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Jeff Bezos on AI (1998) [video]

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Re: Jeff Bezos on AI (1998) [video]

#81

Post by rudasn »

59nadir wrote: post #28
Baeocystin wrote: post #20

Earlier quoted context omitted.

Several years back a bunch of us pet-owning friends wound up round-robin gifting the same model SpotBot carpet cleaner to each other, because it was something we all agreed made our lives better. Nothing weird about it at all.

The fact that you had to preface this with you and your friends being pet owners kind of does make it a special case. You being suggested this vacuum cleaner by Amazon after buying it also doesn't do anything for you in this scenario because you bought the same one for your friends, so the recommendation wasn't needed. I think people are losing sight of the original argument which is that Amazon's recommendations can…

Yeah, but everyone is "special case" in retail.

Re: Jeff Bezos on AI (1998) [video]

#82

Post by worksonmine »

vczf wrote: post #48
flatline wrote: post #26

Earlier quoted context omitted.

There is a famous Dijkstra quote, “The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” Do the intrinsic properties of the system really matter at the end of the day if it performs as well as we do at some task? Heck they’ve been doing many things better for decades, but those are the types of tasks we take it for granted that a machine should be able…

I wrote about my definition of intelligence earlier this month: https://tildes.net/~comp/194n/language_is_a_poor_heuristic_f... I have a definition of intelligence. [...] Intelligence is prediction. In the case of intelligent living processes ranging from single celled organisms to complex multicellular life, intelligence arises from the need to predict the future to survive and reproduce. More intelligent organisms…

I don't agree with your definition at all.

2 people want to kill each other. The one taking the first step is the intelligent one because according to your definition he was better at predicting an outcome than his opponent.

The real world is more complex than that and there are multiple options where both survive, or letting your opponent live and killing yourself because his life is more beneficial to humanity and so on.

Any organism can survive, but for most (including us) that implies a selfish outlook but the most intelligent people I know or heard of never even consider their own ego.

Re: Jeff Bezos on AI (1998) [video]

#84

Post by oldandtired »

ben_w wrote: post #66
oldandtired wrote: post #60

Earlier quoted context omitted.

The question to ask is why? The answer is that we have programmed these systems to do what we require. They cannot exceed but they fail becasue of errors that we have placed in these systems. All of the tasks that you have mentioned have been programmed that way. It has taken human ingenuity to work out how to do this programming. The end result is a machine (non-sentient, non-intelligent) that is doing what we requi…

> All of the tasks that you have mentioned have been programmed that way. It has taken human ingenuity to work out how to do this programming. The successful Go AI were programmed to learn ; we still can't program a decent Go AI with rules humans come up with. > The literature is there Do you have a link? Two Minute Papers just had a video about an AI systematic finding ways to confound other AI, but I thought we'd p…

Your example of the Go AI being programmed to learn is not all that accurate for what has been achieved here. I didn't keep the link for the discussion on the confounding of the Go AI system. What the discussion covered though was that there were simple Go configurations that the GO AI failed abysmally on when playing a human - it didn't learn here.

I have spent forty years dealing with all sorts of computer systems - designing, building, maintaining, repairing, redesigning and rebuilding. One thing I have learnt over that time is that none of the systems ever built has been error free in terms of the logic entailed within them. All to often, I have seen systems that were used to make decisions with and those using them assuming that the outputs were correct or reasonable. Yet on investigation, the logic entailed in them was completely rubbish.

We make assumptions and often we do not carefully check that those assumptions are actually real. I don't trust anything I write until I have gone over it with a fine tooth comb and then I will try to document all my assumptions and this usually shows up various logic errors or conditions that I didn't think about. I don't see this happening much out in the real world.

Re: Jeff Bezos on AI (1998) [video]

#85

Post by bondarchuk »

keiferski wrote: post #41
BoiledCabbage wrote: post #14

Earlier quoted context omitted.

> That's what ultimately depresses me about AI. It's still just a parlor trick. We haven't actually taught computers to think, to reason, to be innovative. And what do you feel when we make these parlor tricks more capable than us at the majority of tasks? And what do you feel when we understand it well enough to realize we're the same type of parlor tricks? To me it seems like you're most interested in a magic 'aha'…

And what do you feel when we understand it well enough to realize we’re the same type of parlor tricks? That’s called positivism and it has a lot of philosophical issues. I wouldn’t be so quick to assume that sensory appearance is equivalent to reality. https://en.wikipedia.org/wiki/Positivism

Sensory appearance not being equivalent to reality does not have any relevance to the question of AI and humans ultimately being the same kind of information-processing system. Just handwaving "that's X philosophical position and it has problems" does not strike me as a good argument either unless you manage to explain how these problems pertain to the question at hand.

Re: Jeff Bezos on AI (1998) [video]

#86

Post by keiferski »

bondarchuk wrote: post #85
keiferski wrote: post #41

Earlier quoted context omitted.

And what do you feel when we understand it well enough to realize we’re the same type of parlor tricks? That’s called positivism and it has a lot of philosophical issues. I wouldn’t be so quick to assume that sensory appearance is equivalent to reality. https://en.wikipedia.org/wiki/Positivism

Sensory appearance not being equivalent to reality does not have any relevance to the question of AI and humans ultimately being the same kind of information-processing system. Just handwaving "that's X philosophical position and it has problems" does not strike me as a good argument either unless you manage to explain how these problems pertain to the question at hand.

Unless AI becomes indistinguishable from human beings on a cellular level, yes, it’s entirely relevant and is the single most relevant thing. A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one. It might introduce some problems WRT to determining if an entity is human or not, but this doesn’t somehow prove they humans are just a “parlor trick.”

This is a positivistic argument and as I pointed out, positivism has a lot of issues. The best counter argument IMO being that it’s needlessly reductive. This is all covered pretty clearly in the link.

Re: Jeff Bezos on AI (1998) [video]

#87

Post by bondarchuk »

keiferski wrote: post #86
bondarchuk wrote: post #85

Earlier quoted context omitted.

Sensory appearance not being equivalent to reality does not have any relevance to the question of AI and humans ultimately being the same kind of information-processing system. Just handwaving "that's X philosophical position and it has problems" does not strike me as a good argument either unless you manage to explain how these problems pertain to the question at hand.

Unless AI becomes indistinguishable from human beings on a cellular level, yes, it’s entirely relevant and is the single most relevant thing. A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one. It might introduce some problems WRT to determining if an entity is human or not, but this doesn’t somehow prove they humans are just a “parlor trick.” T…

>A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one.

That is not what BoiledCabbage was saying. He was saying: "And what do you feel when we understand it well enough to realize we're the same type of parlor tricks?"

>This is a positivistic argument and as I pointed out, positivism has a lot of issues. The best counter argument IMO being that it’s needlessly reductive. This is all covered pretty clearly in the link.

You're not really making any specific claim about what is wrong with BoiledCabbage's speculation, and why this specific thing is wrong. "That's wrong because positivism, it's all in this 5k word wikipedia article!" just doesn't prove anything.

Re: Jeff Bezos on AI (1998) [video]

#88

Post by imiric »

mholt wrote: post #5

The common sentiment around AI in the 90s and early 2000s was that it didn't work; it had its hype, it had its heyday, but it seemed like a dead-end for the most part. The Perceptron was merely a linear function approximator. And the Multi-layer Perceptron was a little more capable, but the many orders of magnitude it would have to scale up in order to be convincing just wasn't feasible back then (it finally was in t…

The reason ML took off in the 2010s is because hardware finally became powerful enough to brute force classical solutions. If anything, this lends credence to the idea that these are more than just "parlor tricks", but that with sufficient hardware we can approximate the value of intelligence. We've certainly experienced the leaps in just the last few years when more hardware is thrown at the problem. Imagine what can be accomplished in the next decade or two based on this growth alone.

We don't necessarily have to replicate the way the human brain works, but as long as the machine is capable of performing quasi-cognitive tasks, there will be immense value (and disruption) to society.

Re: Jeff Bezos on AI (1998) [video]

#89

Post by IanCal »

worksonmine wrote: post #79
IanCal wrote: post #67

Earlier quoted context omitted.

> A process of analysing or pattern matching the input question with the data stored retrieves an answer. They're not just retrieving stored text like pulling the most relevant passage from a database. If they were they'd not be able to deal with things outside the training set. They couldn't write code for a custom library that was created after the cutoff (they can with a description), and they couldn't write about…

I don't see why not. It's not taking a single answer from a database no, it's taking several based on probability and merging them into what it thinks we're looking for. If you learn to multiply with code to perform one task, you can then apply that knowledge for a completely different task. It may look like solving a completely new problem but the LLM doesn't even see the difference. When you use the term "custom li…

> . It's still just looking up function to do x, function to do y and applying it to the output.

I mean no, no it isn't.

I'm giving it info on how to construct data models with a custom library, so interacting with that is not using anything previously stored, and then giving it businesses/tasks to model as simple human descriptions.

If you tell me that something which

* Takes a human description of a problem

* Describes back to me the overall structure and components required to solve it with a hierarchy

* Converts that into code, correctly identifying where it makes sense for an address to be contained within a model or distinct and referenced

* Correctly reuses previously created classes that are obviously not in its original dataset

has no understanding or reasoning and it just regurgitating things it's seen before simply mashed together, I don't know what to say.

Frankly

> it's taking several based on probability and merging them into what it thinks we're looking for. I

Sounds pretty much like understanding and reasoning to me.

> but there's no need to exaggerate it as magic.

I'm absolutely not saying there's magic. Humans aren't magic and they can do reasoning. I'm saying it's not just looking up text and regurgitating it.

I think this is supported by things like othello-gpt, which builds an internal world model and outputs based on that.

Re: Jeff Bezos on AI (1998) [video]

#90

Post by keiferski »

bondarchuk wrote: post #87
keiferski wrote: post #86

Earlier quoted context omitted.

Unless AI becomes indistinguishable from human beings on a cellular level, yes, it’s entirely relevant and is the single most relevant thing. A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one. It might introduce some problems WRT to determining if an entity is human or not, but this doesn’t somehow prove they humans are just a “parlor trick.” T…

> A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one. That is not what BoiledCabbage was saying. He was saying: " And what do you feel when we understand it well enough to realize we're the same type of parlor tricks? " > This is a positivistic argument and as I pointed out, positivism has a lot of issues. The best counter argument IMO being tha…

If you haven’t done the reading, I can’t explain it to you in a HN comment. I’m not trying to be snarky about it, but I genuinely don’t know what else to tell you. This is a pretty foundational ideal in the philosophy of science.

What’s wrong with the speculation is that it’s a positivistic argument that is needlessly reductive. It’s reductive because it assumes that appearing human-like is equivalent to being human.

The fact that we can understand how “AI” works as a parlor trick yet appears human-like in no way implies that human beings are nothing more than the same parlor trick processes. To argue that it does is to make a positivistic argument that doesn't take in account a whole host of other things. As noted in the Criticism section of the article (which is hardly 5,000 words) there are many issues with this approach.

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