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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

#211

Post by pilsetnieks »

vidarh wrote: post #201
riffraff wrote: post #166

Earlier quoted context omitted.

I think this is the culprit: ChatGPT does not understand , as proven by hallucinations, by being wrong on certain questions or puzzle etc.. It just seems to understand. This is useful, and deeply impressive, but it's not the same thing.

Humans are confidently wrong about all kinds of things all the time. We don't call it hallucination other than for very specific, limited subsets. We call each other names over it, call it mistakes, stupidity, or lies. In fact, we structure large parts of society around it (the presence of multiple contradictory world religions means the majority of the worlds population goes through life being confidently wrong). It…

You seem to propose a "if it quacks like a duck" scenario here (aka the Chinese Room), and applying it to people who are mistaken or acting on incorrect information.

Those people are reasoning, however rightly or wrongly, based on that wrong information. LLMs are not.

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

#212

Post by jokoon »

I tried to classify images using tensorflow and inception using a pre trained model, it was awfully slow. I asked almost everywhere for a faster and less accurate model, no answer.

I'm starting to suspect that GPU vendors are the ones selling AI.

If you think about it, software is often used by the hardware industry to increase sales, it's the law of Wirth. Seems like it's the norm now.

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

#213

Post by CrampusDestrus »

blast wrote: post #100
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…

"We dont have better algorithms, we just have more data" - Peter Norvig

"We don't have better brains than our ancestors, we just have more data"

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

#214

Post by TheSpiceIsLife »

rullelito wrote: post #150
ml-anon wrote: post #144

Earlier quoted context omitted.

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

We're building human-like intelligence, so this seems quite apt?

Are we?

I'd settle for a poor fascimillie, and argue strongly against human-like.

Human-like would be, let's say, a Cylon skin-job. ChatGPT is just a fraking toaster, at best.

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

#215

Post by vidarh »

kranke155 wrote: post #207
vidarh wrote: post #175

Earlier quoted context omitted.

Humans "hallucinate" in the AI sense (it's an awful word that obscures how often we do it) all the time too. You'll find people confidently make claims not supported by data or indeed by any of their own data all the time, where when you poke around in their justifications you'll find they have none. The key difference appears a combination of two factors: We appear to be more likely to have learnt which subjects we'…

Humans have a way to verify reality. Their senses + scientific method Saying “most humans make dumb statements” is not a defense to build a machine that makes dumb statements imo

Nobody is suggesting we shouldn't improve on it. The point is that the jump to a significant improvement is not necessarily very big once you add reinforcement of the limits of the models knowledge, be that through conversations or senses (they're both just data).

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

#216

Post by vidarh »

pilsetnieks wrote: post #211
vidarh wrote: post #201

Earlier quoted context omitted.

Humans are confidently wrong about all kinds of things all the time. We don't call it hallucination other than for very specific, limited subsets. We call each other names over it, call it mistakes, stupidity, or lies. In fact, we structure large parts of society around it (the presence of multiple contradictory world religions means the majority of the worlds population goes through life being confidently wrong). It…

You seem to propose a "if it quacks like a duck" scenario here (aka the Chinese Room), and applying it to people who are mistaken or acting on incorrect information. Those people are reasoning , however rightly or wrongly, based on that wrong information. LLMs are not.

We do not have sufficient knowledge of what reasoning entails to be able to tell whether there's any meaningful distinction between human reasoning and LLMs. It's likely there is some difference. It's not clear whether there's any major qualitative difference.

Claiming we can tell that there's a distinction that merits saying people are reasoning and LLMs are not, is "hallucination" to me. It's making a claim there is insufficient evidence to make a reasoned statement about.

EDIT: Ironically, on feeding ChatGPT (w/GPT4) my comment and your reply and asking it to "compose a reply on behalf of 'vidarh'" it produced a reply that was far more willing to accept your claim that there is a fundamental difference (while otherwise giving a reasonable reaffirmation of my argument that reinforcement of the boundaries of its knowledge would reduce its "hallucinations")

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

#217

Post by somewhereoutth »

meindnoch wrote: post #170
somewhereoutth wrote: post #164

Earlier quoted context omitted.

You don't need non-linearities, an infinite series of sine functions is enough to model any function. For extraordinary claims ('intelligence'), the burden of proof is on those making the claim, not on others to prove the negative.

>You don't need non-linearities, an infinite series of sine functions is enough The sine function is nonlinear.

Ah so it is! I guess my point was that even this simple function is enough, you don't need any 'magic' beyond that. In particular, this continuous function can be used (infinitely) to represent discontinuous functions - the step function being the usual example. That is the more interesting and relevant mathematical fact I think.

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

#218

Post by dr_dshiv »

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…

Sure. Let’s take quantum theory. There are lots of concepts that are based in math but can be reasoned about non-mathematically.

The reason that chatGPT can write quantum computer programs to in any domain (despite the lack of existing programs!) is because it can deal with the concepts of quantum computing and the concepts in a domain (eg, predicting housing prices) and align them.

Very little of human reasoning is based on logic and math.

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

#220

Post by otabdeveloper4 »

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…

You miss the point.

Just make humans dumber and more predictable. Problem solved. (This isn't that hard since humans will adapt to the stupidity level of the "AI" they use daily on their own without special social engineering efforts.)

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