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I think perhaps what's more upsetting is that GPT-3 flips the traditional notions of what machines are good at and what humans are good at on their respective h

I think perhaps what's more upsetting is that GPT-3 flips the traditional notions of what machines are good at and what humans are good at on their respective heads. GPT-3 seems to indicate there's a chance that "creative" domains such as poetry, literature, music, etc. will be taken over by AI (i.e. AIs will have superhuman performance) before "logical" domains such as logic, mathematics, and the sciences. This means that it is becoming more and more conceivable to more and more people that sometime in the foreseeable future an AI will be better than any human along any dimension you choose to measure, even when it comes to the ability to elicit emotions and reactions in other humans.

theontheone 6y ago
I think you hit the nail on the head, with the salient point here being that in the near future "creative" things will be automated first (see Image GPT, Jukebox, etc. Google has 100 billion dollars cash and countless TPUs, best engineers, infra, etc - they could probably replicate results far better than each of these OpenAI projects within a few years). One of the things that got me into ML research was the notion that we could automate a lot of the hard work humans do every day (agriculture, cooking, desk jobs, etc) so that humans could do things that were uniquely theirs & interesting, that were human, that were beautiful... Unfortunately it turns out that classical music and waxing poetic are easily generative in an enjoyable way. In the most ironic fashion possible, it turns out that the very thing we do when we conduct ML research, what you call the "logical domain", is one of the only things that stays human-only in the foreseeable future. GPT-3 and other projects seem to drive hype cycles in the tech community and convince people like Elon Musk that the AGI revolution is near. But I think recent progress is just another example of machine learning models being able to generalize on super large datasets, even if it's the biggest model so far. It's not clear to me that larger models will solve this in the limit; take the way GPT3 fails on addition past a certain number, and the fundamental inability for transformers to learn certain algorithms. It is certainly still possible for this type of large dataset, large model style of ML to make human life better in many ways - like Tesla is trying to do with self driving cars, or Covariant with automating Amazon-like jobs. But I think when it comes to tackling the hard problems of true intelligence, we're missing a dimension somewhere.
- qppo 6y ago
  This is going to sound very dismissive and condescending: "meh." Generative music has been around for half a century, or longer depending on how you want to interpret things. Mimicry as a mechanism for composition has been around for as long as humans have made music. It is wholly uninteresting to discover that we can design generative systems for music that excel at mimicry, because we've already perfected that mechanism in analog. The interesting bit is that the genesis of new musical ideas is driven by manual interaction and direction of the generative system, and at that point it's the guiding hand of the engineer turned artist that we can respect and appreciate, not the mimicry of a machine.
  - visarga 6y ago
    > Generative music has been around for half a century, If you start by referring to results from 50 years ago, have you tried listening to state of the art generative music systems lately? They can probably compose music better than 99% of humans.
    - chrisco255 6y ago
      Have you been moved by any of that music though? Am I missing something?
      - TomMarius 6y ago
        Yeah, it's very moving to see a human-made machine do such wonders. Fills me with awe, appreciation, and hope.
        dahfizz 6y ago
        That's exactly it, though. This stuff is interesting because of the novelty of AI. The works themselves are not independently relevant (not yet, at least).
        6y ago
simonh 6y ago
How about politics? Load all the political punditry, polling data, blogs, transcripts of Fox News and CNBC and build the perfect Presidential tweet bot, speech writer and campaign adviser. Of course what you'd end up with is a presidency that only cared about electoral chances, and would have no understanding whatsoever of the actual impact of policies or how to manage issues and crises to achieve actual goals.
- braymundo 6y ago
  Nothing new there, then.
YeGoblynQueenne 6y ago
AI systems have been known to be able to elicit emotions and reactions in humans, even very strong such emotions and reactions, since the early days of the field. A classic example is Joseph Weizenbaum's ELIZA, which gives its name to the "Eliza effect", i.e. the tendency to anthropomorphise AI programs [1], even very simple ones, with a small range of pre-scripted behaviours, like ELIZA. For a longer example involving a robot specifically designed to mimick emotions by manipulating actuators to change its "facial" expressions, see Rodnay Brooks' third part of his tripartite essay on "Steps towards super-intelligence", specifically the chapter titled "7. Bond With Humans" [2] (there's no direct link to the chapter but you xcan search for it in the article). I quote from Rodney Brooks' article: In the 1990’s my PhD student Cynthia Breazeal used to ask whether we would want the then future robots in our homes to be “an appliance or a friend”. So far they have been appliances. For Cynthia’s PhD thesis (defended in the year 2000) she built a robot, Kismet, an embodied head, that could interact with people. She tested it with lab members who were familiar with robots and with dozens of volunteers who had no previous experience with robots, and certainly not a social robot like Kismet. I have put two videos (cameras were much lower resolution back then) from her PhD defense online. In the first one Cynthia asked six members of our lab group to variously praise the robot, get its attention, prohibit the robot, and soothe the robot. As you can see, the robot has simple facial expressions, and head motions. Cynthia had mapped out an emotional space for the robot and had it express its emotion state with these parameters controlling how it moved its head, its ears and its eyelids. A largely independent system controlled the direction of its eyes, designed to look like human eyes, with cameras behind each retina–its gaze direction is both emotional and functional in that gaze direction determines what it can see. It also looked for people’s eyes and made eye contact when appropriate, while generally picking up on motions in its field of view, and sometimes attending to those motions, based on a model of how humans seem to do so at the preconscious level. In the video Kismet easily picks up on the somewhat exaggerated prosody in the humans’ voices, and responds appropriately. In the second video, a naïve subject, i.e., one who had no previous knowledge of the robot, was asked to “talk to the robot”. He did not know that the robot did not understand English, but instead only detected when he was speaking along with detecting the prosody in his voice (and in fact it was much better tuned to prosody in women’s voices–you may have noticed that all the human participants in the previous video were women). Also he did not know that Kismet only uttered nonsense words made up of English language phonemes but not actual English words. Nevertheless he is able to have a somewhat coherent conversation with the robot. They take turns in speaking (as with all subjects he adjusts his delay to match the timing that Kismet needed so they would not speak over each other), and he successfully shows it his watch, in that it looks right at his watch when he says “I want to show you my watch”. It does this because instinctively he moves his hand to the center of its visual field and makes a motion towards the watch, tapping the face with his index finger. Kismet knows nothing about watches but does know to follow simple motions. Kismet also makes eye contact with him, follows his face, and when it loses his face, the subject re-engages it with a hand motion. And when he gets close to Kismet’s face and Kismet pulls back he says “Am I too close?”. The article includes links to the videos. _____________ [1] https://en.wikipedia.org/wiki/ELIZA_effect https://en.wikipedia.org/wiki/ELIZA_effect [2] https://rodneybrooks.com/forai-steps-toward-super-intelligence-iii-hard-things-today/ https://rodneybrooks.com/forai-steps-toward-super-intelligen...
PaulHoule 6y ago
Here is the scary bit. This 1957 novel https://www.commentarymagazine.com/articles/wallace-markfield/remember-me-to-god-by-myron-s-kaufmann/ https://www.commentarymagazine.com/articles/wallace-markfiel... points out that low-status jobs are jobs where you can be held accountable for doing something wrong (e.g. bank teller who gives out two $20 bills instead of one $20 bill) and high-status jobs where you can can't. (Back in the the 1980s looting a bank as CEO could get you in jail, today the DOJ seems to think a judge and jury couldn't understand how a bank gets looted.) If current patterns continued, GPT-3 would get the "Brahmin" jobs and real people would get the "Dalit" jobs. GPT-3 can do the job of Bill Lumbergh, probably better than Lumbergh himself, but if it tried to pass as anybody who gets real work done, it wouldn't.
nemoniac 6y ago
There's a quote attributed to Donald Knuth that goes "Science is what we understand well enough to explain to a computer. Art is everything else we do." Now if you take the word "explain" broadly and maintain that we've actually found a way to "explain" a huge volume of information to GPT-3 then you might hold that Knuth had got it backwards. But maybe that's the crux of it. GPT-3 doesn't get explained anything. You might better say it was force fed.

theontheone 6y ago

I think you hit the nail on the head, with the salient point here being that in the near future "creative" things will be automated first (see Image GPT, Jukebox, etc. Google has 100 billion dollars cash and countless TPUs, best engineers, infra, etc - they could probably replicate results far better than each of these OpenAI projects within a few years). One of the things that got me into ML research was the notion that we could automate a lot of the hard work humans do every day (agriculture, cooking, desk jobs, etc) so that humans could do things that were uniquely theirs & interesting, that were human, that were beautiful... Unfortunately it turns out that classical music and waxing poetic are easily generative in an enjoyable way. In the most ironic fashion possible, it turns out that the very thing we do when we conduct ML research, what you call the "logical domain", is one of the only things that stays human-only in the foreseeable future. GPT-3 and other projects seem to drive hype cycles in the tech community and convince people like Elon Musk that the AGI revolution is near. But I think recent progress is just another example of machine learning models being able to generalize on super large datasets, even if it's the biggest model so far. It's not clear to me that larger models will solve this in the limit; take the way GPT3 fails on addition past a certain number, and the fundamental inability for transformers to learn certain algorithms. It is certainly still possible for this type of large dataset, large model style of ML to make human life better in many ways - like Tesla is trying to do with self driving cars, or Covariant with automating Amazon-like jobs. But I think when it comes to tackling the hard problems of true intelligence, we're missing a dimension somewhere.

qppo 6y ago
This is going to sound very dismissive and condescending: "meh." Generative music has been around for half a century, or longer depending on how you want to interpret things. Mimicry as a mechanism for composition has been around for as long as humans have made music. It is wholly uninteresting to discover that we can design generative systems for music that excel at mimicry, because we've already perfected that mechanism in analog. The interesting bit is that the genesis of new musical ideas is driven by manual interaction and direction of the generative system, and at that point it's the guiding hand of the engineer turned artist that we can respect and appreciate, not the mimicry of a machine.
- visarga 6y ago
  > Generative music has been around for half a century, If you start by referring to results from 50 years ago, have you tried listening to state of the art generative music systems lately? They can probably compose music better than 99% of humans.
  - chrisco255 6y ago
    Have you been moved by any of that music though? Am I missing something?
    - TomMarius 6y ago
      Yeah, it's very moving to see a human-made machine do such wonders. Fills me with awe, appreciation, and hope.
      - dahfizz 6y ago
        That's exactly it, though. This stuff is interesting because of the novelty of AI. The works themselves are not independently relevant (not yet, at least).
        6y ago

simonh 6y ago

How about politics? Load all the political punditry, polling data, blogs, transcripts of Fox News and CNBC and build the perfect Presidential tweet bot, speech writer and campaign adviser. Of course what you'd end up with is a presidency that only cared about electoral chances, and would have no understanding whatsoever of the actual impact of policies or how to manage issues and crises to achieve actual goals.

braymundo 6y ago
Nothing new there, then.

YeGoblynQueenne 6y ago

AI systems have been known to be able to elicit emotions and reactions in humans, even very strong such emotions and reactions, since the early days of the field. A classic example is Joseph Weizenbaum's ELIZA, which gives its name to the "Eliza effect", i.e. the tendency to anthropomorphise AI programs [1], even very simple ones, with a small range of pre-scripted behaviours, like ELIZA. For a longer example involving a robot specifically designed to mimick emotions by manipulating actuators to change its "facial" expressions, see Rodnay Brooks' third part of his tripartite essay on "Steps towards super-intelligence", specifically the chapter titled "7. Bond With Humans" [2] (there's no direct link to the chapter but you xcan search for it in the article). I quote from Rodney Brooks' article: In the 1990’s my PhD student Cynthia Breazeal used to ask whether we would want the then future robots in our homes to be “an appliance or a friend”. So far they have been appliances. For Cynthia’s PhD thesis (defended in the year 2000) she built a robot, Kismet, an embodied head, that could interact with people. She tested it with lab members who were familiar with robots and with dozens of volunteers who had no previous experience with robots, and certainly not a social robot like Kismet. I have put two videos (cameras were much lower resolution back then) from her PhD defense online. In the first one Cynthia asked six members of our lab group to variously praise the robot, get its attention, prohibit the robot, and soothe the robot. As you can see, the robot has simple facial expressions, and head motions. Cynthia had mapped out an emotional space for the robot and had it express its emotion state with these parameters controlling how it moved its head, its ears and its eyelids. A largely independent system controlled the direction of its eyes, designed to look like human eyes, with cameras behind each retina–its gaze direction is both emotional and functional in that gaze direction determines what it can see. It also looked for people’s eyes and made eye contact when appropriate, while generally picking up on motions in its field of view, and sometimes attending to those motions, based on a model of how humans seem to do so at the preconscious level. In the video Kismet easily picks up on the somewhat exaggerated prosody in the humans’ voices, and responds appropriately. In the second video, a naïve subject, i.e., one who had no previous knowledge of the robot, was asked to “talk to the robot”. He did not know that the robot did not understand English, but instead only detected when he was speaking along with detecting the prosody in his voice (and in fact it was much better tuned to prosody in women’s voices–you may have noticed that all the human participants in the previous video were women). Also he did not know that Kismet only uttered nonsense words made up of English language phonemes but not actual English words. Nevertheless he is able to have a somewhat coherent conversation with the robot. They take turns in speaking (as with all subjects he adjusts his delay to match the timing that Kismet needed so they would not speak over each other), and he successfully shows it his watch, in that it looks right at his watch when he says “I want to show you my watch”. It does this because instinctively he moves his hand to the center of its visual field and makes a motion towards the watch, tapping the face with his index finger. Kismet knows nothing about watches but does know to follow simple motions. Kismet also makes eye contact with him, follows his face, and when it loses his face, the subject re-engages it with a hand motion. And when he gets close to Kismet’s face and Kismet pulls back he says “Am I too close?”. The article includes links to the videos. _____________ [1] https://en.wikipedia.org/wiki/ELIZA_effect https://en.wikipedia.org/wiki/ELIZA_effect [2] https://rodneybrooks.com/forai-steps-toward-super-intelligence-iii-hard-things-today/ https://rodneybrooks.com/forai-steps-toward-super-intelligen...

PaulHoule 6y ago

Here is the scary bit. This 1957 novel https://www.commentarymagazine.com/articles/wallace-markfield/remember-me-to-god-by-myron-s-kaufmann/ https://www.commentarymagazine.com/articles/wallace-markfiel... points out that low-status jobs are jobs where you can be held accountable for doing something wrong (e.g. bank teller who gives out two $20 bills instead of one $20 bill) and high-status jobs where you can can't. (Back in the the 1980s looting a bank as CEO could get you in jail, today the DOJ seems to think a judge and jury couldn't understand how a bank gets looted.) If current patterns continued, GPT-3 would get the "Brahmin" jobs and real people would get the "Dalit" jobs. GPT-3 can do the job of Bill Lumbergh, probably better than Lumbergh himself, but if it tried to pass as anybody who gets real work done, it wouldn't.

nemoniac 6y ago

There's a quote attributed to Donald Knuth that goes "Science is what we understand well enough to explain to a computer. Art is everything else we do." Now if you take the word "explain" broadly and maintain that we've actually found a way to "explain" a huge volume of information to GPT-3 then you might hold that Knuth had got it backwards. But maybe that's the crux of it. GPT-3 doesn't get explained anything. You might better say it was force fed.