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While the slowness of learning of all ML is absolutely something I recognise, what you describe here: > You can reasonably expect from a human that they will l

by ben_w 1y ago

While the slowness of learning of all ML is absolutely something I recognise, what you describe here: > You can reasonably expect from a human that they will learn from their mistake, and be genuinely sorry about it which will motivate them to not repeat the same mistake in the future. Wildly varies depending on the human. Me? I wish I could learn German from a handful of examples. My embarrassment at my mistakes isn't enough to make it click faster, and it's not simply a matter of motivation here: back when I was commuting 80 minutes each way each day, I would fill the commute with German (app) lessons and (double-speed) podcasts. As the Germans themselves will sometimes say: Deutsche Sprache, schwere Sprache. There's been a few programmers I've worked with who were absolutely certain they knew better than me, when they provably didn't. One, they insisted a start-up process in a mobile app couldn't be improved, I turned it from a 20 minute task to a 200ms task by the next day's standup, but they never at any point showed any interest in improving or learning. (Other problems they demonstrated included not knowing or caring how to use automated reference counting, why copy-pasting class files instead of subclassing cannot be excused by the presence of "private" that could just have been replaced with "public", and casually saying that he had been fired from his previous job and blaming this on personalities without any awareness that even if true he was still displaying personality conflicts with everyone around him). Another, complaining about too many views on screen, wouldn't even let me speak, threatened to end the call when I tried to say anything, even though I had already demonstrated before the call that even several thousand (20k?) widgets on-screen at the same time would still run at 60fps and they were complaining about order-of 100 widgets.

danaris 1y ago
> Wildly varies depending on the human. Sure. And the situation. But the difference is, all humans are capable of it, whether or not they have the tools to exercise that capability in any given situation. No LLM is capable of it*. * Where "it" is "recognizing they made a mistake in real time and learning from it on their own", as distinct from "having their human handlers recognize they made 20k mistakes after the fact and running a new training cycle to try to reduce that number (while also introducing fun new kinds of mistakes)".
- ben_w 1y ago
  > But the difference is, all humans are capable of it, whether or not they have the tools to exercise that capability in any given situation. When they don't have the tools to exercise that capability, it's a distinction without any practical impact. > Where "it" is "recognizing they made a mistake in real time and learning from it on their own" "Learn" I agree. But as an immediate output, weirdly not always: they can sometimes recognise they made a mistake and correct it.
  - danaris 1y ago
    > When they don't have the tools to exercise that capability, it's a distinction without any practical impact. It has huge practical impact. If a human doesn't currently have the tools to exercise the capability, you can help them get those. This is especially true when the tools in question are things like "enough time to actually think about their work, rather than being forced to rush through everything" or "enough mental energy in the day to be able to process and learn, because you're not being kept constantly on the edge of a breakdown." Or "the flexibility to screw up once in a while without getting fired." Now, a lot of managers refuse to give their subordinates those tools, but that doesn't mean that there's no practical impact. It means that they're bad managers and awful human beings. An LLM will just always be nondeterministic. If you're the LLM "worker"'s "boss", there is nothing you can do to help it do better next time. > they can sometimes recognise they made a mistake and correct it. ...And other times, they "recognize they made a mistake" when they actually had it right, and "correct it" to something wrong. "Recognizing you made a mistake and correcting it" is a common enough pattern in human language—ie, the training corpus—that of course they're going to produce that pattern sometimes.
    - ben_w 1y ago
      > you can help them get those. A generic "you" might, I personally don't have that skill. But then, I've never been a manager. > An LLM will just always be nondeterministic. This is not relevant, humans are also nondeterministic. At least practically speaking, theoretically doesn't matter so much as we can't duplicate our brains and test us 10 times on the same exact input without each previous input affecting the next one. > If you're the LLM "worker"'s "boss", there is nothing you can do to help it do better next time. Yes there is, this is what "prompt engineering" (even if "engineering" isn't the right word) is all about: https://en.wikipedia.org/wiki/Prompt_engineering https://en.wikipedia.org/wiki/Prompt_engineering > "Recognizing you made a mistake and correcting it" is a common enough pattern in human language—ie, the training corpus—that of course they're going to produce that pattern sometimes. Yes. This means that anthropomorphising them leads to a useful prediction. For similar reasons, I use words like "please" and "thank you" with these things, even though I don't actually expect these models to have constructed anything resembling a real human emotional qualia within them — humans do better when praised, therefore I have reason to expect that any machine that has learned to copy human behaviour will likely also do better when praised.

by ben_w 1y ago

danaris 1y ago

> Wildly varies depending on the human. Sure. And the situation. But the difference is, all humans are capable of it, whether or not they have the tools to exercise that capability in any given situation. No LLM is capable of it*. * Where "it" is "recognizing they made a mistake in real time and learning from it on their own", as distinct from "having their human handlers recognize they made 20k mistakes after the fact and running a new training cycle to try to reduce that number (while also introducing fun new kinds of mistakes)".

ben_w 1y ago
> But the difference is, all humans are capable of it, whether or not they have the tools to exercise that capability in any given situation. When they don't have the tools to exercise that capability, it's a distinction without any practical impact. > Where "it" is "recognizing they made a mistake in real time and learning from it on their own" "Learn" I agree. But as an immediate output, weirdly not always: they can sometimes recognise they made a mistake and correct it.
- danaris 1y ago
  > When they don't have the tools to exercise that capability, it's a distinction without any practical impact. It has huge practical impact. If a human doesn't currently have the tools to exercise the capability, you can help them get those. This is especially true when the tools in question are things like "enough time to actually think about their work, rather than being forced to rush through everything" or "enough mental energy in the day to be able to process and learn, because you're not being kept constantly on the edge of a breakdown." Or "the flexibility to screw up once in a while without getting fired." Now, a lot of managers refuse to give their subordinates those tools, but that doesn't mean that there's no practical impact. It means that they're bad managers and awful human beings. An LLM will just always be nondeterministic. If you're the LLM "worker"'s "boss", there is nothing you can do to help it do better next time. > they can sometimes recognise they made a mistake and correct it. ...And other times, they "recognize they made a mistake" when they actually had it right, and "correct it" to something wrong. "Recognizing you made a mistake and correcting it" is a common enough pattern in human language—ie, the training corpus—that of course they're going to produce that pattern sometimes.
  - ben_w 1y ago
    > you can help them get those. A generic "you" might, I personally don't have that skill. But then, I've never been a manager. > An LLM will just always be nondeterministic. This is not relevant, humans are also nondeterministic. At least practically speaking, theoretically doesn't matter so much as we can't duplicate our brains and test us 10 times on the same exact input without each previous input affecting the next one. > If you're the LLM "worker"'s "boss", there is nothing you can do to help it do better next time. Yes there is, this is what "prompt engineering" (even if "engineering" isn't the right word) is all about: https://en.wikipedia.org/wiki/Prompt_engineering https://en.wikipedia.org/wiki/Prompt_engineering > "Recognizing you made a mistake and correcting it" is a common enough pattern in human language—ie, the training corpus—that of course they're going to produce that pattern sometimes. Yes. This means that anthropomorphising them leads to a useful prediction. For similar reasons, I use words like "please" and "thank you" with these things, even though I don't actually expect these models to have constructed anything resembling a real human emotional qualia within them — humans do better when praised, therefore I have reason to expect that any machine that has learned to copy human behaviour will likely also do better when praised.