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> On the other hand, there does seem something funny about GPT-3 presents this shiny surface where you can send it any query and it gives you an answer, but und

> On the other hand, there does seem something funny about GPT-3 presents this shiny surface where you can send it any query and it gives you an answer, but under the hood there are a bunch of freelancers busily checking all the responses and rewriting them to make the computer look smart. The author seems to be stating that there are people live rewriting answers on the fly so that they look better. I don't really see the evidence of that. What openai states is that they have humans performing labeling and data cleaning, which, duh? And then there's a bunch of examples where it gives the wrong answer, and that it's not truly AI, which, also duh...

visarga 5y ago
The author seems to retract the story, or at least its original title in light on new information. > So the above post was misleading. I’d originally titled it, “Open AI gets GPT-3 to work by hiring an army of humans to fix GPT’s bad answers.” I changed it to “Interesting questions involving the mix of humans and computer algorithms in Open AI’s GPT-3 program.” I appreciate all the helpful comments! Stochastic algorithms are hard to understand, especially when they include tuning parameters.
gojomo 5y ago
There seems suggestive evidence, in the pattern of improvement after a few days on specific questions, that some of the worst answers have been human-reviewed & improved "on the fly" – on a scale of days/weeks. If such tweaks show useful generalization – correcting a few answers also helps the network better determine entire classes of experessions that deserve more definitive & correct answers – that's not such a big deal, expecially if this constant-human-guided reinforcement-training is well-disclosed. If instead the corrections work more like a lookup-table 'cheat sheet' of answers to give in preference to the bulk-learned answers, with little generalization, that's a bit more slight-of-hand, like the original (late-1700s) 'Mechanical Turk' chess-playing 'machine' that was actually controlled by a hidden person. If the disclosure of this constant human-guided correction-process is hidden, or downplayed, the impression of trickery, rather than innovation, is larger.
- rowanG077 5y ago
  A lot of human communication is "lookup-tables". The entirety of geography, mathematical axioms and theorems, names of colors, names of people, language, shape of various things. I'd wager even that it's more important for an AI to have good lookup tables then to have good inference if it were to pass for Human.
  - gojomo 5y ago
    Agreed! But, it's important not to confuse what's possible via 'human-in-the-loop' 'active-learning' with what's possible from an algorithm on a fixed training corpus. Sometimes GPT-like models are portrayed as the latter – a highly automated, reproducible process – while this article makes a pretty strong case that the responses from OpenAI's public-facing interface get rapidly improved by a staff of dozens of contractors. It's not surprising that a staff of 40 humans, given a few days time to consider & compose, can prepare human-quality answers to arbitrary questions!
    - cyanydeez 5y ago
      I think, ultimately, what matters is how the labeling and corrective actions falloff over time. But reasonable people will notice that information is streaming In faster than any single person can code
      - ImPostingOnHN 5y ago
        In this example, it seems they fell off immediately, because the responses were only coded in response to questions asked in the way the author pre-published, and did not appear when the same question was asked in a slightly different way, which the GPT-3 authors did not have the opportunity to prepare for well ahead of time
  - dustingetz 5y ago
    Ah so when OpenAI codes fizzbuzz, it's returning human tweaked fizzbuzz from the lookup table? https://twitter.com/sama/status/1503820489927495682 https://twitter.com/sama/status/1503820489927495682
deleted 5y ago
[deleted]
XorNot 5y ago
It's worth generally remembering that the best neural networks on this planet take 20 to 30 years of education to become useful. The benefit of AIs has always been that once we educate one, we can just copy+paste for the next one.
- jsnodlin 5y ago

visarga 5y ago

The author seems to retract the story, or at least its original title in light on new information. > So the above post was misleading. I’d originally titled it, “Open AI gets GPT-3 to work by hiring an army of humans to fix GPT’s bad answers.” I changed it to “Interesting questions involving the mix of humans and computer algorithms in Open AI’s GPT-3 program.” I appreciate all the helpful comments! Stochastic algorithms are hard to understand, especially when they include tuning parameters.

gojomo 5y ago

There seems suggestive evidence, in the pattern of improvement after a few days on specific questions, that some of the worst answers have been human-reviewed & improved "on the fly" – on a scale of days/weeks. If such tweaks show useful generalization – correcting a few answers also helps the network better determine entire classes of experessions that deserve more definitive & correct answers – that's not such a big deal, expecially if this constant-human-guided reinforcement-training is well-disclosed. If instead the corrections work more like a lookup-table 'cheat sheet' of answers to give in preference to the bulk-learned answers, with little generalization, that's a bit more slight-of-hand, like the original (late-1700s) 'Mechanical Turk' chess-playing 'machine' that was actually controlled by a hidden person. If the disclosure of this constant human-guided correction-process is hidden, or downplayed, the impression of trickery, rather than innovation, is larger.

rowanG077 5y ago
A lot of human communication is "lookup-tables". The entirety of geography, mathematical axioms and theorems, names of colors, names of people, language, shape of various things. I'd wager even that it's more important for an AI to have good lookup tables then to have good inference if it were to pass for Human.
- gojomo 5y ago
  Agreed! But, it's important not to confuse what's possible via 'human-in-the-loop' 'active-learning' with what's possible from an algorithm on a fixed training corpus. Sometimes GPT-like models are portrayed as the latter – a highly automated, reproducible process – while this article makes a pretty strong case that the responses from OpenAI's public-facing interface get rapidly improved by a staff of dozens of contractors. It's not surprising that a staff of 40 humans, given a few days time to consider & compose, can prepare human-quality answers to arbitrary questions!
  - cyanydeez 5y ago
    I think, ultimately, what matters is how the labeling and corrective actions falloff over time. But reasonable people will notice that information is streaming In faster than any single person can code
    - ImPostingOnHN 5y ago
      In this example, it seems they fell off immediately, because the responses were only coded in response to questions asked in the way the author pre-published, and did not appear when the same question was asked in a slightly different way, which the GPT-3 authors did not have the opportunity to prepare for well ahead of time
- dustingetz 5y ago
  Ah so when OpenAI codes fizzbuzz, it's returning human tweaked fizzbuzz from the lookup table? https://twitter.com/sama/status/1503820489927495682 https://twitter.com/sama/status/1503820489927495682

deleted 5y ago

[deleted]

XorNot 5y ago

It's worth generally remembering that the best neural networks on this planet take 20 to 30 years of education to become useful. The benefit of AIs has always been that once we educate one, we can just copy+paste for the next one.

jsnodlin 5y ago