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New antibiotic targets IBD and AI predicted how it would work

healthsci.mcmaster.ca

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Re: New antibiotic targets IBD and AI predicted how it would work

#41
post #9
post #5

Earlier quoted context omitted.

It's also the case that there is a bewildering variety of things that get sort of lumped together as "IBD." Crohn's and ulcerative colitis are two of them, but there's no particular reason to assume inflammatory bowel diseases all have the same set of causes. Pretty much all of them are made worse by an e. coli infection, though, so a drug that can target just those bacteria is helpful! During my own IBD journey, I'v…

Doctors are the only people I’ve encountered who are ready to inform you of their poorly supported contradictory conclusions with full confidence, and are fully ready to meet any pushback with gaslighting or the dreaded “difficult patient” label. They approach the phenomenon of dropping trust and respect for their profession in much the same way. It’s really frustrating. I don’t get why they feel entitled to acting t…

After making you wait 40 minutes later than when your appointment was supposed to start, I’ve looked at your chart for about 2 minutes and have spoken to you 60 seconds I’ve confidently diagnosed you with X. Here’s a prescription, let’s see you back in 6 months.

Re: New antibiotic targets IBD and AI predicted how it would work

#42
post #38

In light of the meta context that this article reinforces the view that ai can replace researchers job I found this part of the artcile very true to how I use AI tools at work. "Stokes stresses that while the prediction was intriguing, it was just that — a prediction. He would still have to conduct traditional MOA studies in the lab. “Currently, we can’t just assume that these AI models are totally right, but the not…

Same. I note in-advance that I'm not sure whether you yourself are referring to use of LLM tools in your research or rather the results of your own domain specific application of deep learning etc -- here, I assume the former.

I feel like the common refrain of most LLM success stories over the past year is that these tools are of significantly greater help to specialists with "skin in the game", so to speak, than they are to complete amateurs. I think a lot of complaints about hallucinations reflect the experience of people who aren't working at the edge of a field where they've read all the existing literature and there simply aren't other places to turn for further leads. At the frontier, moreover, the probability that there exists a paper or book that covers the exact combination of topics that interests you is actually rather low; peer discussions are terrific, but everyone is time-starved.

Thus I find the synthetic ability of LLMs to tie together one's own field of focus with those you've never thought about or are less familiar with to be of incomparable utility. On top of that, the ability to help formulate potential hypotheses and leads -- where of course you the researcher are ultimately going to carry out the investigation or, in the best case, attempt to replicate results. Conversely, when I'm uncertain of my own conclusions, I often find myself feeding the best LLM I have access to the data I reasoned from to see whether it independently gets to the same place. I'm not concerned about hallucinations because I know there's nobody but me ultimately responsible for error -- and, at the fringe of knowledge, even a total fabrication can inspire a new (correct) approach to the matter at hand.

I think if I had to succinctly describe my own experience it would be that I never get stuck any more for days, weeks, months without even a hint of where to turn next.

Related, there's an ancient Palantir blog post (2010!) that always stuck in my memory about a chess tournament that allowed computers, grandmasters, amateurs and any combination of the above to enter [0]. At that time, the winning combination turned out to be amateurs with the best workflow for interfacing with machine. The moral of the story is probably still true (workflow is everything), but I think these new tools for the first time are really biased towards experts, i.e. the best workflow now is no longer "content neutral" but always emerges from a particular domain.

[0] https://web.archive.org/web/20120916051031/http://www.palant...

Re: New antibiotic targets IBD and AI predicted how it would work

#43
post #37
post #2

Here is the original study published in nature microbiology. https://www.nature.com/articles/s41564-025-02142-0 Wanted to share what I thought the interesting parts. From the university press release. "To date, AI has been leveraged as a tool for predicting which molecules might have therapeutic potential, but this study used it to describe what researchers call “mechanism of action” (MOA) — or how drugs attack disea…

Is DiffDock a large language model? Because that is what the general public believes AI means, and Open AI say they are building thinking machines with it, and this headline says ”predicted”.

[deleted]

Re: New antibiotic targets IBD and AI predicted how it would work

#45
post #38

In light of the meta context that this article reinforces the view that ai can replace researchers job I found this part of the artcile very true to how I use AI tools at work. "Stokes stresses that while the prediction was intriguing, it was just that — a prediction. He would still have to conduct traditional MOA studies in the lab. “Currently, we can’t just assume that these AI models are totally right, but the not…

AI is becoming a difficult term to grapple with, especially because the public just assumes AI = ChatGPT = "ChatGPT discovered a new medicine"

In reality, a lot of research uses a variety of different general ML tools that have almost nothing to do with transformers, much less LLMs.

Re: New antibiotic targets IBD and AI predicted how it would work

#46
post #38

In light of the meta context that this article reinforces the view that ai can replace researchers job I found this part of the artcile very true to how I use AI tools at work. "Stokes stresses that while the prediction was intriguing, it was just that — a prediction. He would still have to conduct traditional MOA studies in the lab. “Currently, we can’t just assume that these AI models are totally right, but the not…

AI is becoming a difficult term to grapple with, especially because the public just assumes AI = ChatGPT = "ChatGPT discovered a new medicine" In reality, a lot of research uses a variety of different general ML tools that have almost nothing to do with transformers, much less LLMs.

You know this water-muddling technique is being used on purpose, don't you? Most of the time to attract money. At least in this case the aim is noble.

Re: New antibiotic targets IBD and AI predicted how it would work

#47
post #38

In light of the meta context that this article reinforces the view that ai can replace researchers job I found this part of the artcile very true to how I use AI tools at work. "Stokes stresses that while the prediction was intriguing, it was just that — a prediction. He would still have to conduct traditional MOA studies in the lab. “Currently, we can’t just assume that these AI models are totally right, but the not…

Same. I note in-advance that I'm not sure whether you yourself are referring to use of LLM tools in your research or rather the results of your own domain specific application of deep learning etc -- here, I assume the former. I feel like the common refrain of most LLM success stories over the past year is that these tools are of significantly greater help to specialists with "skin in the game", so to speak, than the…

While I agree, one must be careful anyway. I'm ignorant in most fields, reasonably good at two, and quite good (but far from excellent) in one. So while there is a lot to learn in the former, when it comes to the latter, all LLMs, including SOTA models, give me a very high percentage of answers that are misleading, wrong, dangerously incomplete, only superficially correct, amalgamate of correct and incorrect bits etc. Knowing this first hand, repeatedly, on hundreds and hundreds of issues, I basically built a deep, methodological distrust towards LLMs answers. In the end, I assume the answer to be wrong, but I look for verifiable hints that could lead me in the right direction. This is my default working mode in my niche.

Re: New antibiotic targets IBD and AI predicted how it would work

#48
post #39

Machine-learning has been used in scientific research for a decade? Is there something new? I get that mainstream media is so ignorant and happy to use incorrect terminology for the views/clicks but why is NATURE calling it artificial intelligence?

Why not AI? It’s a generative diffusion model. They are typically bucketed into the term AI. Do you generally say all diffusion models are not AI?

Re: New antibiotic targets IBD and AI predicted how it would work

#50
post #5

Earlier quoted context omitted.

It's also the case that there is a bewildering variety of things that get sort of lumped together as "IBD." Crohn's and ulcerative colitis are two of them, but there's no particular reason to assume inflammatory bowel diseases all have the same set of causes. Pretty much all of them are made worse by an e. coli infection, though, so a drug that can target just those bacteria is helpful! During my own IBD journey, I'v…

Sounds like you first decimated the bacteria with antibiotics, and then made it heavily disadvantaged by eating something that preferentially feeds other gut bacteria. What was the food, out of curiosity?

Actually when I medicated it, it was with mesalamine, not an antibiotic. I didn't do anything to attack the bacteria.

The meal consisted of well-boiled meat (pork/beef/chicken together, slow cooked, overnight), and carrots, zucchini, and butternut squash cooked in its juice until it mostly wasn't soup anymore.

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