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> That's not true. Yes, you can get more effective at something with more effort, but you can get even more effective at it if you find a way to get results wit

> That's not true. Yes, you can get more effective at something with more effort, but you can get even more effective at it if you find a way to get results without actually doing the work yourself in the first place. This has been going on for decades. It is called outsourcing development. We've just previously passed the work to people in countries with lower wages and conditions, now people are increasingly passing the work to a predictive text engine (either directly, or because that is what the people they are outsourcing to are doing). Personally I'm avoiding the “AI” stuff¹, partly because I don't agree with how most of the models were trained, partly because I don't want to be beholden to an extra 3rd party commercial entity to be able to do my job, but mainly because I tinker with tech because I enjoy it. Same reason I've always avoided management: I want to do things, not tell others to do things. If it gets to the point that I can't work in the industry without getting someone/something else to do the job for me, I'll reconsider management or go stack shelves! -------- [1] It is irritating that we call it AI now because the term ML became unfashionable. Everyone seems to think we've magically jumped from ML into _real_ AI which we are having to make sure we call something else (AGI usually) to differentiate reasoning from glorified predictive text.

sshine 2y ago
> Everyone seems to think we've magically jumped from ML into _real_ AI But we have: - LLMs pass the Turing test more convincingly than anything before - LLMs are vastly more popular than any AI/ML methods before it - "But they don't reason!" -- we're advancing chain of thought LLMs are AI (behaving artificially human) LLMs are also ML (using statistical methods)
- bluefirebrand 2y ago
  > LLMs pass the Turing test more convincingly than anything before I know this sounds like moving the goalposts, but maybe all this does is show that the Turing Test was not sufficient? > LLMs are vastly more popular than any AI/ML methods before it Are we back in high school? Popularity contests?
  - lupire 2y ago
    The Turing test was never a deep thesis. It was an offhand illustration of the challenge facing AI efforts, citing an example of something that was clearly impossible with technology of the day.
- enugu 2y ago
  The Turing test is meant to see if computers can functionally replicate human thought (just focussing on textual conversations aspect for simplicity). The implications of passing the Turing Test are profound. Tricking a user with a 5 minute conversation isn't the same. The examiner is allowed to be an expert questionner. For one thing, software engineering would quickly be taken over as a client can just chat with an AI to get the code. That is far from happening, even with all the recent LLM advances. Similarly for literature, science etc. Currently, you can detect a difference between a competent human & machine in all these fields just by text chat. Another way of saying this is that the Turing Test is AI-complete and is a test for AGI.
  - SAI_Peregrinus 2y ago
    And there's a more general sort of Turing test: Just like the original test, there are 3 participants in a test: an examiner, a human, and an AI. The examiner may ask any question or series of questions to the human &/or AI, and receive responses. This is done via text or other means which prevent the examiner from directly seeing the body of responder. Both AI and human are to attempt to convince the examiner that they're the human. Unlike the original test, it then needs to repeat with different examiners. If there exists an examiner which can distinguish an AI from a human (for all humans) in a Turing test with probability non-negligibly different from 50%, then the AI fails this meta-Turing Test. Just because an AI can fool some people doesn't mean it's a human-equivalent intelligence.
    - TeMPOraL 2y ago
      Your "meta-Turing Test" is rigged. There are 8 billion humans on this planet, statistically someone is bound to be able to distinguish AI from a human with near-100% accuracy across a reasonable amount of rounds through sheer chance. Existence is too strong a criterion. Even correcting for random chance, if there's 1, 10, 100, even 1 000 000 examiners who could distinguish an AI from a human with high probability, that steal means the AI passed the test in practice, because even a million examiners is still a rounding error compared to the human population.
  - sshine 2y ago
- dspillett 2y ago
  > LLMs pass the Turing test more convincingly than anything before Being able to converse (or convince someone the conversation is natural) is not the same as being able to perform a technical task well. The same applies to humans as well, of course, which perhaps brings us back to the outsourcing comparison — how often does that work out great or not? > LLMs are vastly more popular than any AI/ML methods before it Popular is not what I'm looking for. I've seen the decisions the general public make elsewhere, I'm not letting them chose how I do my job :) > "But they don't reason!" -- we're advancing chain of thought Call me back when we've advanced chain of thought much more than is currently apparent, and again: for being correct in technical matters, not conversation.

sshine 2y ago

> Everyone seems to think we've magically jumped from ML into _real_ AI But we have: - LLMs pass the Turing test more convincingly than anything before - LLMs are vastly more popular than any AI/ML methods before it - "But they don't reason!" -- we're advancing chain of thought LLMs are AI (behaving artificially human) LLMs are also ML (using statistical methods)

bluefirebrand 2y ago
> LLMs pass the Turing test more convincingly than anything before I know this sounds like moving the goalposts, but maybe all this does is show that the Turing Test was not sufficient? > LLMs are vastly more popular than any AI/ML methods before it Are we back in high school? Popularity contests?
- lupire 2y ago
  The Turing test was never a deep thesis. It was an offhand illustration of the challenge facing AI efforts, citing an example of something that was clearly impossible with technology of the day.
enugu 2y ago
The Turing test is meant to see if computers can functionally replicate human thought (just focussing on textual conversations aspect for simplicity). The implications of passing the Turing Test are profound. Tricking a user with a 5 minute conversation isn't the same. The examiner is allowed to be an expert questionner. For one thing, software engineering would quickly be taken over as a client can just chat with an AI to get the code. That is far from happening, even with all the recent LLM advances. Similarly for literature, science etc. Currently, you can detect a difference between a competent human & machine in all these fields just by text chat. Another way of saying this is that the Turing Test is AI-complete and is a test for AGI.
- SAI_Peregrinus 2y ago
  And there's a more general sort of Turing test: Just like the original test, there are 3 participants in a test: an examiner, a human, and an AI. The examiner may ask any question or series of questions to the human &/or AI, and receive responses. This is done via text or other means which prevent the examiner from directly seeing the body of responder. Both AI and human are to attempt to convince the examiner that they're the human. Unlike the original test, it then needs to repeat with different examiners. If there exists an examiner which can distinguish an AI from a human (for all humans) in a Turing test with probability non-negligibly different from 50%, then the AI fails this meta-Turing Test. Just because an AI can fool some people doesn't mean it's a human-equivalent intelligence.
  - TeMPOraL 2y ago
    Your "meta-Turing Test" is rigged. There are 8 billion humans on this planet, statistically someone is bound to be able to distinguish AI from a human with near-100% accuracy across a reasonable amount of rounds through sheer chance. Existence is too strong a criterion. Even correcting for random chance, if there's 1, 10, 100, even 1 000 000 examiners who could distinguish an AI from a human with high probability, that steal means the AI passed the test in practice, because even a million examiners is still a rounding error compared to the human population.
- sshine 2y ago
dspillett 2y ago
> LLMs pass the Turing test more convincingly than anything before Being able to converse (or convince someone the conversation is natural) is not the same as being able to perform a technical task well. The same applies to humans as well, of course, which perhaps brings us back to the outsourcing comparison — how often does that work out great or not? > LLMs are vastly more popular than any AI/ML methods before it Popular is not what I'm looking for. I've seen the decisions the general public make elsewhere, I'm not letting them chose how I do my job :) > "But they don't reason!" -- we're advancing chain of thought Call me back when we've advanced chain of thought much more than is currently apparent, and again: for being correct in technical matters, not conversation.