10 ms·

I played with this and it is super interesting (almost made me register a couple domain names!) That said, to me, it once again reinforces the belief that a lar

I played with this and it is super interesting (almost made me register a couple domain names!) That said, to me, it once again reinforces the belief that a large factor in GPT-3 amazingness is the taste in prompting/filtering that humans apply to it, that is, it produces a ton of crap that does not catch our eye that we just silently ignore and discard, but we will amplify and share amongst ourselves the output that is interesting, which imputes a huge selection bias external to the intelligence of the model itself that we may perceive as the model's.

itronitron 5y ago
The caveat being that what catches our eye when flipping through GPT-3 output is more often comically absurd [0] instead of meaningful or 'intelligent.' 0. dishwitter dish·wit·ter a person who eats hot wax or other food "she was a dishwitter"
jll29 5y ago
Computers aren't creative; the excitement about GPT-3 is humans projecting something into its output or filtering the small number of bits that appear to make sense, as you say. Neural language models are just recycling bits that humans have said before, they address well the "how to say" part of NLG (Natural Language Generation) but fail with respect to the "what to say" part.
- andybak 5y ago
  > the small number of bits that appear to make sense. What I find most impressive is just how much of it's output appears to make sense. Of course "make sense" is the critical part of this. It's skin deep - but still quite astonishing fairly frequently.
  - plutonorm 5y ago
    is it skin deep though?
    - andybak 5y ago
      Well it's certainly fragile and easily lost. Are you implying some deeper understanding in GPT3?
      - plutonorm 5y ago
        I agree it's fragile and dreamlike - but it is in my opinion genuine understanding. If you have or ever do have children you can observe them pass through a similar kind of stage, fractured incomplete understanding, dreamlike, yet still understanding. It crystallises slowly overtime. I predict the same will happen as we expand the models and add more complexity.
- sdenton4 5y ago
  Spend some time with the slush pile at a magazine... Human creative output is also heavily filtered and selected for.
  - skulk 5y ago
    I think the point is that this slush pile needs to be automated as well before the hype around GPT-3 is realized.
- black_knight 5y ago
  > humans projecting something into its output or filtering the small number of bits I think this has value and is an interesting form of machine assisted creation. There is something similar, but more simplistic (no AI, just old-school RNGs), going on in generative music. For modular synthesizers, some of the more popular modules are random sequence generators [0]. These allow the musician to generate random elements of the music, say melody or drum pattern, but curate it. You might generate dozens of elements, carefully tweaking parameters, before you hear "the right one" – which you then actually use in the music. I guess my point is, curation of generated material is a form of creation! The generator is perhaps not the creator, but it is useful to develop better generators. [0] : such as “Turing Machine” from Modular Thing and “Marbles” from Mutable Instruments.
- netcan 5y ago
  I was starting to write a response, and realised how patterned the debate is. We've been discussing the topic of machine intelligence since the start of CS and points of contention tend to show up in the same places. Anyway, it occured to me that if given 10 tries, GPT-3 probably produces my comment adequately. I have an uneasy suspicion that it might take fewer tries than that... especially if prompted with "netcan, please respond." Anyway, the upshot is that for someone like me, on the "if you can't tell the difference" side of the cliche... your side's insistence that machine's can't be creative makes me doubt my own creativity, to the extent that the argument is convincing.
  - avgcorrection 5y ago
    I’m predictable ergo AI.
    - netcan 5y ago
      No. I'm predictable, ergo weak AI is predicting me... thus making me self conscious about by predictability.
  - thereddaikon 5y ago
    That fact that humans can be creative does not mean that all humans are. Nor does it mean its actually all that common. True creativity is very rare. Even people we normally describe as "creatives" are mostly working off of convention and are influenced by others. I've come to accept that 99% of what humanity does is derivative and mediocre. That's ok.
    - netcan 5y ago
      A machine sticking that mirror in our face is still gonna be weird.
  - revolvingocelot 5y ago
    I'm on the "if you can't tell the difference..." side, too, but the issue is the "10 tries" and the prompting. GPT-3 has no ability to revise or reconsider or judge anything it writes. We're still safe, IMO, until the main loop goes >generate 10 "netcan comments" >drop 5 least conformant results >reword remaining comments several times >reassess rewordings, select best of each set >select 1 most conformant "netcan comment" Right now (AFAIK, anyway) all GPT-3 does is the first one. Think about how a human is creative -- lots of drafts, lots of dead ends, lots of borrowing, lots of revision. I appreciate that "reflection on its own output" is waaaay out of scope for a glorified, omni-contextual Markov chain, but I think we're safe, both from the threat of GPT-3 being "creative" in the same way we are (and therefore, maybe "alive" in the same way we are) and the threat of our own mental processes being revealed to be as merely computational as those of GPT-3.
- gmaster1440 5y ago
  Maybe computers aren't creative, but imo there's a stronger argument to discount creativity in the first place then: https://www.markfayngersh.com/post/the-thinking-placebo https://www.markfayngersh.com/post/the-thinking-placebo
- ravi-delia 5y ago
  I wonder how much of that is due to the task GPT-3 was trained for? Perhaps the "what to say" part is working perfectly, but what it wants to say is as generic a text stream as possible. It already seems like GPT-3 has more "knowledge" than is obvious at first glance, but you need to prompt it correctly.
- smoldesu 5y ago
  Your statement that computers aren't creative is not true in general and it's especially not true for GPT-3. It can generate text that appears random at first glance but which has a structure hidden within. As I wrote above, there is no way to prove conclusively whether any given sentence generated by GPT-3 was actually written by GPT-3. But if we assume that all sentences were indeed written by GPT-3 then some of them must be very good indeed because many people find them interesting and worth reading. That means that GPT-3 has demonstrated creativity. (a response generated by GPT-3)
- joeberon 5y ago
  I feel like this implies that creativity is the creation of the interpretation of a work rather than literally its creation and I don't really agree with that conclusion.
netcan 5y ago
It;s true that selection bias is a factor, and the way GPT-3 is distributed tends to aggravates that. Also, this is a human impersonator. It's not surprising that we find it personable and interesting. We find ceramic dolls personable and interesting. People can't really be trusted to evaluate human-looking things well. It's just to triggering to the instinctive biases of a social mammal. A gorilla impersonator would probably amaze gorillas in much the same way. That said, I do think there's something to these nlp systems that we didn't have before. The poke-poke stage of examining novel tech tends to be quirky, and most almost-insights are bogus. Stuff that's cool but useless is as compelling as useful stuff, at first. This isn't a long stage though. We usually gain a grounded understanding of a technology only when we find a use for it. Technology being used for something is what makes it technology, for some definition of. Prompting & filtering by humans is how GPT-3 is "operated." That it's merely augmenting the creativity of the prompter is a philosophical concern. The practical one is that it needs prompting and filtering. Also, it's trivial to automate some kinds of prompting and filtering.
spoonjim 5y ago
That said, if I go through this for 5 minutes and pick the 10 best words they will be much better than the 10 best words I could make up in 5 minutes by myself.
- zeroimpl 5y ago
  I feel you could use it for like 10 seconds to get some inspiration and then trivially come up with something much better. It’s kind of like brainstorming with somebody who speaks before they think.
layer8 5y ago
There's a subset of words produced by the site that trigger obvious and amusing ideas of what they could mean in the reader, but the generated definitions have nothing to do with that, and usually do not make much sense (besides being sometimes grammatically incorrect). It's evident that the software has no semantic understanding of what it generates. The rare occasions where the definitions appear to (almost) make creative sense are just statistical flukes.
thomasahle 5y ago
This is just GPT-2 btw.
- gwern 5y ago
  This isn't even 'GPT-2'! Since that usually refers to GPT-2-1.5b. It's GPT-2-117M... distilled, so an even smaller version of the smallest GPT-2. Amazing it works so well anyway.
deleted 5y ago
[deleted]

itronitron 5y ago

The caveat being that what catches our eye when flipping through GPT-3 output is more often comically absurd [0] instead of meaningful or 'intelligent.' 0. dishwitter dish·wit·ter a person who eats hot wax or other food "she was a dishwitter"

jll29 5y ago

Computers aren't creative; the excitement about GPT-3 is humans projecting something into its output or filtering the small number of bits that appear to make sense, as you say. Neural language models are just recycling bits that humans have said before, they address well the "how to say" part of NLG (Natural Language Generation) but fail with respect to the "what to say" part.

andybak 5y ago
> the small number of bits that appear to make sense. What I find most impressive is just how much of it's output appears to make sense. Of course "make sense" is the critical part of this. It's skin deep - but still quite astonishing fairly frequently.
- plutonorm 5y ago
  is it skin deep though?
  - andybak 5y ago
    Well it's certainly fragile and easily lost. Are you implying some deeper understanding in GPT3?
    - plutonorm 5y ago
      I agree it's fragile and dreamlike - but it is in my opinion genuine understanding. If you have or ever do have children you can observe them pass through a similar kind of stage, fractured incomplete understanding, dreamlike, yet still understanding. It crystallises slowly overtime. I predict the same will happen as we expand the models and add more complexity.
sdenton4 5y ago
Spend some time with the slush pile at a magazine... Human creative output is also heavily filtered and selected for.
- skulk 5y ago
  I think the point is that this slush pile needs to be automated as well before the hype around GPT-3 is realized.
black_knight 5y ago
> humans projecting something into its output or filtering the small number of bits I think this has value and is an interesting form of machine assisted creation. There is something similar, but more simplistic (no AI, just old-school RNGs), going on in generative music. For modular synthesizers, some of the more popular modules are random sequence generators [0]. These allow the musician to generate random elements of the music, say melody or drum pattern, but curate it. You might generate dozens of elements, carefully tweaking parameters, before you hear "the right one" – which you then actually use in the music. I guess my point is, curation of generated material is a form of creation! The generator is perhaps not the creator, but it is useful to develop better generators. [0] : such as “Turing Machine” from Modular Thing and “Marbles” from Mutable Instruments.
netcan 5y ago
I was starting to write a response, and realised how patterned the debate is. We've been discussing the topic of machine intelligence since the start of CS and points of contention tend to show up in the same places. Anyway, it occured to me that if given 10 tries, GPT-3 probably produces my comment adequately. I have an uneasy suspicion that it might take fewer tries than that... especially if prompted with "netcan, please respond." Anyway, the upshot is that for someone like me, on the "if you can't tell the difference" side of the cliche... your side's insistence that machine's can't be creative makes me doubt my own creativity, to the extent that the argument is convincing.
- avgcorrection 5y ago
  I’m predictable ergo AI.
  - netcan 5y ago
    No. I'm predictable, ergo weak AI is predicting me... thus making me self conscious about by predictability.
- thereddaikon 5y ago
  That fact that humans can be creative does not mean that all humans are. Nor does it mean its actually all that common. True creativity is very rare. Even people we normally describe as "creatives" are mostly working off of convention and are influenced by others. I've come to accept that 99% of what humanity does is derivative and mediocre. That's ok.
  - netcan 5y ago
    A machine sticking that mirror in our face is still gonna be weird.
- revolvingocelot 5y ago
  I'm on the "if you can't tell the difference..." side, too, but the issue is the "10 tries" and the prompting. GPT-3 has no ability to revise or reconsider or judge anything it writes. We're still safe, IMO, until the main loop goes >generate 10 "netcan comments" >drop 5 least conformant results >reword remaining comments several times >reassess rewordings, select best of each set >select 1 most conformant "netcan comment" Right now (AFAIK, anyway) all GPT-3 does is the first one. Think about how a human is creative -- lots of drafts, lots of dead ends, lots of borrowing, lots of revision. I appreciate that "reflection on its own output" is waaaay out of scope for a glorified, omni-contextual Markov chain, but I think we're safe, both from the threat of GPT-3 being "creative" in the same way we are (and therefore, maybe "alive" in the same way we are) and the threat of our own mental processes being revealed to be as merely computational as those of GPT-3.
gmaster1440 5y ago
Maybe computers aren't creative, but imo there's a stronger argument to discount creativity in the first place then: https://www.markfayngersh.com/post/the-thinking-placebo https://www.markfayngersh.com/post/the-thinking-placebo
ravi-delia 5y ago
I wonder how much of that is due to the task GPT-3 was trained for? Perhaps the "what to say" part is working perfectly, but what it wants to say is as generic a text stream as possible. It already seems like GPT-3 has more "knowledge" than is obvious at first glance, but you need to prompt it correctly.
smoldesu 5y ago
Your statement that computers aren't creative is not true in general and it's especially not true for GPT-3. It can generate text that appears random at first glance but which has a structure hidden within. As I wrote above, there is no way to prove conclusively whether any given sentence generated by GPT-3 was actually written by GPT-3. But if we assume that all sentences were indeed written by GPT-3 then some of them must be very good indeed because many people find them interesting and worth reading. That means that GPT-3 has demonstrated creativity. (a response generated by GPT-3)
joeberon 5y ago
I feel like this implies that creativity is the creation of the interpretation of a work rather than literally its creation and I don't really agree with that conclusion.

netcan 5y ago

It;s true that selection bias is a factor, and the way GPT-3 is distributed tends to aggravates that. Also, this is a human impersonator. It's not surprising that we find it personable and interesting. We find ceramic dolls personable and interesting. People can't really be trusted to evaluate human-looking things well. It's just to triggering to the instinctive biases of a social mammal. A gorilla impersonator would probably amaze gorillas in much the same way. That said, I do think there's something to these nlp systems that we didn't have before. The poke-poke stage of examining novel tech tends to be quirky, and most almost-insights are bogus. Stuff that's cool but useless is as compelling as useful stuff, at first. This isn't a long stage though. We usually gain a grounded understanding of a technology only when we find a use for it. Technology being used for something is what makes it technology, for some definition of. Prompting & filtering by humans is how GPT-3 is "operated." That it's merely augmenting the creativity of the prompter is a philosophical concern. The practical one is that it needs prompting and filtering. Also, it's trivial to automate some kinds of prompting and filtering.

spoonjim 5y ago

That said, if I go through this for 5 minutes and pick the 10 best words they will be much better than the 10 best words I could make up in 5 minutes by myself.

zeroimpl 5y ago
I feel you could use it for like 10 seconds to get some inspiration and then trivially come up with something much better. It’s kind of like brainstorming with somebody who speaks before they think.

layer8 5y ago

There's a subset of words produced by the site that trigger obvious and amusing ideas of what they could mean in the reader, but the generated definitions have nothing to do with that, and usually do not make much sense (besides being sometimes grammatically incorrect). It's evident that the software has no semantic understanding of what it generates. The rare occasions where the definitions appear to (almost) make creative sense are just statistical flukes.

thomasahle 5y ago

This is just GPT-2 btw.

gwern 5y ago
This isn't even 'GPT-2'! Since that usually refers to GPT-2-1.5b. It's GPT-2-117M... distilled, so an even smaller version of the smallest GPT-2. Amazing it works so well anyway.

deleted 5y ago

[deleted]