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Google DeepMind CEO says some form of AGI possible in a few years

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Re: Google DeepMind CEO says some form of AGI possible in a few years

#261

Post by dr_dshiv »

AnimalMuppet wrote: post #253
dr_dshiv wrote: post #199

Earlier quoted context omitted.

It’s terrible and math and logic, but ChatGPT is amazing at concepts—that’s why it is so powerful. It doesn’t work programmatically—that’s why it fails at logic. But it can reason inductively very very well. Do you have an example besides logic/math where it doesn’t understand simple concepts?

No, it's amazing at words . Humans use words to encode concepts, but ChatGPT doesn't get the concepts at all - just words and their relationships. To the extent that humans have encoded the concepts into words, and that text is in the training set, to that degree ChatGPT can work with the words in a way that is at least somewhat true to the concepts encoded in them. But it doesn't actually understand any of the conce…

This is the debate, isn’t it? I think if we create tests for understanding and deliver them to people, we will find variations in what people understand. I think we will find the same for chatGPT.

But I suspect your notion of understanding is not measurable, is it? For you, chatGPT lacks something essential such that it is incapable of understanding, no matter the test. Or do you have a way to measure this without appeal to consciousness or essentialism?

Re: Google DeepMind CEO says some form of AGI possible in a few years

#262

Post by jebarker »

23B1 wrote: post #152
ml-anon wrote: post #144

Earlier quoted context omitted.

Calling them "hallucinations" is a shoddy piece of terminology by the community which anthropomorphises them.

What would you recommend calling them? Genuinely curious.

According to Geoff Hinton the correct term from human psychology is "confabulations".

Hallucinations are a mistake in perception.

Re: Google DeepMind CEO says some form of AGI possible in a few years

#263

Post by bondarchuk »

Lerc wrote: post #258
bondarchuk wrote: post #241

Earlier quoted context omitted.

> The notion "This can't be all thought is" is as old as the idea of AI. Older still: > It must be confessed, moreover, that perception, and that which depends on it, are inexplicable by mechanical causes, that is, by figures and motions, And, supposing that there were a mechanism so constructed as to think, feel and have perception, we might enter it as into a mill. And this granted, we should only find on visiting…

I would argue that that quote contains the idea of AI

Fair enough.

Re: Google DeepMind CEO says some form of AGI possible in a few years

#264

Post by [deleted] »

VHRanger wrote: post #255
ogogmad wrote: post #247

Earlier quoted context omitted.

That would suggest that 1-Hidden-Layer neural nets would work fine, since they are also universal function approximators. But no -- when people talk about "deep learning", the word "deep" refers to having lots of hidden layers. I'm not an expert, but the motivation seems more like this: - Linear regression and SVM sometimes work. But they apply to very few problems. - We can fit those models using gradient descent. A…

RE: 1-layer neural nets, yes, that's the point. Deep learning has been a series of *engineering* successes stacking over each other rather than theory being applied rigorously. It's hard to scale training on the "dumb" approximators like a kitchen sink regression, and balancing overfitting becomes a nightmare.

[deleted]

Re: Google DeepMind CEO says some form of AGI possible in a few years

#265

Post by liampulles »

If I'm trying to solve a generic problem, I try to break it down into pieces which I have familiarity with and barring that I will look to google to fill the gaps. I might try think of alternative approaches and compare them, and reflect on individual steps to try and improve them. I'll review my work and test it as I go to ensure it is actually solving the problem.

Given some of the capabilities I have seen with chain-of-thought processing, embeddings, and vector databases - it does seem to me conceivable that computers could be made to do all of this. One gap maybe is being able to pick up that the problem statement is wrong, i.e. not solving the right problem, or being aware of subtle undocumented details about the system and the business that need to be factored in. The AI needs to actually know about these subtle details somehow in order to factor them in.

Perhaps that is the big problem that remains - capturing subtle details about the world.

Re: Google DeepMind CEO says some form of AGI possible in a few years

#266

Post by _acco »

PheonixPharts wrote: post #41

As someone who has worked in the field of AI/ML for quite awhile now, the problem with current AGI predictions is ML hasn't done anything new since the 80s (or arguably earlier). At the end of the day all ML is using gradient descent to do some sort of non-linear projection of the data on to a latent space, then doing some relatively simple math in this latent space to perform some task. Personally I think the limits…

Yes, that’s right.

AGI ≠ a lot of AI. They are fundamentally different things.

The first computer was designed in 1837, long before a computer was ever built. We know how fusion reactions work, now we’re tweaking the engineering to harness it in a reactor.

We don’t know how human intelligence works. We don’t have designs or even a philosophy for AGI. Yet, the prevailing view is that our greatest invention will just suddenly “emerge.”

No other field I’m aware of so strongly purports it will reach its ultimate breakthrough without having a clue of the fundamentals of that breakthrough.

It’s like nuclear scientists saying “if we just do a lot of fission, we think fusion will just happen.”

Re: Google DeepMind CEO says some form of AGI possible in a few years

#267

Post by chimprich »

dr_dshiv wrote: post #249
chimprich wrote: post #238

Earlier quoted context omitted.

> Do you have an example besides logic/math where it doesn’t understand simple concepts? All the time. It often fails to understand simple concepts. It doesn't really seem to understand anything. For example, try to get it to write some code for a program in a moderately obscure programming language. It's terrible: it will confidently produce stuff, but make errors all over the place. It's unable to understand that i…

Sure, so what are the specific concepts it doesn’t understand? I don’t think its ability to program in an obscure program is really a great test. That’s a matter of syntax more than semantics, no? Novel conceptual blends are where it excels. Yes, it needs to understand the concepts involved to blend them —but humans need that too.

I think you missed my point. It's understandable that it doesn't know how to program in a moderately obscure language. But the model doesn't understand that it doesn't. The specific concepts it doesn't understand are understanding what it is, its limitations, and what it's being asked to do.

It doesn't seem to have any "meta" understanding. It's subconscious thought only.

If I asked a human to program in a language they didn't understand, they'd say they couldn't, or they'd ask for further instructions, or some reference to the documentation, or they'd suggest asking someone else to do it, or they'd eventually figure out how to write in the language by experimenting on small programs and gradually writing more complex ones.

GPT4 and friends "just" take an input that seems like it could plausibly answer the request. If it gets it wrong then it just has another go using the same generative technique as before with whatever extra direction the human decides to give it. It doesn't think about the problem.

("just" doing a lot of work in the above sentence: what it does is seriously impressive! But it still seems to be well behind humans in capability.)

Re: Google DeepMind CEO says some form of AGI possible in a few years

#268

Post by AnimalMuppet »

dr_dshiv wrote: post #261
AnimalMuppet wrote: post #253

Earlier quoted context omitted.

No, it's amazing at words . Humans use words to encode concepts, but ChatGPT doesn't get the concepts at all - just words and their relationships. To the extent that humans have encoded the concepts into words, and that text is in the training set, to that degree ChatGPT can work with the words in a way that is at least somewhat true to the concepts encoded in them. But it doesn't actually understand any of the conce…

This is the debate, isn’t it? I think if we create tests for understanding and deliver them to people, we will find variations in what people understand. I think we will find the same for chatGPT. But I suspect your notion of understanding is not measurable, is it? For you, chatGPT lacks something essential such that it is incapable of understanding, no matter the test. Or do you have a way to measure this without ap…

Well, consciousness is part of the question, isn't it? We know that we are conscious (even if we can't precisely define what that means). Is ChatGPT conscious? I'm pretty sure the answer is no, but how do you prove it?

Does understanding require consciousness? Maybe yes, for the kind of understanding I'm thinking of, but I'm not certain of that.

How do you measure understanding? You step a bit outside the training set, and see if whoever (or whatever) being tested can apply what it has learned in that somewhat novel situation. That's hard when ChatGPT has been trained on the entire internet. But to the degree we can test it, ChatGPT often falls down horribly. (It even falls down on things that should be within its training set.) So we conclude that it doesn't actually understand.

Re: Google DeepMind CEO says some form of AGI possible in a few years

#269

Post by RugnirViking »

andrepd wrote: post #210
dr_dshiv wrote: post #199

Earlier quoted context omitted.

It’s terrible and math and logic, but ChatGPT is amazing at concepts—that’s why it is so powerful. It doesn’t work programmatically—that’s why it fails at logic. But it can reason inductively very very well. Do you have an example besides logic/math where it doesn’t understand simple concepts?

What do you mean exactly "besides math/logic"? Because logic underpins everything we think. For example it cannot identify musical chords because despite (I presume) ample training material including explanations of how exactly this works, it cannot reasonable represent this as an abstract rigorous rule, as humans do. So I ask what is C E G and it tells me C major correctly, as it presumably appears many times throug…

i dunno man, I asked it about that chord and it told me it was an F diminished 7th chord. I asked it what a d flat major chord was and it told me. I then asked it what the relationship between the two was. It didnt catch it immediately but when I told it to think about inversions it got it. That's decent for a music student.

It even told me about the role of each in a chord progression and how even though they share the same notes they resolve differently

Humans clearly don't think logically anyhow. Thats why we need things like abacus to help us concretely store things, in our head everything is relative in importance to other things in the moment

Re: Google DeepMind CEO says some form of AGI possible in a few years

#270

Post by circuit10 »

HKH2 wrote: post #229
circuit10 wrote: post #112

Earlier quoted context omitted.

Why is instinct not computable? That seems way easier to compute than rational thinking based on principles, it's just "if this, do that" and machine learning should be able to do that easily

If you could isolate processes like that, sure.

With machine learning the processes are learnt so there’s not much manual programming other than the training and inference code
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