KalMann

This interview lasted over an hour. If he was answering wrong they should have said something.

I think this is disingenuous comparison. When we read a book we can estimate the amount of data we're taking in based on the character count (each character being represented by some fixed amount of bits).

What you're suggesting on the other hand is something akin to counting the number of pixels on each page we look at. That's absurd overestimate of the amount of data a person reading is actually taking in.

I really don't think your argument is very convincing. Some of your examples are downright ridiculous? "Jobs" Making a movie about one of the creation of some of one of the most famous companies on Earth is obviously interesting. That's not comparable at all.

I think there's been natural but steady progress with since 2024 with the release of the o1 model, which showed impressive reasoning capabilities. But I think it's wrong to look at the magnitude of the accomplishments and assume that will be field independent. We don't know the range of problems reasoning techniques are useful for. What we see here is refinement of capabilities that have been noticeable for years.

Maybe you need to phrase it better. Like with a more specific direction of thinking.

I think he's talking about reasoning models.

I think your analogy is good but I don't believe modern LLMs use Lean or any lean-like structure in their proofs. At least recent open source ones like DeepSeek can do advanced math without it (maybe the most cutting edge ones are doing it I can't say).

Not a physicist either but my understanding is that is that if you believe that we can discover all the laws of physics that explain how the world operates then it needs to have a solution.

Like we have formulas describing how gravity works. We can test these formulas by observing the motion of the planets and galaxies. Is this theory true? There's lots of evidence for it so it feels like it's gotta be pretty close to "the truth"

We also have formulas describing how elementary particles behave. These formulas have been tested to a very high degree of precision so it seems they've got to be close to the truth as well. But if you use both our formulas for gravitation and formulas for elementary particles you can derive a contradiction. So these two theories cannot simultaneously be true. There's got to be something wrong with them.

I suppose there's the possibility that at a certain point nature simply doesn't follow any laws and you can't possibly make sense of it.

Are you sure? I think "normies" would prefer to see and try on the clothes they buy.

I can give you the exact mathematical formula used to statistically optimize the output of a neural network from input examples. Can you do the same for the brain?

But we are? That's our education system.

That is not what the education system does. That's an obvious distortion of reality. People train over billions of documents to statistically predict the next word to gain and understanding of language. LLMs do this statistical processing in order to mimic humans natural language learning ability. And there has been continued evidence of the limitations of this approach to accurately mimic the totality of human cognition.

So are humans.

AI advocates are _way_ too confident about the nature human cognition. Questions that have been debated by philosophers and cognitive scientists for decades are now "obvious" according to you people, though you never provide any argument to support your statements.

Did you misstate your comment? The Jordan normal form is more general than spectral decomposition so it should come after.

I don't really see how this implies the above commenter's statement is "simply not true".

I think this was a failure. The gold standard should be that the if every human driver was replaced with an AI how well could the system function. This makes it look like things would be catastrophic. Thus, showing how humans continue to be much more versatile and capable than AI.

I suppose if you lower the standards for what you hope AI can accomplish it wouldn't be considered a failure.

This but with hate.

Why are you phrasing your correction in the form of a question? I think it's pretty reasonable to infer that he mistakenly thought it was a Stanford study because the link was from Stanford.

Further, an ad hominem is when a person attacks someone's character without any base.

That is not what an ad hominem is.

It does exactly the same, predicts tokens,

That is an absolutely wild claim you've made. You're being way to presumptious.

Models don't have access to "reality"

This is an explanation of why models "hallucinate" not a criticism for the provided definition of hallucination.

I think the problem with your post is that it started a list of "incorrect statements" with a statement that wasn't incorrect.

You're missing the point. Those kind of narrow AI applications are not the motivation for the trillions of dollars being poured into AI. Of course AI has a variety of applications many disciplines, as it has for decades. The motivation behind the massive investment in AI is as forgetfulness said, reap the benefits from "revolutionizing the workplace"

Aren't you forgetting about the software that makes it so easy and straightforward for newcomers to flash programs and experiment the microcontroller?

I'd try a some more if I were you. I saw an example of generated infographic that was greatly improved over anything I've seen an image generator do before. What you desire seems in the realm of possibility.

He probably meant to say "vector" the second time he said "matrix".

Expecting every little fact to have an "authoritative source" is just annoying faux intellectualism. You can ask someone why they believe something and listen to their reasoning, decide for yourself if you find it convincing, without invoking such a pretentious phrase. There are conclusions you can think to and reach without an "official citation".

I think his point is it means a lot in the context of investors seeking to make returns on their investments.

This seems like a strange comment to make since the above comment in no way suggests that we are currently in an AI winter.

Well I think you have to ask what the goal of the researchers are. In the case of fluid mechanics they may research new algorithms that make into the software mechanical engineers use, even if they don't understand the algorithms themselves for example. So mechanical engineers still benefit from the research.

So I guess what I'm wondering is if software engineers benefit from the research that software research produce? (even if they don't understand it themselves)

I don't get why people act like this definition is so circular. If you were to explain in detail what "transforms as a second rank tensor" means then it wouldn't be circular anymore. This just isn't the full definition.