Deep learning gets the glory, deep fact checking gets ignored • Hacker News Board

Re: Deep learning gets the glory, deep fact checking gets ignored

#101

Post by imiric » Wed, Jun 04, 2025, 11:35 AM UTC

aucisson_masque wrote: post #9

It’s like fake news is taking in science now. Saying any stupid thing will attract much more view and « likes » than those debunking them. Except that we can’t compare twitter to nature journal. Science is supposed to be immune to these kind of bullshit thanks to reputed journals and pair reviewing, blocking a publication before it does any harm. Was that a failure of nature ?

> Science is supposed to be immune to these kind of bullshit

You have misplaced confidence in the scientific method. It was never immune to corruption, either by those deliberately manipulating it for their personal gain, or simply due to ignorance and bad methodology. We have examples of both throughout history. In either case, peer review is not infallible.

The new problem introduced by modern AI tools is that they drastically lower the skill requirement for anyone remotely capable in the field to generate data that appears correct on the surface, with relatively little effort and very quickly, while errors can only be discovered by actual experts in the field investing considerable amounts of time and resources. In some fields like programming the required resources to review code are relatively minor, but in fields like biology this (from what I've read) is much more difficult and expensive.

But, yes, science is being flooded with (m|d)isinformation, just like all our other media channels.

Re: Deep learning gets the glory, deep fact checking gets ignored

#102

Post by pessimizer » Wed, Jun 04, 2025, 11:39 AM UTC

Kiyo-Lynn wrote: post #92

eru wrote: post #90

Earlier quoted context omitted.

People typically get paid as a thank you for their corporate work, not just a lukewarm 'thanks for pointing that out.'

A lot of the time, the work we do doesn’t get much recognition, and barely gets seen.But maybe it still helped in some small way. Thinking about that makes it feel a little less disappointing.

Why would you want to help a corporation, rather than being paid? A company's goals aren't the same as yours. The reason it isn't paying you is that its main goal is to make more money than it spends. It doesn't care whether you make more money than you spend.

Re: Deep learning gets the glory, deep fact checking gets ignored

#103

Post by imiric » Wed, Jun 04, 2025, 11:48 AM UTC

BlueTemplar wrote: post #86

imiric wrote: post #76

It's interesting to see this article in juxtaposition to the one shared recently[1], where AI skeptics were labeled as "nuts", and hallucinations were "(more or less) a solved problem". This seems to be exactly the kind of results we would expect from a system that hallucinates, has no semantic understanding of the content, and is little more than a probabilistic text generator. This doesn't mean that it can't be use…

Heh, reminds me of cryptocurrencies... Or even of the Internet in general. I guess it's a common pitfall with information or communication technologies ? (Heck, or with technologies in general, but non-information or communication ones rarely scale as explosively...)

It's a common symptom of the Gartner hype cycle.

This doesn't mean that there aren't very valid use cases for these technologies that can benefit humanity in many ways (and I mean this for both digital currencies and machine learning), but unfortunately those get drowned out by the opportunity seekers and charlatans that give the others the same bad reputation.

As usual, it's best to be highly critical of opinions on both extreme sides of the spectrum until (and if) we start climbing the Slope of Enlightenment.

Re: Deep learning gets the glory, deep fact checking gets ignored

#104

Post by pessimizer » Wed, Jun 04, 2025, 11:49 AM UTC

godelski wrote: post #71

somenameforme wrote: post #52

Earlier quoted context omitted.

Almost nobody is "anti-science". The source of that labeling and division came from appeals to authority. You must do or believe this because it's "the science." If you don't, or you disagree, then you are anti-science. It has nothing to do with science, but rather people not finding that a sufficient justification for unpopular actions. For instance it's 100% certain that banning sugary drinks would dramatically imp…

> Almost nobody is "anti-science". Last I checked: - 15% of Americans don't believe in Climate Change[0] - 37% believe God created man in our current form within the last ~10k years (i.e. don't believe in evolution)[1] I don't think these are just rounding errors. They're large enough numbers that you should know multiple people who hold these beliefs unless you're in a strong bubble. I'm obviously with you in news a…

According to your model, scientists who believe in God are anti-science.

That's almost weirder than declaring that 15% of people not believing in anthropogenic global warming is some sort of crisis. It's a theory that seems to fit the data (with caveats), not an Axiom of Science.

It's actually bizarre that 85% of people trust Science so much that they would believe in something that they have never seen any direct evidence of. That's a result of marketing. The public don't believe in global warming because it's "correct"; they have no idea if it's correct, and they often believe in things that are wrong that people in white coats on television tell them.

Re: Deep learning gets the glory, deep fact checking gets ignored

#105

Post by [deleted] » Wed, Jun 04, 2025, 11:56 AM UTC

amelius wrote: post #2

Before making AI do research, perhaps we should first let it __reproduce__ research. For example, give it a paper of some deep learning technique and make it produce an implementation of that paper. Before it can do that, I have no hope that it can produce novel ideas.

[deleted]

Re: Deep learning gets the glory, deep fact checking gets ignored

#106

Post by bluGill » Wed, Jun 04, 2025, 12:05 PM UTC

teruakohatu wrote: post #96

b0a04gl wrote: post #66

Man, I’ve been there. Tried throwing BERT at enzyme data once—looked fine in eval, totally flopped in the wild. Classic overfit-on-vibes scenario. Honestly, for straight-up classification? I’d pick SVM or logistic any day. Transformers are cool, but unless your data’s super clean, they just hallucinate confidently. Like giving GPT a multiple-choice test on gibberish—it will pick something, and say it with its chest.…

> Like giving GPT a multiple-choice test on gibberish—it will pick something, and say it with its chest. If I gave a classroom of under grad students a multiple choice test where no answers were correct, I can almost guarantee almost all the tests would be filled out. Should GPT and other LLMs refuse to take a test? In my experience it will answer with the closest answer, even if none of the options are even remotely…

In multiple choice if you don't know then a random guess is your best answer in most cases. In a few tests blank is scored better than wrong but that is rare and the professors will tell you.

as such I would expect students to but in something. However after class they would talk about how bad they think they did because they are all self aware enough to know where they guessed.

Re: Deep learning gets the glory, deep fact checking gets ignored

#107

Post by rsfern » Wed, Jun 04, 2025, 12:07 PM UTC

r3trohack3r wrote: post #68

softwaredoug wrote: post #29

We also love deep cherry picking. Working hard to find that one awesome time some ML / AI thing worked beautifully and shouting its praises to the high heavens. Nevermind the dozens of other times we tried and failed...

Dude. I just asked my computer to write [ad lib basic utility script] and it spit out a syntactically correct C program that does it with instructions for compiling it. And then I asked it for [ad lib cocktail request] and got back thorough instructions. We did that with sand. That we got from the ground. And taught it to talk. And write C programs. Never mind what? That I had to ask twice? Or five times? What maximu…

This is all awesome, but a bit off topic for the thread which focuses on AI for science

The disconnect here is that the cost of iteration is low and it’s relatively easy to verify the quality of a generated C program (does the compiler issue warnings or errors? Does it pass a test suite?) or a recipe (basic experience is probably enough to tell if an ingredient sends out of place or proportions are wildly off)

In science, verifying a prediction is often super difficult and/or expensive because at prediction time we’re trying to shortcut around an expensive or intractable measurement or simulation. Unreliable models can really change the tradeoff point of whether AI accelerates science or just massively inflated the burn rate

Re: Deep learning gets the glory, deep fact checking gets ignored

#108

Post by [deleted] » Wed, Jun 04, 2025, 12:09 PM UTC

pessimizer wrote: post #102

Kiyo-Lynn wrote: post #92

Earlier quoted context omitted.

A lot of the time, the work we do doesn’t get much recognition, and barely gets seen.But maybe it still helped in some small way. Thinking about that makes it feel a little less disappointing.

Why would you want to help a corporation, rather than being paid? A company's goals aren't the same as yours. The reason it isn't paying you is that its main goal is to make more money than it spends. It doesn't care whether you make more money than you spend.

[deleted]

Re: Deep learning gets the glory, deep fact checking gets ignored

#109

Post by bluGill » Wed, Jun 04, 2025, 12:10 PM UTC

pessimizer wrote: post #102

Kiyo-Lynn wrote: post #92

Earlier quoted context omitted.

A lot of the time, the work we do doesn’t get much recognition, and barely gets seen.But maybe it still helped in some small way. Thinking about that makes it feel a little less disappointing.

Why would you want to help a corporation, rather than being paid? A company's goals aren't the same as yours. The reason it isn't paying you is that its main goal is to make more money than it spends. It doesn't care whether you make more money than you spend.

by paying me enough to stay I will continue to produce value.

Re: Deep learning gets the glory, deep fact checking gets ignored

#110

Post by stevenae » Wed, Jun 04, 2025, 12:24 PM UTC

b0a04gl wrote: post #66

Man, I’ve been there. Tried throwing BERT at enzyme data once—looked fine in eval, totally flopped in the wild. Classic overfit-on-vibes scenario. Honestly, for straight-up classification? I’d pick SVM or logistic any day. Transformers are cool, but unless your data’s super clean, they just hallucinate confidently. Like giving GPT a multiple-choice test on gibberish—it will pick something, and say it with its chest.…

> Lately, I just steal embeddings from big models and slap a dumb classifier on top. Works better, runs faster, less drama.

You may know this but many don't -- this is broadly known as "transfer learning".