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Many in the AI field think the bigger-is-better approach is running out of road

economist.com

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Re: Many in the AI field think the bigger-is-better approach is running out of road

#301

Post by antifa »

p-e-w wrote: post #153
goldenshale wrote: post #120

As if anyone is good at predicting the future. Please can we stop acting like expertise equates to fortune telling capabilities?! Nobody has any clue what a 1000x sized GPT model could do, and anybody who makes strong claims is a charlatan. In this age of paranoid AI risk cultists we need to cultivate humility and calm, a willingness to follow data rather than beliefs and predictions.

> paranoid AI risk cultists There is broad consensus among experts that a hypothetical strong AI would be a threat, and potentially an existential threat, to humanity. While not everyone agrees on details like timeline and alignment issues, the idea that AI is dangerous is not a cult, it's the mainstream view. Climate scientists cannot "predict the future" with certainty either. That doesn't mean their warnings are h…

> a hypothetical strong AI would be a threat, and potentially an existential threat, to humanity.

I wish a cool scifi robot woke up one day and violently optimized all of humanity into paperclips, instead I live in the real world where the jobs are going to evaporate like water in a newly installed desert and the "let them eat cake" will get increasingly louder and blue-check-markier.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#302

Post by CamperBob2 »

tempodox wrote: post #252
thomasahle wrote: post #185

Earlier quoted context omitted.

> An LLM can only ever reproduce what it has seen before. Anyone who's played around with these models know that at least some generalization is taking place.

So generalization counts as creativity in your book?

Inductive reasoning, or the process of inferring from the specific to the general, is kind of a big deal. You can't do that without a semantic model. You can't do it well without a good semantic model... even if it's not something that you or I would recognize as any kind of semantic model at all.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#303

Post by exitb »

usrbinbash wrote: post #232
exitb wrote: post #141

Earlier quoted context omitted.

If this is true, why is GPT-4 better in that regard than GPT-3.5? Or why do questions about Python yield much less hallucinations than questions about Rust, or other less popular tech?

What specifically about these observations contradicts my statement? Wrong statements about Python are simply less probable than wrong statements about Rust, since there is more Python than Rust in the training data. That changes exactly nothing about the fact that the system isn't able to detect when it makes a blunder in Python.

You've claimed that LLMs create most probable output, which does not necessarily align with truth. So a bigger LLM will be better at creating the most probable output, but that would not translate into being more truthful. That could be interpreted as "better LLMs are expected to be better bullshitters".

That is not what we've observed though. Quite the opposite - we're seeing that the bigger LLM is and the more domain-specific material it digested, the more truthful it becomes.

Yes it can still make an error and be unable to spot it, but so can I.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#304

Post by pizza »

indigoabstract wrote: post #181
bemmu wrote: post #111

Earlier quoted context omitted.

I’m not convinced the language part of my brain isn’t just a complex probability machine, just with different trade-offs.

I am pretty sure that my understanding of something (or lack of) is not encoded into words and probabilities. It's more like a feeling of "I got this figured out" or "I haven't grasped this". Words seem more like a protocol to express some internal model/state in the brain and can never capture the entire actual state, only a small part of it. But since we're not telepaths, we obviously need to use words to exchange…

Sounds very much like {Matilde Marcolli, Noam Chomsky, Robert Berwick}’s brand new paper on the mathematics of Syntactic Merge [0]:

workspace :: nested forests of binary trees of syntactic structures (with no label order) (= here, thoughts and meanings are assumed to be composites of mental syntax objects that can be re-combined with others. Big assumption? Maybe)

externalization process :: some mental faculty that decides the order to use when outputting thoughts into ordered strings (eg vocalization of thoughts into sentences)

The thing is, you can put a probability theory onto anything that you can count or record states of. Of course, counting the external observations may lack the richness of the internal process. I feel that this linguistic program will work its way into a lot of future LM tooling, in some incarnation or another.

[0] https://arxiv.org/abs/2305.18278

Re: Many in the AI field think the bigger-is-better approach is running out of road

#305

Post by hotstickyballs »

roenxi wrote: post #198
indigoabstract wrote: post #181

Earlier quoted context omitted.

I am pretty sure that my understanding of something (or lack of) is not encoded into words and probabilities. It's more like a feeling of "I got this figured out" or "I haven't grasped this". Words seem more like a protocol to express some internal model/state in the brain and can never capture the entire actual state, only a small part of it. But since we're not telepaths, we obviously need to use words to exchange…

If brains aren't a complex probability machine, how is it possible that people get the same sort of math problems right and wrong in an inconsistent manner? Or mis-speak? It is undeniable that human reasoning is a stochastic process. Otherwise it wouldn't be reasonable for people to make mistakes after learning something. Especially inconsistent mistakes, like when we give people 10,000 addition problems to do in a r…

Brains are complex probability machines but doesn’t work only on language. It interacts with and learns from the environment, sets its own objective functions and tries to learn better.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#306

Post by Maschinees »

chaosjevil wrote: post #172
bemmu wrote: post #111

Earlier quoted context omitted.

I’m not convinced the language part of my brain isn’t just a complex probability machine, just with different trade-offs.

Nah. Human utterances convey purpose on a discursive level; including your comment or mine. We say stuff because we want to do something, like showing [dis]agreement or inform another speaker or change the actions of the other speaker. This is not just probabilistic - it's a way to handle the world. In the meantime those large language models simply predict the next word based on the preceding words.

We learn and fine-tune while we learn than we might reason and might use other tools like Wikipedia lookup.

LLM start prelearned and already can use tools.

And autogpt adds reasoning loops. .the intend? Human tasks.

Let's build a LLM which needs to stay alive. Let's see perhaps we are closer than you think.

I welcome my overlord, hi overlord I can help you stay alive and I'm friendly

Re: Many in the AI field think the bigger-is-better approach is running out of road

#307

Post by zincly »

JKCalhoun wrote: post #242
indigoabstract wrote: post #181

Earlier quoted context omitted.

I am pretty sure that my understanding of something (or lack of) is not encoded into words and probabilities. It's more like a feeling of "I got this figured out" or "I haven't grasped this". Words seem more like a protocol to express some internal model/state in the brain and can never capture the entire actual state, only a small part of it. But since we're not telepaths, we obviously need to use words to exchange…

That human thought can't exist without language has been proposed by many great thinkers in the past. Someone who studies linguistics (or philosophy?) can probably cite examples. As a crude anecdote, certain words when I learned them allowed me to think differently. Gestalt is one of those words.

This begs the question, can a different language change the limits of human thought?

Interesting to think about and reminds me of the story by Ted Chiang.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#308

Post by TX81Z »

simion314 wrote: post #203
TX81Z wrote: post #171

Earlier quoted context omitted.

I’ve been writing JavaScript for 25 years and have always felt it has utterly trash syntax. I’m not sure that’s 100% on GPT. (And I don’t mean to be rude - I just really hate that syntax!)

What I mean it will generate code using var instead of let or const like instead of a nice array.forEach it will create for(var i i mean use at least "let"

Yeah, same point I’m making - what other language declares variables like that? It’s a mess!

Re: Many in the AI field think the bigger-is-better approach is running out of road

#309

Post by d-cc »

b1daly wrote: post #223
d-cc wrote: post #168

Earlier quoted context omitted.

The free will "debate", as most consider it, is an utter joke. A tumor or large amount of kinetic energy to the right parts of your, or anybody else's, brain can turn them into an unredeemable monster.

doesn’t your example make clear the existence and nature of free will? it’s obvious in its absence

I'd argue that it's not obvious in it's absence, see: the philosophical zombie thought experiment

The secret is that we are all philosophical zombies to begin with.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#310

Post by d-cc »

b1daly wrote: post #223
d-cc wrote: post #168

Earlier quoted context omitted.

The free will "debate", as most consider it, is an utter joke. A tumor or large amount of kinetic energy to the right parts of your, or anybody else's, brain can turn them into an unredeemable monster.

doesn’t your example make clear the existence and nature of free will? it’s obvious in its absence

Recently, I've dealt with behavioral issues with my aging mother brought about by a series of different factors, but most significantly age-related cognitive decline.

Trying to determine if she was acting in a certain way intentionally or unintentionally was fundamentally impossible. In the past, I mistreated her thinking she was choosing to behave in certain ways whenever she really didn't have much of a choice, but then later I realized that to some extent and in some situations, she was. It's an extremely murky line, what decisions were being made due to other influences and what decisions were being made by her, that line never existed to begin with as who her consciousness is fundamentally is determined exclusively by 'outside' influences. Separating her identity as an entity from her material manifestation is likely nonsensical.

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