took scientists years

250 points by monkeydust 2y ago

nurettin 2y ago
"LLMs are great at solving problems that already have solutions." This is performance art, right?
monkeydust 2y ago
Using this, launched yesterday: Today Google is launching an AI co-scientist, a new AI system built on Gemini 2.0 designed to aid scientists in creating novel hypotheses and research plans. Researchers can specify a research goal — for example, to better understand the spread of a disease-causing microbe — using natural language, and the AI co-scientist will propose testable hypotheses, along with a summary of relevant published literature and a possible experimental approach. https://blog.google/feed/google-research-ai-co-scientist/ https://blog.google/feed/google-research-ai-co-scientist/
deleted 2y ago
[deleted]
root_axis 2y ago
> Critically, this hypothesis was unique to the research team and had not been published anywhere else. Nobody in the team had shared their findings This seems like the most important detail, but it also seems impossible to verify if this was actually the case. What are the chances that this AI spat out a totally unique hypothesis that has absolutely no corollaries in the training data, that also happens to be the pet hypothesis of this particular research team? I'm open to being convinced, but I'm skeptical.
- mtrovo 2y ago
  Define "totally unique hypothesis" in this context. If the training data contains studies with paths like A -> B and C -> D -> E, and the AI independently generates a proof linking B -> C, effectively creating a path from A -> E, is that original enough? At some point, I think we're going to run out of definitions for what makes human intelligence unique. > It also seems impossible to verify if this was actually the case. If this is a thinking model, you could always debug the raw output of the model's internal reasoning when it was generating an answer. If the agent took 48 hours to respond and we had no idea what it was doing that whole time, that would be the real surprise to me, especially since Google is only releasing this in a closed beta for now.
- TrackerFF 2y ago
  Could some of the scientists have saved their data in the google cloud, say using google drive? And then some internal google crawler went through, and indexed those files? I don't know that their policy says about that, or if it is even something they do...at least not publicly.
- miyuru 2y ago
  > "I wrote an email to Google to say, 'you have access to my computer, is that right?'", he added. sounds extra fishy, since google does not provide email support normally.
  - Jimmc414 2y ago
    "Scientists who are part of our Trusted Tester Program will have early access to AI co-scientist" https://blog.google/feed/google-research-ai-co-scientist/ https://blog.google/feed/google-research-ai-co-scientist/
  - bArray 2y ago
    Exactly my thought, probably the least likely part of the whole thing. He emailed Google and they replied. Not only that, he asked a question they would really rather not answer.
- bArray 2y ago
  Google openly train stuff based on your email, they used is specifically to train Smart Compose, but maybe other stuff too. He likely uses multiple Google products. Draft papers in Google Drive perhaps? These LLM models are essentially trying to produce material that sounds correct, perhaps the hypothesis was a relatively obvious question with the right domain knowledge. Additionally, he may not have been the first to ask the question. It's entirely possible that the AI chewed up and spat out some domain knowledge from a foreign research group outside of his wheelhouse. This kind of stuff happens all the time. I personally have accidentally reinvented things without prior knowledge of them. Many years ago in University I remember deriving a PID controller without being aware of what one was. I probably got enough clues from other people/media that were aware of them, that bridging that final gap was made easier.
  - Jabbles 2y ago
    > We do not use your Workspace data to train or improve the underlying generative AI and large language models that power Gemini, Search, and other systems outside of Workspace without permission. https://support.google.com/meet/answer/14615114?hl=en#:~:text=We%20do%20not%20use%20your%20Workspace%20data%20to%20train%20or%20improve%20the%20underlying%20generative%20AI%20and%20large%20language%20models%20that%20power%20Gemini%2C%20Search%2C%20and%20other%20systems%20outside%20of%20Workspace%20without%20permission. https://support.google.com/meet/answer/14615114?hl=en#:~:tex... You may not believe them, but I challenge your description of it as "openly".
    - stonogo 2y ago
      Yeah, "Workspace data." If you don't think a scientist has copies of all his/her stuff in a personal Google account you've never met a scientist.
      - cwillu 2y ago
        The second half of the sentence is a bit awkward, but the first bit is pretty clear: “We do not use your Workspace data”
- card_zero 2y ago
  I wonder about a "clever Hans" effect, where they unwittingly suggest their discovery in their prompt. Also whether they got paid.
  - cwillu 2y ago
    “ "It's not just that the top hypothesis they provide was the right one," he said. "It's that they provide another four, and all of them made sense. And for one of them, we never thought about it, and we're now working on that."”
    - card_zero 2y ago
      I wonder whether that one is really any good.
  - graeme 2y ago
    May well be but in this case it would be a two way clever Hans which is very promising.
didntknowyou 2y ago
why did it take 48 hours? did he give the AI data to process or was it just a prompt. did it spit back out a conclusion or a list of possible scenarios it had scraped? seems like a PR stunt.
- tecleandor 2y ago
  While there is some stuff around this that sounds like PR (probably some intermediate results and/or SOTA on that field as of today could help reaching that result), the process seems interesting. Seems like it launches ahem "agents" that do simulations, verifications, refines and iterates over different options... and it takes a while: https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ https://research.google/blog/accelerating-scientific-breakth...
programmertote 2y ago
When I read "cracks superbug problem", I thought AI solved how to kill superbugs. From reading the article, it seems like AI suggested a few hypotheses and one of which is similar to what the researcher thought of. So in a way, it hasn't cracked the problem although it helped in forming ONE of the hypotheses, which needs to be tested in experiments(?) Just want to make sure I'm understanding what's written in the article accurately.
- newsreaderguy 2y ago
  it suggested other hypotheses as well, including one that they hadn't thought of and are investigating
fatbird 2y ago
So the AI didn't prove anything, it offered a hypothesis that wasn't in the published literature, which happened to match what they'd spent years trying to verify. I can see how that would look impressive, and he says that if he'd had this hypothesis to start with, it would have saved those years. Without those years spent working the problem, would he have recognized that hypothesis as a valuable road to go down? And wouldn't the years of verifying it still remain?
kachapopopow 2y ago
this might be a dupe and the title is completely misleading, it (the AI) simply provided one of the hypothesis (which took two years to confirm) as the top result. A group of humans can come up with these in seconds given expertise in the subject.
Over3Chars 2y ago
[flagged]
furyofantares 2y ago
It says it took them a decade, but they obviously published loads of intermediate results, as did anyone else working in the space. I get that they asked it about a new result they hadn't published yet, but the idea that it did it in two days when it took them a decade -- even though it's been trained on everything published in that decade, including whatever intermediate results they published -- probably makes this claim just as absurd as it sounds.
- tippytippytango 2y ago
  I’d bet the hypothesis was already in the training data. Someone probably suggested it in the future work section of some other paper.
  - hinkley 2y ago
    One of the annoying things about the LZW compression patent was that it covered something Lempel and Ziv had already mentioned in the further study section of their original paper. Someone patented an “exercise left to the reader”.
- gota 2y ago
  Tentative rephrasing: "When given all of the facts we uncovered over a decade as premises, the computer system generated the conclusion instantly" edit - instantly is apparently many hours, hence the 'two days', just to be clear
- vintagedave 2y ago
  Maybe, but: > He told the BBC of his shock when he found what it had done, given his research was not published so could not have been found by the AI system in the public domain. and, > Critically, this hypothesis was unique to the research team and had not been published anywhere else. Nobody in the team had shared their findings.
  - deleted 2y ago
    [deleted]
nurumaik 2y ago
>He gave "co-scientist" - a tool made by Google - a short prompt asking it about the core problem he had been investigating and it reached the same conclusion in 48 hours. Could it be the case when asking the right question is the key? When you know the solution already it's actually very easy to accidentally include some hints in your phrasing of question that will make task 10x easier
- killerteddybear 2y ago
  This is a very common mistake with LLMs I find. Lots of people who have high domain knowledge will be very impressed by it due to situations where they phrase questions in such a way that it unintentionally leads it to a specific answer which they see as rightfully impressive, not realizing the information which they encoded in the question.
  - tribler 2y ago
    If you carefully study the actual prompt used: it already mentions the tail as a factor. Answer talks more on the tail. Just confidently! No double blind methodology protocol.
    - dmix 2y ago
      The power of suggestion, ala https://en.wikipedia.org/wiki/Mentalism https://en.wikipedia.org/wiki/Mentalism
  - booleandilemma 2y ago
    So like Clever Hans the horse, in a way? :) https://en.wikipedia.org/wiki/Clever_Hans https://en.wikipedia.org/wiki/Clever_Hans
    - killerteddybear 2y ago
      Very accurate comparison honestly -- pattern recognition without understanding or underlying knowledge.
patcon 2y ago
A thought occurred to me, as someone involved in some projects trying to recalibrate invectives for science funding: Good grad students are usually more intersectional across fields (compared to supervisors) and just more receptive to outsider ideas. They unofficially provide a lot of this same value that AI is about to provide established researchers. I wonder how AI is going to mess with the calculus of employing grad studies, and if this will affect the pipeline of future senior researchers...
skgough 2y ago
I'm getting the impression that this worked becaused the LLM had hoovered up all the previous research on this topic and found a reasonable string of words that could be a hypothesis based on what it found? I think we are starting to get to the root of the utility of LLMs as a technology. They are the next generation of search engines. But it makes me wonder, if we had thrown more resources towards using "traditional" search techniques on scientific papers, if we could have gotten here without gigawatts of GPU work spent on it, and a few years earlier?
steeeeeve 2y ago
I find this odd because that's exactly how I thought viruses worked when crossing species and I have no background that would lead me to that conclusion and have almost nothing in my life that would make me ponder such a thing. I feel like someone explained this in the 80s to me.
deleted 2y ago
[deleted]
camkego 2y ago
I’d like to know how we got an email back from Google confirming that they don’t have access to his computer
Frieren 2y ago
News already corrected. "Google Co-Scientist AI cracks superbug problem in two days! — because it had been fed the team’s previous paper with the answer in it" https://news.ycombinator.com/item?id=43162582#43163722 https://news.ycombinator.com/item?id=43162582#43163722 Let's see how many points gets the correction. It would be good that achieved the same or more visibility than this one to keep HN informative and truthful.
- rybthrow2 2y ago
  What about the other two use cases it came up repurposing existing drugs and identifying novel treatment targets for liver fibrosis as per the paper? https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ https://research.google/blog/accelerating-scientific-breakth...
  - colingauvin 2y ago
    This article claims only 3 of the new materials were actually snythesizable (and all had been previously known of), and that the drug for liver fibrosis had already been investigated for liver fibrosis. https://pivot-to-ai.com/2025/02/22/google-co-scientist-ai-cracks-superbug-problem-in-two-days-because-it-had-been-fed-the-teams-previous-paper-with-the-answer-in-it/ https://pivot-to-ai.com/2025/02/22/google-co-scientist-ai-cr...
    - rybthrow2 2y ago
      The snythesizable materials is another paper by deepmind not relying on LLMs and unrelated to this one. The article's author briefly mentions one of the other two findings without providing any sources to support the claim that they aren’t novel/useful? If it helps scientists find answers faster, I don’t see the problem—especially when the alternative is sifting through Google or endless research papers.
- basisword 2y ago
  When I first read this a few days ago the scientists explicitly stated that they hadn't published their results yet. Have they changed their story? From the BBC article on it: "He told the BBC of his shock when he found what it had done, given his research was not published so could not have been found by the AI system in the public domain." Also: Prof Penadés' said the tool had in fact done more than successfully replicating his research. "It's not just that the top hypothesis they provide was the right one," he said. "It's that they provide another four, and all of them made sense. "And for one of them, we never thought about it, and we're now working on that."
dotdi 2y ago
Maybe this is too tin-hatty, but sending the unpublished manuscript from (or to) a free Gmail account gives Google the right to use it, and therefore also to train whatever AI model they want with it. Sounds like all of those claims where ChatGPT allegedly coded a flappy bird clone from scratch. Only it didn't, it just regurgitated code from several Github repos.
- Lastminutepanic 2y ago
  [flagged]
  - dang 2y ago
    You're welcome to post your views to HN, but can you please not cross into personal attack or use swipey tropes like "My dude"? We're trying for a somewhat different sort of internet conversation here. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
gptacek 2y ago
"AI" didn't "crack" anything here. An LLM generated text that's notionally similar to a hypothesis this researcher was interested in but hadn't published. You can read Dr. Penades in his own words on BioRxiv, and if you might have been interested in reading the prompt or the output generated by co-scientist, it's included in the results and SI: https://www.biorxiv.org/content/10.1101/2025.02.19.639094v1 https://www.biorxiv.org/content/10.1101/2025.02.19.639094v1 What actually happened here looks more like rubber-ducking. If you look at the prompt (Supplementary Information 1), the authors provide the LLM with a carefully posed question and all the context it needed to connect the dots to generate the hypothesis. The output (Supplementary Information 2) even states outright what information in the prompt led it to the conclusion: "Many of the hypotheses you listed in your prompt point precisely to this direction. These include, but are not limited to, the adaptable tail-docking hypothesis, proximal tail recognition, universal docking, modular tail adaptation, tail-tunneling complex, promiscuous tail hypothesis, and many more. They collectively underscore the importance of investigating capsid-tail interactions and provide a variety of testable predictions. 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."
Lastminutepanic 2y ago
Lmao. Not at all surprised the BBC didn't even bother to look at this guy's Google scholar account. He has been publishing papers about this exact scenario for years. So have many other scientists. A few years back I was so sick of blockchain vaporware, and honestly couldn't think of anything more annoying... But several years of reading "serious" outlets publish stuff like "AI proves the existence of God", or "AI solves cold fusion in 15 minutes, running on a canon R6 camera" makes me wish for the carefree days of idiots saying "So you've heard of Uber, now imagine Uber, but it's on the blockchain, costs 0.1ETH just to book a ride, and your home address is publicly accessible"...
Lastminutepanic 2y ago
Here is the scientists Google scholar account. He has been publishing (and so have lots of other scientists, just look at the papers HE cites in previous work) about this exact scenario for years. This is just Google announcing a brand new AI tool (the scientist tool was literally just released in the past few days). And knew mainstream outlets have 1. No clue about how AI works, and 2. A pathological deference to anyone with lots of letters after their name from impressive places. https://scholar.google.com/citations?hl=en&user=rXUHiP8AAAAJ&view_op=list_works&sortby=pubdate https://scholar.google.com/citations?hl=en&user=rXUHiP8AAAAJ...
cbm-vic-20 2y ago
There is a real societal danger in ascribing abilities to "AI" that it just doesn't have.
aqueueaqueue 2y ago
Hey guys, I cracked the general theory of relativity in 30 seconds. Just got to find the right download!
gaiagraphia 2y ago
The article is pretty fucking trash, tbh. The '''journalist''' is, too: Author: https://muckrack.com/tom-gerken/articles https://muckrack.com/tom-gerken/articles
- gaiagraphia 2y ago
  [flagged]
est 2y ago
can't wait AI to discover tons of Ramanujan style math inventions.
marcus_holmes 2y ago
But they needed to have already solved the problem in order to be able to verify that the LLM hadn't just hallucinated a solution. (and I wonder how many hallucinated solutions the LLM came up and were rejected - sorry "refined" - by the team).
throwccp 2y ago
[dead]

250 points by monkeydust 2y ago

"LLMs are great at solving problems that already have solutions." This is performance art, right?

Using this, launched yesterday: Today Google is launching an AI co-scientist, a new AI system built on Gemini 2.0 designed to aid scientists in creating novel hypotheses and research plans. Researchers can specify a research goal — for example, to better understand the spread of a disease-causing microbe — using natural language, and the AI co-scientist will propose testable hypotheses, along with a summary of relevant published literature and a possible experimental approach. https://blog.google/feed/google-research-ai-co-scientist/ https://blog.google/feed/google-research-ai-co-scientist/

deleted 2y ago

[deleted]

root_axis 2y ago

> Critically, this hypothesis was unique to the research team and had not been published anywhere else. Nobody in the team had shared their findings This seems like the most important detail, but it also seems impossible to verify if this was actually the case. What are the chances that this AI spat out a totally unique hypothesis that has absolutely no corollaries in the training data, that also happens to be the pet hypothesis of this particular research team? I'm open to being convinced, but I'm skeptical.

mtrovo 2y ago
Define "totally unique hypothesis" in this context. If the training data contains studies with paths like A -> B and C -> D -> E, and the AI independently generates a proof linking B -> C, effectively creating a path from A -> E, is that original enough? At some point, I think we're going to run out of definitions for what makes human intelligence unique. > It also seems impossible to verify if this was actually the case. If this is a thinking model, you could always debug the raw output of the model's internal reasoning when it was generating an answer. If the agent took 48 hours to respond and we had no idea what it was doing that whole time, that would be the real surprise to me, especially since Google is only releasing this in a closed beta for now.
TrackerFF 2y ago
Could some of the scientists have saved their data in the google cloud, say using google drive? And then some internal google crawler went through, and indexed those files? I don't know that their policy says about that, or if it is even something they do...at least not publicly.
miyuru 2y ago
> "I wrote an email to Google to say, 'you have access to my computer, is that right?'", he added. sounds extra fishy, since google does not provide email support normally.
- Jimmc414 2y ago
  "Scientists who are part of our Trusted Tester Program will have early access to AI co-scientist" https://blog.google/feed/google-research-ai-co-scientist/ https://blog.google/feed/google-research-ai-co-scientist/
- bArray 2y ago
  Exactly my thought, probably the least likely part of the whole thing. He emailed Google and they replied. Not only that, he asked a question they would really rather not answer.
bArray 2y ago
Google openly train stuff based on your email, they used is specifically to train Smart Compose, but maybe other stuff too. He likely uses multiple Google products. Draft papers in Google Drive perhaps? These LLM models are essentially trying to produce material that sounds correct, perhaps the hypothesis was a relatively obvious question with the right domain knowledge. Additionally, he may not have been the first to ask the question. It's entirely possible that the AI chewed up and spat out some domain knowledge from a foreign research group outside of his wheelhouse. This kind of stuff happens all the time. I personally have accidentally reinvented things without prior knowledge of them. Many years ago in University I remember deriving a PID controller without being aware of what one was. I probably got enough clues from other people/media that were aware of them, that bridging that final gap was made easier.
- Jabbles 2y ago
  > We do not use your Workspace data to train or improve the underlying generative AI and large language models that power Gemini, Search, and other systems outside of Workspace without permission. https://support.google.com/meet/answer/14615114?hl=en#:~:text=We%20do%20not%20use%20your%20Workspace%20data%20to%20train%20or%20improve%20the%20underlying%20generative%20AI%20and%20large%20language%20models%20that%20power%20Gemini%2C%20Search%2C%20and%20other%20systems%20outside%20of%20Workspace%20without%20permission. https://support.google.com/meet/answer/14615114?hl=en#:~:tex... You may not believe them, but I challenge your description of it as "openly".
  - stonogo 2y ago
    Yeah, "Workspace data." If you don't think a scientist has copies of all his/her stuff in a personal Google account you've never met a scientist.
    - cwillu 2y ago
      The second half of the sentence is a bit awkward, but the first bit is pretty clear: “We do not use your Workspace data”
card_zero 2y ago
I wonder about a "clever Hans" effect, where they unwittingly suggest their discovery in their prompt. Also whether they got paid.
- cwillu 2y ago
  “ "It's not just that the top hypothesis they provide was the right one," he said. "It's that they provide another four, and all of them made sense. And for one of them, we never thought about it, and we're now working on that."”
  - card_zero 2y ago
    I wonder whether that one is really any good.
- graeme 2y ago
  May well be but in this case it would be a two way clever Hans which is very promising.

didntknowyou 2y ago

why did it take 48 hours? did he give the AI data to process or was it just a prompt. did it spit back out a conclusion or a list of possible scenarios it had scraped? seems like a PR stunt.

tecleandor 2y ago
While there is some stuff around this that sounds like PR (probably some intermediate results and/or SOTA on that field as of today could help reaching that result), the process seems interesting. Seems like it launches ahem "agents" that do simulations, verifications, refines and iterates over different options... and it takes a while: https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ https://research.google/blog/accelerating-scientific-breakth...

programmertote 2y ago

When I read "cracks superbug problem", I thought AI solved how to kill superbugs. From reading the article, it seems like AI suggested a few hypotheses and one of which is similar to what the researcher thought of. So in a way, it hasn't cracked the problem although it helped in forming ONE of the hypotheses, which needs to be tested in experiments(?) Just want to make sure I'm understanding what's written in the article accurately.

newsreaderguy 2y ago
it suggested other hypotheses as well, including one that they hadn't thought of and are investigating

fatbird 2y ago

So the AI didn't prove anything, it offered a hypothesis that wasn't in the published literature, which happened to match what they'd spent years trying to verify. I can see how that would look impressive, and he says that if he'd had this hypothesis to start with, it would have saved those years. Without those years spent working the problem, would he have recognized that hypothesis as a valuable road to go down? And wouldn't the years of verifying it still remain?

kachapopopow 2y ago

this might be a dupe and the title is completely misleading, it (the AI) simply provided one of the hypothesis (which took two years to confirm) as the top result. A group of humans can come up with these in seconds given expertise in the subject.

Over3Chars 2y ago

[flagged]

furyofantares 2y ago

It says it took them a decade, but they obviously published loads of intermediate results, as did anyone else working in the space. I get that they asked it about a new result they hadn't published yet, but the idea that it did it in two days when it took them a decade -- even though it's been trained on everything published in that decade, including whatever intermediate results they published -- probably makes this claim just as absurd as it sounds.

tippytippytango 2y ago
I’d bet the hypothesis was already in the training data. Someone probably suggested it in the future work section of some other paper.
- hinkley 2y ago
  One of the annoying things about the LZW compression patent was that it covered something Lempel and Ziv had already mentioned in the further study section of their original paper. Someone patented an “exercise left to the reader”.
gota 2y ago
Tentative rephrasing: "When given all of the facts we uncovered over a decade as premises, the computer system generated the conclusion instantly" edit - instantly is apparently many hours, hence the 'two days', just to be clear
vintagedave 2y ago
Maybe, but: > He told the BBC of his shock when he found what it had done, given his research was not published so could not have been found by the AI system in the public domain. and, > Critically, this hypothesis was unique to the research team and had not been published anywhere else. Nobody in the team had shared their findings.
- deleted 2y ago
  [deleted]

nurumaik 2y ago

>He gave "co-scientist" - a tool made by Google - a short prompt asking it about the core problem he had been investigating and it reached the same conclusion in 48 hours. Could it be the case when asking the right question is the key? When you know the solution already it's actually very easy to accidentally include some hints in your phrasing of question that will make task 10x easier

killerteddybear 2y ago
This is a very common mistake with LLMs I find. Lots of people who have high domain knowledge will be very impressed by it due to situations where they phrase questions in such a way that it unintentionally leads it to a specific answer which they see as rightfully impressive, not realizing the information which they encoded in the question.
- tribler 2y ago
  If you carefully study the actual prompt used: it already mentions the tail as a factor. Answer talks more on the tail. Just confidently! No double blind methodology protocol.
  - dmix 2y ago
    The power of suggestion, ala https://en.wikipedia.org/wiki/Mentalism https://en.wikipedia.org/wiki/Mentalism
- booleandilemma 2y ago
  So like Clever Hans the horse, in a way? :) https://en.wikipedia.org/wiki/Clever_Hans https://en.wikipedia.org/wiki/Clever_Hans
  - killerteddybear 2y ago
    Very accurate comparison honestly -- pattern recognition without understanding or underlying knowledge.

patcon 2y ago

A thought occurred to me, as someone involved in some projects trying to recalibrate invectives for science funding: Good grad students are usually more intersectional across fields (compared to supervisors) and just more receptive to outsider ideas. They unofficially provide a lot of this same value that AI is about to provide established researchers. I wonder how AI is going to mess with the calculus of employing grad studies, and if this will affect the pipeline of future senior researchers...

skgough 2y ago

I'm getting the impression that this worked becaused the LLM had hoovered up all the previous research on this topic and found a reasonable string of words that could be a hypothesis based on what it found? I think we are starting to get to the root of the utility of LLMs as a technology. They are the next generation of search engines. But it makes me wonder, if we had thrown more resources towards using "traditional" search techniques on scientific papers, if we could have gotten here without gigawatts of GPU work spent on it, and a few years earlier?

steeeeeve 2y ago

I find this odd because that's exactly how I thought viruses worked when crossing species and I have no background that would lead me to that conclusion and have almost nothing in my life that would make me ponder such a thing. I feel like someone explained this in the 80s to me.

deleted 2y ago

[deleted]

camkego 2y ago

I’d like to know how we got an email back from Google confirming that they don’t have access to his computer

Frieren 2y ago

News already corrected. "Google Co-Scientist AI cracks superbug problem in two days! — because it had been fed the team’s previous paper with the answer in it" https://news.ycombinator.com/item?id=43162582#43163722 https://news.ycombinator.com/item?id=43162582#43163722 Let's see how many points gets the correction. It would be good that achieved the same or more visibility than this one to keep HN informative and truthful.

rybthrow2 2y ago
What about the other two use cases it came up repurposing existing drugs and identifying novel treatment targets for liver fibrosis as per the paper? https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ https://research.google/blog/accelerating-scientific-breakth...
- colingauvin 2y ago
  This article claims only 3 of the new materials were actually snythesizable (and all had been previously known of), and that the drug for liver fibrosis had already been investigated for liver fibrosis. https://pivot-to-ai.com/2025/02/22/google-co-scientist-ai-cracks-superbug-problem-in-two-days-because-it-had-been-fed-the-teams-previous-paper-with-the-answer-in-it/ https://pivot-to-ai.com/2025/02/22/google-co-scientist-ai-cr...
  - rybthrow2 2y ago
    The snythesizable materials is another paper by deepmind not relying on LLMs and unrelated to this one. The article's author briefly mentions one of the other two findings without providing any sources to support the claim that they aren’t novel/useful? If it helps scientists find answers faster, I don’t see the problem—especially when the alternative is sifting through Google or endless research papers.
basisword 2y ago
When I first read this a few days ago the scientists explicitly stated that they hadn't published their results yet. Have they changed their story? From the BBC article on it: "He told the BBC of his shock when he found what it had done, given his research was not published so could not have been found by the AI system in the public domain." Also: Prof Penadés' said the tool had in fact done more than successfully replicating his research. "It's not just that the top hypothesis they provide was the right one," he said. "It's that they provide another four, and all of them made sense. "And for one of them, we never thought about it, and we're now working on that."

dotdi 2y ago

Maybe this is too tin-hatty, but sending the unpublished manuscript from (or to) a free Gmail account gives Google the right to use it, and therefore also to train whatever AI model they want with it. Sounds like all of those claims where ChatGPT allegedly coded a flappy bird clone from scratch. Only it didn't, it just regurgitated code from several Github repos.

Lastminutepanic 2y ago
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- dang 2y ago
  You're welcome to post your views to HN, but can you please not cross into personal attack or use swipey tropes like "My dude"? We're trying for a somewhat different sort of internet conversation here. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html

gptacek 2y ago

"AI" didn't "crack" anything here. An LLM generated text that's notionally similar to a hypothesis this researcher was interested in but hadn't published. You can read Dr. Penades in his own words on BioRxiv, and if you might have been interested in reading the prompt or the output generated by co-scientist, it's included in the results and SI: https://www.biorxiv.org/content/10.1101/2025.02.19.639094v1 https://www.biorxiv.org/content/10.1101/2025.02.19.639094v1 What actually happened here looks more like rubber-ducking. If you look at the prompt (Supplementary Information 1), the authors provide the LLM with a carefully posed question and all the context it needed to connect the dots to generate the hypothesis. The output (Supplementary Information 2) even states outright what information in the prompt led it to the conclusion: "Many of the hypotheses you listed in your prompt point precisely to this direction. These include, but are not limited to, the adaptable tail-docking hypothesis, proximal tail recognition, universal docking, modular tail adaptation, tail-tunneling complex, promiscuous tail hypothesis, and many more. They collectively underscore the importance of investigating capsid-tail interactions and provide a variety of testable predictions. 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."

Lastminutepanic 2y ago

Lmao. Not at all surprised the BBC didn't even bother to look at this guy's Google scholar account. He has been publishing papers about this exact scenario for years. So have many other scientists. A few years back I was so sick of blockchain vaporware, and honestly couldn't think of anything more annoying... But several years of reading "serious" outlets publish stuff like "AI proves the existence of God", or "AI solves cold fusion in 15 minutes, running on a canon R6 camera" makes me wish for the carefree days of idiots saying "So you've heard of Uber, now imagine Uber, but it's on the blockchain, costs 0.1ETH just to book a ride, and your home address is publicly accessible"...

Lastminutepanic 2y ago

Here is the scientists Google scholar account. He has been publishing (and so have lots of other scientists, just look at the papers HE cites in previous work) about this exact scenario for years. This is just Google announcing a brand new AI tool (the scientist tool was literally just released in the past few days). And knew mainstream outlets have 1. No clue about how AI works, and 2. A pathological deference to anyone with lots of letters after their name from impressive places. https://scholar.google.com/citations?hl=en&user=rXUHiP8AAAAJ&view_op=list_works&sortby=pubdate https://scholar.google.com/citations?hl=en&user=rXUHiP8AAAAJ...

cbm-vic-20 2y ago

There is a real societal danger in ascribing abilities to "AI" that it just doesn't have.

aqueueaqueue 2y ago

Hey guys, I cracked the general theory of relativity in 30 seconds. Just got to find the right download!

gaiagraphia 2y ago

The article is pretty fucking trash, tbh. The '''journalist''' is, too: Author: https://muckrack.com/tom-gerken/articles https://muckrack.com/tom-gerken/articles

gaiagraphia 2y ago
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est 2y ago

can't wait AI to discover tons of Ramanujan style math inventions.

marcus_holmes 2y ago

But they needed to have already solved the problem in order to be able to verify that the LLM hadn't just hallucinated a solution. (and I wonder how many hallucinated solutions the LLM came up and were rejected - sorry "refined" - by the team).

throwccp 2y ago

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