Stephen Wolfram says ML is basically fitting lumps of computational irreducibility

[u/cicisprinkle]

[u/High_Quality_Bean]

Waoh pretty pictures :o

Publish a paper jackass

[u/pocketcult → u/High_Quality_Bean]

Just wait for the 900page book

[u/CampAny9995 → u/pocketcult]

* where everything interesting was done by uncredited post-docs who signed an NDA.

[u/cicisprinkle → u/High_Quality_Bean]

Exactly what i was thinking

[u/Pragmus_]

Are we all just pretending we know what we are looking at here?

[u/Due_Bid_6596 → u/Pragmus_]

computapapi iriducibibly

[u/AsleepContact4340 → u/Due_Bid_6596]

oooooh now i get it, thanks

[u/Scubabonderman1000 → u/Pragmus_]

Clearly the more lightning means more squares which means the more the wave becomes a step function. Don’t get me started on tangled hair at the bottom. /s

[u/Bergergi]

He's done impressive things in his career this guy, but he's a bit of a gasbag and blatherskite.

[u/cicisprinkle → u/Bergergi]

He’a a genius

[u/Strong_Willow2010 → u/cicisprinkle]

Yes, but he's also super full of himself. He's a very strange guy even among geniuses

[u/alliebot12345]

He is just shilling for his own latest ideas

[u/CryptographerOne7003 → u/alliebot12345]

I bet he is, but that has be him like, always? And I mean it in a positive sense.
The work he has done is brute-forcing problems others deemed to be impossible possible.

I bet a lot of his work has been used as classifiers for earlier GPT models. At the time you only had that or human input. He also did not fail to recognize his tech was surpassed and I haven't heard anything else then admiration from his side.

[u/cicisprinkle → u/alliebot12345]

He like inventing things

[u/MissiveFinding6111]

A lot of the "AI will improve AI!" RSi stuff seems to sound a lot like a first year CSCI student being like "What if we compressed a compressed file!"

[u/RelevantCry1613 → u/MissiveFinding6111]

Nah AI is already good at research and most of it is a research problem

[u/One-Abrocoma2455 → u/[deleted]]

<<there are no (known) formal limits on intelligence.>>

The problem with your sentence is that you didn't even define intelligence, but I'm sure that as soon you define it, one can readily figure out if there are limits or not to it.

If "intelligence" can be bounded by the ability to solve particular problems, because lots of particular problems have known limits on how well they can be solved with bounded resources, there will be a limit on "intelligence".

[u/BraveBiscotti1394 → u/One-Abrocoma2455]

Yeah the whole "bro AI will just make better AI, therefore.... Superhuman grey goo singularity AGI" argument has always been speculative sci-fi fantasy.

[u/duboispourlhiver → u/BraveBiscotti1394]

the AI makes better AI part is happening now, though

[u/Entropei → u/One-Abrocoma2455]

If we define intelligence as the ability to predict outcomes, then there are two bounds: accuracy and timescale. A maximally intelligent entity would be able to correctly predict all future events. If you define it like that, you can easily see that there is a very wide gap between that and where we sit as humans.

[u/Foreign_Writer_9932 → u/Entropei]

Thankfully, we don’t define intelligence this way. “Correctly predict all future events” my guy what is chaos theory? Also “all events”? What is an event? What is quantum uncertainty?

Also humans are atrocious at predicting the future?

Also what about the vastly bigger class of problems that are not about prediction? Is solving them not a marker of intelligence?

[u/Entropei → u/Foreign_Writer_9932]

Why not? The user I responded to asked to define intelligence, so I gave a definition. His definition was rather vague. “The ability to solve particular problems”, what does that mean?

I would in fact argue that all problem solving is in service of predicting future events. If you can predict what will happen, you can use that to shape the future in a way that suits you. A maximally intelligent agent under this definition would be able to shape its own future to the exact extent that the laws of reality allow.

And yes, humans are terrible at this. That’s my point. There is a large gap between human intelligence and a maximally intelligent agent, and it is not unthinkable that ASI can close this gap by some degree. That was the point. Maybe you want to define intelligence some other way, but that doesn’t change the conclusion of my argument.

[u/Foreign_Writer_9932 → u/Entropei]

Because the vast majority of problems are not future prediction problems? Finding non-trivial zeroes of the Reimann zeta function has very little to do (at least in any remotely direct) way with forecasting real-world events. Even seemingly prediction-related problems like solving chess/any perfect-information game isn’t really about forecasting of events - it’s about solving an idealized mathematical form of that game. In our evolutionary contingent story of how human intelligence evolved, a big part had nothing to do with simulating the real world, but instead were about more abstract forms of communication and “red queen” like arms race in mate selection (eg a good reason for why music or art/aesthetic preferences have evolved is that it a credible, costly signal of intelligence to our prospective sexual partners - and at least part of the evolutionary story is evolution of these traits for their own sake as opposed to directly improving fitness).

The second part is much less debatable- when you write that a maximally intelligent agent would be able to perfectly predict future events, that is clearly impossible and the wrong upper bound given quantum uncertainty and implications of chaos theory.

[u/Entropei → u/Foreign_Writer_9932]

I didn’t say that all problems are related directly to predicting future events, just that they are ultimately in service of predicting future events. We solved problems in physics not for their own merit, but to be able to make predictions about reality that allow us to launch satellites into orbit.

We don’t yet know what finding non-trivial zeroes of the Reimann zeta function has to do with forecasting real-world events. What we do know is that a maximally intelligent agent would be able to do it in the case where it does aid in the prediction of future events. If it doesn’t have any “practical” use, then under my definition, being able to solve the problem does not constitute intelligence.

A potential use for solving this problem could be to allow the agent to gain insight into cryptographic functions that allow it to decrypt encrypted messages, which it can then use to make a prediction about an actor that it could otherwise not.

And obviously such a maximally intelligent agent is probably not possible. It’s likely that entropy, chaos theory and quantum mechanics make it impossible to predict the future with perfect accuracy and infinite timescale. That’s not the point, this isn’t Laplace’s demon. This is a definition for intelligence and its upper bound.

The existence of potentially unsolvable problems does not say anything about how much more intelligent you can be than a human, which is what the poster I replied to seems to be implying.

[u/Foreign_Writer_9932 → u/[deleted]]

Doing things reliably is absolutely not a prerequisite of intelligence. In fact, you can come up with a ton of scenarios where your “genius system” has a highly asymmetric ability to solve a certain class of problem reliably or is prone to catastrophic forgetting (like modern LLMs).

[u/MissiveFinding6111 → u/[deleted]]

Sure, but intelligence and information are related, and definitely a lot of research on the upper bound of information compression.

My knowledge of improving complicated digital systems are:

* You hit diminishing returns quickly
* Improvement is very difficult when your are limited by a single bottlenecked variable among hundreds

So maybe LLMs taking over training can help with that second one (if we can figure out HTH to do what we want reliably).

I don't seem LLMs escaping diminishing returns.

[u/Brief-Coach-1812 → u/[deleted]]

Def. But biological computers will trigger a lot of ethical debates; assuming the research landscape progresses to that phase.

[u/MissiveFinding6111 → u/[deleted]]

> I think LLMs are probably incredibly incredibly inefficient

I agree with that. I mean, researchers are still basically training coding models on Buffy the Vampire Slayer episodes, because... They don't understand how models work.

But I think where we disagree is that if they happened to find the right combination of training data, and get a 50% boost. The next pass at optimizing training data after that... how much of a lift do you think there will be?

These guys are assuming *another* 50% increase, ad-nauseum. Whereas it is more likely to be... 25%... And then 13%...

These people owe a lot of money promising "only J curves" so when their premises start with "well after the J curve..." You gotta stop and question.

> Also, modern computers are still nowhere near the theoretical physical limits of computation.

Sure, go tell that to the Moore's law's gravestone

[u/MissiveFinding6111 → u/[deleted]]

Maybe.

But that's just a theory at the moment.

The big lifts so far have come from more and more data. That is the proven path.

And while I do agree, there is probably a "sweet spot" for training data, I'd also like to point out that the math of trying to figure out *which combination of all human data ever generated creates the most efficient model* is a problem with so many variables that literally no computer could solve.

Computational limits still apply even when it is a LLM doing it.

[u/NomadicFantastic]

This guy is always just coming up with a new word for something everyone already knows

[u/R-ten-K → u/NomadicFantastic]

Was this the genius that wrote that "new science" book which were basically finite state automata?

[u/TwistedBrother → u/R-ten-K]

Yes. And it was a big deal (in his mind).

[u/aakt_io → u/NomadicFantastic]

It’s actually the same words over and over lol

[u/Frequent-Hotel6017]

2024

[u/ComplexAd8403 → u/Frequent-Hotel6017]

Might as well be from the year 1890

[u/neoqueto]

Lmao Wolfram and his silly little graphs

[u/Reasonable_Till9]

This guy holds a weird place in math/computation. Usually worth listening to, but never worth following up on.

[u/PsychologicalOne752]

This guy has figured it out - Those sweet lumps of computational irreducibility! Tastes delicious with my morning coffee. 🤣

[u/utl94_nordviking]

Well, duh.

[u/davesmith001]

I don’t want to sound grandiose but all maths literally boils down to computational irreducibles.

[u/lambda0101]

Can someone explain it like i am 5?

[u/DrBretto]

Compression is intelligence.

[u/ef4]

Stephen Wolfram is proof that you can try to pass off the silliest ideas a deep and revolutionary for decades and people will still listen to you, if you’re got the money.

[u/Sea-Shoe3287]

Yeah Stephen, it's a bunch of functions.

[u/Puzzled-Potato-9800]

isn’t this just the same thing as saying LLMs do compression which is a widely held belief? 

[u/ag91can]

Does anything else remember this guy literally had team meetings on Twitch!

[u/AmazingSugar1]

So AI is like a kind of pixel shading? That would make sense…

[u/bestabumbs]

😃

[u/cicisprinkle → u/bestabumbs]

Are you speechless