[HN Gopher] AI cracks superbug problem in two days that took sci...
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AI cracks superbug problem in two days that took scientists years
Author : monkeydust
Score : 149 points
Date : 2025-02-20 15:05 UTC (4 days ago)
(HTM) web link (www.bbc.co.uk)
(TXT) w3m dump (www.bbc.co.uk)
| monkeydust wrote:
| 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/
| root_axis wrote:
| > _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 wrote:
| 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.
| card_zero wrote:
| I wonder about a "clever Hans" effect, where they unwittingly
| suggest their discovery in their prompt. Also whether they got
| paid.
| cwillu wrote:
| " "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 wrote:
| I wonder whether that one is really any good.
| graeme wrote:
| May well be but in this case it would be a two way clever
| Hans which is very promising.
| TrackerFF wrote:
| 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 wrote:
| > "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 wrote:
| "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/
| bArray wrote:
| 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 wrote:
| 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 wrote:
| > 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#:~:tex.
| ..
|
| You may not believe them, but I challenge your description of
| it as "openly".
| stonogo wrote:
| 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 wrote:
| The second half of the sentence is a bit awkward, but the
| first bit is pretty clear: "We do not use your Workspace
| data"
| protimewaster wrote:
| Isn't it saying that it might be trained on Workspace
| data, but that the results of that training will only be
| used within the same Workspace?
| cwillu wrote:
| It's not being used to train the underlying generative
| AI.
| protimewaster wrote:
| Doesn't it only say it won't be trained for generative AI
| that works outside of the Workspace?
|
| > 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
|
| I.e., they could use it to train an LLM specific to your
| Workspace, but that training data wouldn't be used
| outside of the Workspace, for the general generative
| products.
| progval wrote:
| But a personal account is not Workspace, as Google
| Workspace is a B2B product, right?
| protimewaster wrote:
| Isn't that implying that they do train on Workspace data,
| but the results of the training won't be applied outside of
| the Workspace?
|
| It is an awful sentence, but I'm reading it as:
|
| > We do not use your Workspace data to train or improve the
| underlying generative AI and large language models [...]
| outside of Workspace [...].
|
| Which to me makes it sound like if the answer is in your
| Workspace, and you ask an LLM in your Workspace, it would
| be able to tell you the answer.
| collingreen wrote:
| What constitutes permission? Did we all give full
| permission (in Google's opinion) without knowing it in the
| dozens and dozens of pages of Eula and deluge of privacy
| policy changes? The other comments are valid but irrelevant
| if Google thinks (rightly or wrongly) that "by using this
| product you give permission to xyz".
|
| I'm reminded of when Microsoft said you didn't actually buy
| the Xbox even though you thought you did and they won in
| court to prevent people from changing or even repairing
| their own (well, Microsoft's I guess, even though the
| person paid for it and thought they bought it) machine.
| crazygringo wrote:
| > _Google openly train stuff based on your email_
|
| They do not.
|
| Many years ago, they served _customized ads_ based on your
| email. Then they _stopped_ that, even for free accounts,
| because it led to a lot of unfounded misunderstanding that
| "Google reads your email, Google trains on your email"...
| jsiepkes wrote:
| Can you prove they don't? Right now Google is losing in the
| AI space. I wouldn't be surprised if they went with "it's
| better to ask for forgiveness later than permission
| upfront".
| crazygringo wrote:
| Look at all their legal cost contracts like terms of
| service.
|
| Then also consider how all of their enterprise customers
| would switch to MS/AWS in a heartbeat if they found out
| Google was training on their private, proprietary data.
|
| Google Cloud has been a gigantic investment they've been
| making for well over a decade now. They're not going to
| throw away consumer and enterprise trust to train on a
| bunch of e-mail.
| Lastminutepanic wrote:
| I mean they never stopped "training on your email"... I'm
| sure they started of (back when they may not have had the
| code/compute to trawl and model from the body of the
| email), it was just the metadata they used to help build
| data for targeted marketing. And are still absolutely using
| metadata...
|
| But yeah, in this specific case, it is way less nefarious.
| Just one, or both, of Google, and the scientist, selling a
| new AI product, with a sensationalist, unrealistic story,
| in a huge, publicly funded, "serious" news outlet. At least
| when the NYtimes drools down it's chin at some AI
| vaporware, they may be getting a huge advertising buy, or
| someone there owns a lot of stock in the company... BBC
| can't even hide behind "well that's capitalism baby".
|
| I will say the prime minister and his red thatcherites have
| been obsessed with becoming a player in the AI industry...
| If you want a conspiracy theory i think is more likely
| haha.
| didntknowyou wrote:
| 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 wrote:
| 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-breakth...
| fatbird wrote:
| 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 wrote:
| 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.
| programmertote wrote:
| 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 wrote:
| it suggested other hypotheses as well, including one that they
| hadn't thought of and are investigating
| Over3Chars wrote:
| AI cracks super-profit problem. Fire staff and claim AI
| efficiency has made them redundant. Give executives bonuses for
| "efficiency".
| furyofantares wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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.
| jgalt212 wrote:
| I guess, but pretty much every LLM is trained with data
| outside the public domain--whether they admit to it, or not.
| mossTechnician wrote:
| Since a Google product output the result, it had access to
| the same knowledge base as Google itself - Search, Scholar,
| etc. And use of copyrighted data for research purposes has
| always been, as far as I know, considered fair use in AI
| training.
|
| Unfortunately, even if we wanted to, it might be impossible
| to attribute this success to the authors that it built
| upon.
| monkeydreams wrote:
| > considered fair use in AI training
|
| By AI trainers, if not by the authors whose works were
| encoded.
| fsckboy wrote:
| > _outside the public domain_
|
| public domain is a legal term meaning something like "free
| from copyright or license restrictions"
|
| I believe in this thread people mean not that but
| "published and likely part of the training corpus"
| furyofantares wrote:
| Right, the actual result they asked about was not published.
| But do a search for the author, they indeed have published
| loads of related stuff in the last decade even if not that
| actual result and even if not directly pointing at it.
| CivBase wrote:
| "New hammer builds house in hours that took construction
| workers months." Reads the same to me. They introduced a new
| tool to help with a task that sounds like it was already near
| completion.
|
| It is still a big accomplishment if the AI helped them solve
| the problem faster than they could have without it, but the
| headline makes it sound like it solved the problem completely
| from scratch.
|
| This kind of hyperbole is what makes me continue to be
| skeptical of AI. The technology is unquestionably impressive
| and I think it's going to play a big role in technology and
| advancement moving forward. But every breakthrough comes with
| such a mountain of fluff that it's impossible to sort the
| mundane from the extraordinary and it all ends up feeling like
| a marketing-driven bubble waiting to burst.
| nurumaik wrote:
| >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 wrote:
| 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 wrote:
| 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.
| booleandilemma wrote:
| So like Clever Hans the horse, in a way? :)
|
| https://en.wikipedia.org/wiki/Clever_Hans
| geophile wrote:
| So, maybe a much, much more impressive version of Clever Hans?
| (https://en.wikipedia.org/wiki/Clever_Hans)
|
| This is not to detract from the AIs accomplishment at all. If
| it read the scientist's prior work, then coming up with the
| same discovery as the scientist did is still astounding.
| manmal wrote:
| Or, put more negatively, like a mentalist?
| https://softwarecrisis.dev/letters/llmentalist/
| patcon wrote:
| 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 wrote:
| 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 wrote:
| 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.
| camkego wrote:
| I'd like to know how we got an email back from Google confirming
| that they don't have access to his computer
| Frieren wrote:
| 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
|
| 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 wrote:
| 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-breakth...
| colingauvin wrote:
| 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-
| cr...
| rybthrow2 wrote:
| 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 wrote:
| 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 Penades' 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."
| knowitnone wrote:
| "could not have been found by the AI system in the public
| domain." could he have been working in the cloud that exposed
| his unpublished paper to AI?
| kedean wrote:
| They hadn't published the latest paper, but the many papers
| leading up to this were published, and so its able to work
| off of those. I'm not an expert in this field, but in this
| case, it seems they had already published a paper that listed
| this idea as an option and dismissed it, so in all likelihood
| Co-Scientist simply ignored the theoretical limitation.
|
| Either way, the headline is garbage. It's like being amazed
| that your coworker who you've documented every step in your
| process to managed to solve that problem before you. "I've
| been working on it for months and they solved it in a day!"
| is obviously false, they have all of the information and
| conclusions you've been producing while you worked on it. In
| this case, telling the coworker every detail is the non-
| consensual AI training process.
| bilekas wrote:
| It's clear after you read the article but that title is really
| typical these days. It's frustrating as heck but I will admit,
| it made me click on the link to see what it was all about.
| Still super impressed all the same.
| ipsum2 wrote:
| That's not exactly right. The answer was not explicitly given,
| according to the source:
|
| "However, the team did publish a paper in 2023 - which was fed
| to the system - about how this family of mobile genetic
| elements "steals bacteriophage tails to spread in nature". At
| the time, the researchers thought the elements were limited to
| acquiring tails from phages infecting the same cell. Only later
| did they discover the elements can pick up tails floating
| around outside cells, too.
|
| So one explanation for how the AI co-scientist came up with the
| right answer is that it missed the apparent limitation that
| stopped the humans getting it.
|
| What is clear is that it was fed everything it needed to find
| the answer, rather than coming up with an entirely new idea.
| "Everything was already published, but in different bits," says
| Penades. "The system was able to put everything together.""
|
| https://www.newscientist.com/article/2469072-can-googles-new...
| letitgo12345 wrote:
| Or the humans did think of it and were actively proceeding to
| test that hypothesis
| slashdev wrote:
| Sometimes science isn't doing completely novel things, but
| combining ideas across different disciplines or areas.
|
| AI has some potential here, because unlike a human, AI can be
| trained across all of it and has the opportunity to make
| connections a human, with more limited scope, might miss.
| Borealid wrote:
| What matters isn't that an AI "make connections", it's that
| the AI generates some text that causes a human to make the
| connections. It doesn't even matter if what the AI
| generates is true or not, if it leads the human to truth.
|
| In this particular example it wasn't useful because the
| reader already knew the answer and was fishing for it with
| the LLM. But generally using an LLM as a creativity-inducer
| (a brainstorming tool) is fine, and IMO a better idea than
| trying to use them as an oracle.
| NoPicklez wrote:
| I think in your case both things matter, if the AI gives
| you the answer and/or if the AI leads you to the answer
| yourself.
| guelo wrote:
| I like to think of LLMs as amazing semantic search engines.
| Making these types of missed connections in vast lakes of
| existing data is not something humans are good at.
| dotdi wrote:
| 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 wrote:
| My dude... You're thinking way too hard, and giving everyone
| involved (the scientist and the journalist) WAYYY too much
| credit.
|
| Search the scientists name, click on his Google scholar
| account, and sort his published papers (the ones he literally
| submitted/linked to his scholar account), and you'll see years
| of published works, and all the papers HE referenced, regarding
| the exact bacterial defense mechanism he is talking about.
| gptacek wrote:
| "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
|
| 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 wrote:
| 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 wrote:
| 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...
| cbm-vic-20 wrote:
| There is a real societal danger in ascribing abilities to "AI"
| that it just doesn't have.
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