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AI in my plasma physics research didn’t go the way I expected

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Re: AI in my plasma physics research didn’t go the way I expected

#161

Post by parodysbird »

Flamentono2 wrote: post #58
simianparrot wrote: post #28

Earlier quoted context omitted.

It’s why it keeps looking exactly like NFT’s and crypto hype cycles to me: Yes the technology has legitimate uses, but the promises of groundbreaking use cases that will change the world are obviously not materialising and to anyone that understands the tech it can’t. It’s people making money off hype until it dies and move on to the next scam-with-some-use.

We already have breakthroughs. Benchmark results which have been unheard of before ML. Alone language translation got so much better, voice syntesis, voice transcription. All my meetings now are searchable and i can ask 'ai' to summarize my meetings in a relative accurate way impossible before that. Alphafold made a breakthrough in protein folding. Image and Video generation can now do unbelievable things. Realtime v…

> Alphafold made a breakthrough in protein folding.

Sort of. Alphafold is a prediction tool, or, alternatively framed, a hypothesis generation tool. Then you run an experiment to compare.

It doesn't represent a scientific theory, not in the sense that humans use them. It does not have anywhere near something like the accuracy rate for hypotheses to qualify as akin to the typical scientific testing paradigm. It's an incredibly powerful and efficient tool in certain contexts and used correctly in the discovery phase, but not the understanding or confirmation phase.

It's also got the usual pitfalls with differentiable neural nets. E.g. you flip one amino acid and it doesn't really provide a proper measure of impact.

Ultimately, one major prediction breakthrough is not that crazy. If we compare that to e.g. Random Forest and similar models, the impact in science is infinitely more with them.

Re: AI in my plasma physics research didn’t go the way I expected

#162

Post by lossolo »

Flamentono2 wrote: post #140
whyowhy3484939 wrote: post #129

Earlier quoted context omitted.

> Just last week i asked for a script to do image segmentation with a basic UI and claude just generated that for me in under 1 Minute. Thing is we just see that it's copy pasting stack overflow, but now in a fancy way so this is sounding like "I asked Google for a nearby restaurant and it found it in like 500ms, my C64 couldn't do that". It sounds impressive (and it is) because it sounds like "it learned about navig…

I'm following LLMs, AI/ML for a few years now and not just on a high level. There is not a single system out there today which can do what claude can do. I stil see it for what it is: A technology i can communicate/use with natural language and get a very diverse of tasks done. From writing/generating code, to svgs, to emails, translation etc. etc. etc. Its a paradigma shift for the whole world literaly. We finally h…

> Its a paradigma shift for the whole world literaly.

That's hyperbolic. I use LLMs daily. They speed up tasks you'd normally use Google for and can extrapolate existing code into other languages. They boost productivity for professionals, but it's not like the discovery of the steam engine or electricity.

> And what limitations are obvious? Tell me? We have not reached any real ceiling yet.

Scaling parameters is the most obvious limitation of the current LLM architecture (transformers). That’s why what should have been called GPT-5 is instead named GPT 4.5, it isn’t significantly better than the previous model despite having far more parameters, a lot more cleaned up training data and optimizations.

The low-hanging fruit has already been picked, and most obvious optimizations have been implemented. As a result, almost all leading LLM companies are now operating at a similar level. There hasn’t been a real breakthrough in over two years. And the last huge architectural breakthrough was in 2017 (with paper "Attention is all you need").

Scaling at this point yields only diminishing returns. So no, what you’re saying isn’t accurate, the ceiling is clearly visible now.

Re: AI in my plasma physics research didn’t go the way I expected

#163

Post by boxed »

montebicyclelo wrote: post #90
plasticeagle wrote: post #25

Does anybody else find it peculiar that the majority of these articles about AI say things like "of course I don't doubt that AI will lead to major discoveries", and then go on to explain how they aren't useful in any field whatsoever? Where are the AI-driven breakthroughs? Or even the AI-driven incremental improvements? Do they exist anywhere? Or are we just using AI to remix existing general knowledge, while making…

> then go on to explain how they aren't useful in any field whatsoever > Where are the AI-driven breakthroughs > are we just using AI to remix existing general knowledge, while making no progress of any sort in any field using it? The obvious example of a highly significant AI-driven breakthrough is Alphafold [1]. It has already had a large impact on biotech, helping with drug discovery, computational biology, protei…

I'm personally waiting for the other shoe to drop here. I suspect that, since nature begins with an existing protein and modifies it slightly, AlphaFold is crazy overfitted to the training data. Furthermore, the enormous success of AlphaFold means that the number of people doing protein structure solving has likely crashed.

So not only are we using an overfitting model that probably can't handle truly novel proteins, we have stopped actually doing the research to notice when this happens. Pretty bad.

Re: AI in my plasma physics research didn’t go the way I expected

#164

Post by ktallett »

closewith wrote: post #155
ktallett wrote: post #149

Earlier quoted context omitted.

You would be wrong. I am actually quite perky, I just don't suffer foolish admin tasks easily. I only have meetings with a goal (not just for the sake of it), and then I simply make sure it is clear what the solution is, no matter whose idea it was. I don't care about being right or wrong in a meeting, I care that we have a useful outcome and it isn't an hour wasted. Having a meeting whereby the outcome of a meeting…

[flagged]

You can have your opinion on that.

Re: AI in my plasma physics research didn’t go the way I expected

#165

Post by boxed »

swyx wrote: post #63
plasticeagle wrote: post #25

Does anybody else find it peculiar that the majority of these articles about AI say things like "of course I don't doubt that AI will lead to major discoveries", and then go on to explain how they aren't useful in any field whatsoever? Where are the AI-driven breakthroughs? Or even the AI-driven incremental improvements? Do they exist anywhere? Or are we just using AI to remix existing general knowledge, while making…

> Where are the AI-driven breakthroughs? Or even the AI-driven incremental improvements? literally last week https://deepmind.google/discover/blog/alphaevolve-a-gemini-p...

Yea, except that we see "breakthrough" stuff like this all the time, and it almost always is quickly found out that it's fraudulent in some way. How many times are we to be fooled before we catch on and don't believe press releases with massive selection bias?

Re: AI in my plasma physics research didn’t go the way I expected

#166

Post by currymj »

plasticeagle wrote: post #25

Does anybody else find it peculiar that the majority of these articles about AI say things like "of course I don't doubt that AI will lead to major discoveries", and then go on to explain how they aren't useful in any field whatsoever? Where are the AI-driven breakthroughs? Or even the AI-driven incremental improvements? Do they exist anywhere? Or are we just using AI to remix existing general knowledge, while making…

AlphaFold is real.

To the extent you care about chess and Go as human activities, progress there is real.

there are some other scientific computing problems where AI or neural-network-based methods do appear to be at least part of the actual state-of-the-art (weather forecasting, certain single-molecule quantum chemistry simulations).

i would like the hype of the kind described in the article to be punctured, but this is hard to do if critics make strong absolute claims ("aren't useful in any field whatsoever") which are easily disproven. it hurts credibility.

Re: AI in my plasma physics research didn’t go the way I expected

#167

Post by literalAardvark »

currymj wrote: post #166
plasticeagle wrote: post #25

Does anybody else find it peculiar that the majority of these articles about AI say things like "of course I don't doubt that AI will lead to major discoveries", and then go on to explain how they aren't useful in any field whatsoever? Where are the AI-driven breakthroughs? Or even the AI-driven incremental improvements? Do they exist anywhere? Or are we just using AI to remix existing general knowledge, while making…

AlphaFold is real. To the extent you care about chess and Go as human activities, progress there is real. there are some other scientific computing problems where AI or neural-network-based methods do appear to be at least part of the actual state-of-the-art (weather forecasting, certain single-molecule quantum chemistry simulations). i would like the hype of the kind described in the article to be punctured, but thi…

Even more relvant, AlphaEvolve is real.

Could easily be brick 1 of self-improvement and the start of the banana zone.

Re: AI in my plasma physics research didn’t go the way I expected

#168

Post by Flamentono2 »

whyowhy3484939 wrote: post #146
Flamentono2 wrote: post #140

Earlier quoted context omitted.

I'm following LLMs, AI/ML for a few years now and not just on a high level. There is not a single system out there today which can do what claude can do. I stil see it for what it is: A technology i can communicate/use with natural language and get a very diverse of tasks done. From writing/generating code, to svgs, to emails, translation etc. etc. etc. Its a paradigma shift for the whole world literaly. We finally h…

> We finally have a system which encodes not just basic things but high level concepts That's the thing I'm trying to convey: it's in fact not encoding anything you'll recognize and if it is, it's certainly not "concepts" as you understand them. Not saying it cannot correlate text that includes what you call "high level concepts" or do what you imagine to be useful work in that general direction. Again not making cla…

I do understand it but i also think that the current LLMs are the first step to it.

GPT-3 started proper investment into this topic, there was not enough research done in this direction and now it is. People like Yann LeCun already analyse different approaches/architecture but they still use the infrastructure of LLMs (ML/GPUs) and potentially the data.

I never said that LLM is the breaktrhough in consesnes.

But you can also ask LLM strategies for thinking. It can tell you a lot of things. We will see if a LLM will be a fundamental part of AGI or not but GPU/ML will probably be.

I also think that the compression mechanism through LLM lead to concepts through optimization. You can see from the antropic paper, that an LLM doesn't work in normal language space but in a high dimensional one and then 'expresses' the output in a language you like.

We also see that real multi modal models are better in a lot of tasks due to a lot more context available through them. Estimating what someone said due to context.

The necessary infrastructure and power requirement is something i accept too. We can assume, i do, that further progress in a lot of topics will require this type of compute and it also solves our data bottleneck: normal CPU architecture is limited by memory databus.

Also in comparision to a lot of other companies, if the richest companies in the world invest in nuclear, i think this is a lot better than any other companies. They have a lot higher margins and knowledge. co2 is a market separator for them too.

I also expect this amount of compute to be the base for fixing real issues we all face like cancer or optimizing cancer or any other sickness detection. We need to make medicin a lot cheaper and if someone in africa can do a cheap x ray and send it to the cloud to get any feedback, that would / could help a lot of people.

Doing complex and massive protein analysis or mRna research in virtual space, also requires GPUs.

All of this happened in a timespan of only a few years. I have not seen anything progressing as fast as AI/ML currenly does and as unfortunate it is, this needs compute.

Even my small inhouse image recognition fine tuning explodes when you do a handful parameter optimizations but the quality is a lot better than what we had before.

And enabling people to have real natural language UI is HUGE. It makes so much more accessable. Not just for people with a disability.

Things like 'do a eli5 on topic x'. "explain to me this concept" etc. I would have loved that when i tried to be successful in the university math curiculum.

All of that is already crazy and still is. But in parallel what Nvidia and others currently do with ML and Robotics is also something which requires all of that compute. And the progress is again breath taking. The current flood of basic robots standing and walking around is due to ML.

Re: AI in my plasma physics research didn’t go the way I expected

#169

Post by Closi »

roenxi wrote: post #138
strogonoff wrote: post #48

Earlier quoted context omitted.

There is rarely a constructive discussion around the term “AI”. You can’t say anything useful about what it might lead to or how useful it might be, because it is purely a marketing term that does not have a specific meaning (neither do both of the words in its abbreviation). Interesting discussions tend to avoid “AI” in favour of specific terms such as “ML”, “LLM”, “GAN”, “stable diffusion”, “chatbot”, “image genera…

Also, the strong predictions about AI are using a vague term because the tech often doesn't exist yet. There isn't a chatbot right now that I feel confident can out-perform me at systems design but I'm pretty certain something that can is coming. Odds are also good that in 2-4 years there will be new hotness to replace LLMs that are much more functional (maybe MLLMs, maybe called something else). We can start to pred…

Totally agree.

Also the term 'LLM' is more about the mechanics of the thing than what the user gets. LLM is the technology, but some sort of automated artificial intelligence is what people are generally buying.

As an example, when people use ChatGPT and get an image back, most don't think "oh, so the LLM called out to a diffusion API?" - they just think "oh chat GPT can give me an image if I give it a prompt".

Although again, the term is entirely abused to the extent that washing machines can contain 'AI'. Although just because a term is abused doesn't necessarily mean it's not useful - everything had "Cloud" in it 10 years ago but that term was still useful enough to stick around.

Perhaps there is an issue that AI can mean lots of things, but I don't know yet of another term that encapsulates the last 5 years advancements in automated intelligence, and what that technology is likely to be moving forwards, which people will readily recognise. Perhaps we need a new word, but AI has stuck and there isn't a good alternative yet, so is probably here to stay for a bit!

Re: AI in my plasma physics research didn’t go the way I expected

#170

Post by sanderjd »

Flamentono2 wrote: post #64

I'm not sure why people on HN (of all places) are so divided regarding the perception of AI/ML. I have not seen anything like it before. We literaly had not system or way of even doing things like code generation based on text input. Just last week i asked for a script to do image segmentation with a basic UI and claude just generated that for me in under 1 Minute. I could list tons of examples which are groundbreaki…

HN is always divided on "how much is the currently hype-y technology real vs just hype".

I've seen this over and over again and been on different sides of the question on different technologies at different times.

To me, this is same as it ever was!

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