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Jeff Bezos on AI (1998) [video]

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

#41
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…

> 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

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

#42

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 make these parlor tricks more capable than us at the majority of tasks? This seems like the logical fallacy of "begging the question" since it is far from apparent to me that they are "more capable than us at the majority of tasks."

AI systems are vastly better than humans at a wide variety of tasks. Better at handwriting recognition, better at scheduling, better at playing games, better at speech recognition and transcription, etc.

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

#43

Article has no body for me. Site appears to use an iframe whose src expects the Referer header to be sent, but I have `network.http.referer.XOriginPolicy = 1`set in FF about:config to reduce cross-origin leakage, so no Referer is sent.

Great point. It is using cloudflare stream.

https://developers.cloudflare.com/stream/viewing-videos/usin...

Open to any recomendations for alternative as i too am quite displeased with the state of such things. But still prefer it to YouTube.

I believe the media server is set to reqire referer to prevent embeding on alternative origins.

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

#44

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

That statement also has no basis in neuroscience.

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

#45

Earlier quoted context omitted.

I hate this sentiment. We might learn that human thought and reasoning are parlor tricks too once we understand them better. Anything we start to understand loses its mystery

"Any sufficiently advanced technology is indistinguishable from magic." I know nothing about AI but it seems like we're approaching it from the other end - the human mind seems like magic and when we approximate it using technology it feels like we'll reach a moment of "that's all it is?" and refuse to believe we actually did it because we doubt ourselves. Along the same lines, if achieving equal human rights for all…

It would certainly be neat if we approximated the mind using technology. It's a real shame we haven't done that. And no, computer programs don't have or deserve to have rights.

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

#46
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…

AI is not a parlor trick. AI is a branch of statistics. Nobody said that statistics must limit itself to quasi-linear models of numerical data. It was just a limitation of computational resources (initially "AI" was developed by human computers). The trick is to get people not to associate the dictum "lies, damn lies and statistics" with "hallucinations, damn hallucinations and AI".

statistics are based.

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

#47

Earlier quoted context omitted.

This is why they've called it AI winter the past three times. It's a season. Like the seasons, the cycle repeats.

What a tired and lame take. 100m people used this latest iteration. It’s hardly a winter.

The crash is gonna be wild when people realize all these companies are blowing smoke. We did get Google out of the last crash though I guess.

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

#48
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…

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 build more elaborate models of the world using better developed senses in order to do so.
    
    Humans model the world primarily with language, which allows us to share our models with each other, across both space and time! Without language, it is extraordinarily more difficult to communicate complex abstract thoughts. As a side effect of our high level of intelligence, our wetware is capable of modeling things outside of language, such as mathematics. [...]
    
    In general, I think we need to stop equating intelligence with consciousness, agency, moral value, and living things. These are entirely different concepts, and, as a species, we are blinded by our egotistical identity of being smarter than the other animals.
According to my definition, intelligence is actually all around us. We are blind to it because we focus only on how intelligence manifests in humans (defined by by our specific social organization and biological senses), and then use that as a benchmark to judge every other thing in the world.

A less socially-charged definition of intelligence would make it easier to compare intelligence across living and non-living processes, though it would not be "popular science" useful for ranking humans.

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

#49

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 make these parlor tricks more capable than us at the majority of tasks? This seems like the logical fallacy of "begging the question" since it is far from apparent to me that they are "more capable than us at the majority of tasks."

It's certainly difficult to enumerate all the things we humans actually do.

There's a lot of stuff we consider to be "common sense", sometimes those things are used to criticise AI and sometimes they're used to criticise other humans for not knowing them, but that is a category that we don't even think about until we notice the absence.

For the things not considered common sense, like playing chess (beats all humans) or speaking/reading foreign languages (more than I can name to a higher standard than my second language), to creating art (even if it regularly makes the common sense mistake of getting the number of fingers and limbs wrong it's still better and not just faster than most humans), to arithmetic (a Raspberry Pi Zero can do it faster than all humans combined), to symbolic maths, to flying planes…

A dev conference I was at recently had someone demonstrate how they hooked up their whatsapp voice calls to speech recognition, speech synthesis trained on their own voice, and an LLM, and the criticism of the people who got the AI replies was not "you're using an AI" (he had to actively demonstrate his use of AI to conversation partners who didn't believe him) but "you can't have listed to my message, you replied too quickly to have even played it all back."

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

#50
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 parlor tricks are getting better. In terms of practicality you just need to look at AI art. That stuff is good enough to replace the real thing.

In terms of actual sentience, understanding

I had chatGPT answer questions in the following order:

   1. Describe to me what happens when you throw sugar in coffee
   2. Describe the same thing in terms of atoms. 
   3. Is this an example of entropy decreasing? 
   4. What if the arrow of time was reversed. Describe what happens again at the atomic level. 
   5. What if there were two regions in space one with increasing entropy and another with decreasing entropy. I place the coffee cup such that one half is in one region the other half is in the other region. What happens?
Each answer displayed astonishing understanding of what occurs. This was the final answer to the fifth question:

   -----------------------------------------------

   The scenario you've proposed is purely hypothetical and quite speculative because it defies our current understanding of the laws of physics, particularly the Second Law of Thermodynamics, which stipulates that entropy in an isolated system tends to increase. Nevertheless, it's a fascinating thought experiment. Here's what might happen if you had a cup of coffee straddling two such regions:
   
   The Increasing Entropy Region:

    Dissolution and Distribution: On this side, sugar would behave as it does in our observable universe. It would dissolve in the coffee and disperse randomly throughout the half of the liquid.

    Mixing and Thermal Energy: Molecules in this region would continue to collide and interact based on thermal motion, contributing to faster dissolution and dispersion of sugar.

    Sweetening: The coffee in this half would become sweet as the sugar molecules interact with the liquid and dissolve.

   The Decreasing Entropy Region:

    Reforming Crystals: On this side, dissolved sugar would spontaneously start forming sugar crystals, leading to a decreasing level of entropy.

    Unmixing: The sugar would start to separate from the coffee and move to form a distinct layer or solid chunks, further decreasing entropy in that half.

    Unsweetening: Any sweetness initially imparted to this side would disappear as sugar molecules revert to a more ordered state.

   Challenges:

    Interface: The most mysterious part would be at the interface where the two regions meet. Would a sugar molecule crossing from the increasing to the decreasing entropy region suddenly reverse its course? Would there be some form of "entropy gradient" or "entropy tension" at the boundary? This part is extremely speculative and likely paradoxical.

    Energy Conservation: Energy conservation laws might become complicated here. The energy required for sugar to crystallize in the decreasing entropy zone would have to come from somewhere, and how this balances with the increasing entropy side would pose a significant scientific puzzle.

    Thermodynamic Anomalies: The coffee cup itself would be under very peculiar thermodynamic conditions, subject to two entirely different sets of rules. The temperature might behave inconsistently across the boundary, and heat exchange would likely be disrupted in perplexing ways.

    Taste Experience: If you were to taste the coffee, each half of the cup would offer a radically different experience, one sweet and the other likely reverting back to its original unsweet state.

    Perceptual Paradox: From a human perception standpoint, witnessing sugar both dissolve and crystallize in the same cup of coffee would be a profound and likely disorienting experience.

    Time's Arrow: This set-up implicitly questions the nature of time itself. Time seems to behave differently on each side, challenging our deepest notions about causality, sequence, and even reality.

   Again, it's worth noting that this scenario conflicts with our current understanding of physics, but it's a fascinating avenue for speculative thought. Such a universe, if it could exist, would fundamentally challenge our understanding of physical laws and reality as we know it.

   -------------------------------------------------

This answer here is anything but a magic trick. It shows deep understanding of conceptual reality by answering complex questions that are unlikely to exist anywhere else on the internet. The AI literally talked about the mysterious interface without me prompting it at all. It knows the conceptual consequence of two regions of space side by side with differing levels of entropy. The answer is not simply a trick of the next best language token.

Is it a practical answer? No. Because the question itself isn't practical. But a non-practical answer does not make this answer a parlor trick.

The entire internet is dismissing this thing as a parlor trick because LLMs fail to add large numbers. I mean come on man. You don't need to be able to do math like a calculator in order to "understand" things.

AI is not yet completely practical. That much is true. However, it is clearly No longer a parlor trick and it is getting closer and closer to transitioning into practical. When that day comes.... Good luck to us all.

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