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The BS-Industrial Complex of Phony A.I.

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Re: The BS-Industrial Complex of Phony A.I.

#221

Post by pron »

In 1949, some years after the invention of neural networks, Norbert Weiner, one of the leading minds of the time, was convinced that AI (AGI as you may call it) or a full understanding of the brain is no more than five years away. Alan Turing thought Weiner was delusional, and that it may take as much as fifty years. Seventy years later, we are nowhere near insect-level intelligence.

I don't see any fundamental barrier preventing us from achieving AI, but if someone from the future came to me and said that AI will be achieved in 2130, I would find that quite reasonable. If they said it will be achieved in 2030 or 2230, I would find those equally reasonable. Our current scientific understanding is that we have no idea how far we are from AI, we don't know what the challenges are, and we don't even know what intelligence is. We certainly have no idea whether the approach we are now taking (statistical clustering, AKA deep learning) is a path that leads to AI or not.

In the sixties, the leading minds of that time were also working hard on the problem and did not find it any further away from us as we do today. That some people are optimistic is irrelevant. The fact is that we just have no idea.

Re: The BS-Industrial Complex of Phony A.I.

#222

Post by marvin »

lsc wrote: post #149
misterman0 wrote: post #133

Earlier quoted context omitted.

I don't think it's necessary for us to get a machine to reach "consciousness", whatever that is, before we realise it's overtaken our mental ability to combine two existing concepts in order to create a new one. I imagine this is what's going to happen: we humans have drawn two circles (thank you dear fella for that analogy) and we are about to draw a third, combing two existing concepts. At some point we will have d…

>Tens of thousands of people comprehend Einstein's work. It used to be hundreds. We're smart as shit these days. In some ways, I feel like this is the real singularity. This trend towards feeding and offering education to everyone. Like, it used to be that to be an intellectual, you'd need to be born rich to get the free time and education. I mean, being born rich still helps, sure, but a lot more people are getting…

If you subscribe to the theory of great and continuing, accelerating change due to technological improvements, advanced technological education for everyone is an expected ovservation during the decades or centuries it’s occurring :)

Re: The BS-Industrial Complex of Phony A.I.

#223

Post by skybrian »

sjy wrote: post #187
bjourne wrote: post #153

Earlier quoted context omitted.

The first "AI winter" happened in the 60's. In 1949 Warren Weaver published a memorandum outlining his plan for universal machine translation. He likened the problem to cryptography, a field that had exploded due to WWII, and thought it would be solved in a few years. In hindsight, we know that his ideas were very naive but Weaver was an influential and charismatic person so they inspired lots researchers. They also…

It feels harsh to call him naïve because I'm sure I wouldn't have had any more insight, but it is surprising how little we knew about the science of language pre-Chomsky, considering that we have been learning languages for millions of years. Now that we have had several generations of computer technology fall short of the abilities of human translators, it seems obvious that you're probably not going to be able to w…

Did you mean post-Chomsky? It's my understanding that machine translation started to become semi-useful after abandoning traditional grammars (or anything Chomsky would recognize) and switched to statistics.

Re: The BS-Industrial Complex of Phony A.I.

#224

Post by dijksterhuis »

Quetelet wrote: post #90
dijksterhuis wrote: post #80

Earlier quoted context omitted.

The only nnets I mentioned were “classical” as a purposefully over simplified example. Yeah, they can model any function, but historically they were used for probabilistic density functions (if I remember correctly). Most of what the article talked about can be done with much simpler models, which is what I get peeved about. Also, yes, you can transfer learn with resnet. But if I throw my bank statements at it, it’ll…

You might be confusing the historical use of the sigmoid activation function with probabilistic modeling, neural networks in the 80s were used similarly to how they are today, albeit at a much smaller scale due to hardware limitations at the time. The development of neural networks is a major contribution of the machine learning community, so even if you’d like to split hairs about whether the “computer is learning”…

Ok, it seems like there are some crossed wires or missing context here. Also, widely off topic.

I never said anything about the term machine learning. Check my bio, see what I’m working on. Fully aware of neural network contributions.

I’m all for machine learning. Just not “AI”. “AI” is hype bullshit.

“Learning” when used by the people who spout this BS is not the technical definition version, and is what I was referring to.

Could probably have made that clearer, but I’m 1.5 days without sleep.

What does feeding test data into a network yield? Inference results. Inference seems vaguely familiar from probabilistic modelling?

Bayes rule applies to neural nets too. Two different models may give vastly different results. Whilst they can be very good approximators, they can also be very unreliable if care is not taken during training.

G(x) ~ f(w.f(w.x+b)+b) is literally a fancy weighted sum. A linear regression. It is some easy stats combined together with a few other things that aren’t explicitly necessary, eg activation function can be identity to cancel out f().

EDIT Both the parameters of a network and the training data are variables in the application of Bayes rule. Which inherently deals with likelihoods (probability). /EDIT

So at their fundamental, they are “just some stats” stuff. They may have a few more bells and whistles to make them complex (and better) systems, but they still output a classification/regression based on inference.

You can, of course, approximate many functions with them. I’ve built a network with only weights of +1/-1, for example.

But those examples have extremely specific use cases that are not applicable to anything the article discusses.

Re: The BS-Industrial Complex of Phony A.I.

#225

Post by skybrian »

patrick5415 wrote: post #106
tintor wrote: post #72

Earlier quoted context omitted.

AGI is not needed for self-driving. None of what is mentioned above is a deal-breaker for self-driving car service: - lidar at night works just fine - plenty of cities with no or very little snow - construction zones: blacklisting, remote monitoring & manual mapping, detection of cones, barriers, re-painted lanes - self-driving cars with 360 degree view and plenty of patience and no distraction are safer for bicyclis…

>- lidar at night works just fine at night Yes, let’s rely on a single sensor. > - plenty of cities with no or very little snow But plenty of city have plenty of snow. So perhaps not a deal breaker in a limited set of circumstances. > - construction zones: blacklisting, remote monitoring & manual mapping, detection of cones, barriers, re-painted lanes Why should we add to already high construction costs just because…

Why shouldn't surrounding infrastructure adapt a bit for self-driving cars? Look at everything that had to change for railroads, cars, and airplanes.

If railroads were invented today they would never be allowed. They can't stop for miles? You have to teach everyone everywhere to stay off the tracks? How's that supposed to work?

It's good that our safety standards are a lot higher today for new tech, but perhaps there are a few common sense rules that could be taught, rather than requiring perfection?

Re: The BS-Industrial Complex of Phony A.I.

#226

Post by tim333 »

Causality1 wrote: post #53
solidasparagus wrote: post #12

The author seems confused about what artificial general intelligence is. People have not meaningfully moved towards AGI - it's still a distant pipe dream. The closest we've gotten is probably a Dota bot that's pretty good as long as you give the bot a huge advantage. Which is an incredible piece of technology, but about as close to AGI as an ant is to a human.

Not even an ant. If AGI is a human then what we have is the equivalent of synthetic RNA molecules.

For RNA molecules they are doing quite well at trashing us at go, chess, dota and starcraft.

Re: The BS-Industrial Complex of Phony A.I.

#227

Post by dijksterhuis »

raverbashing wrote: post #192
waynecochran wrote: post #9

Getting ready for the next AI winter.... this is a cyclic phenomena.

Hopefully we don't take decades again for a simple but important change like changing tanh to relu activations.

my bet is on capsule networks, Hinton is usually on point with his stuff

Re: The BS-Industrial Complex of Phony A.I.

#228

Post by plaidfuji »

Sure, “AI” as it is used today implies “software that codifies decision-making using data”. No, it’s not the T3000. But as the author acknowledges:

> Dynamic Yield can pay for itself many times over by helping McDonald’s better understand its customers

Ok, so it’s not hype - it is delivering real value. “AI” is just a marketing term to help C-suite suits and Silicon Valley sales reps get on the same page about what’s being sold with as few words as possible. What’s being sold is software that helps make optimal decision using data.

AI isn’t a rigorously defined academic term, so people will use it how they want. It’s only hype when real value isn’t delivered.

Re: The BS-Industrial Complex of Phony A.I.

#229

Post by [deleted] »

w0utert wrote: post #89
Quekid5 wrote: post #45

Earlier quoted context omitted.

I suppose it's a subset of "well defined rules", but it's worth calling out explicitly, I think: Chess also has an objective (and trivially verifiable) win condition. There are few interesting situations in real life where such a thing exists.

In that regard, AlphaGo is a lot more impressive, not just because it is a vastly more complex problem to find a loss function for playing Go (compared to chess), but also because AlphaGo basically learned to play the game by itself without even having a model of the game rules initially (or so I've heard). That said, I would still not consider it anything like generalized AI, if only because the set of possible (val…

[deleted]

Re: The BS-Industrial Complex of Phony A.I.

#230

Post by epr »

plaidfuji wrote: post #228

Sure, “AI” as it is used today implies “software that codifies decision-making using data”. No, it’s not the T3000. But as the author acknowledges: > Dynamic Yield can pay for itself many times over by helping McDonald’s better understand its customers Ok, so it’s not hype - it is delivering real value. “AI” is just a marketing term to help C-suite suits and Silicon Valley sales reps get on the same page about what’s…

> What’s being sold is software that helps make optimal decision using data

Doesn't this apply to virtually all software?

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