Thread

1. ErrantX · 1790879836 · focus · HN ↗

   What is interesting to me is in 2016 people were like; pass Turing test, write code, order me a coffee.

   And even in 2024 the themes are similar, generally more complex or specific about the coding/turing/action test.

   But in 2026 a huge shift, we have things like; can open a physical door, emulates human pettiness convincingly, makes novel scientific breakthroughs.

   That alone tells you a lot IMO

   1. ianjbutler · 1790882681 · focus · HN ↗

      Sigh, the whole "obviously the turing test is solved" meme is annoying.

      Like, if we meant that it convincingly masquerades as a shitposter, ok. But everyone still bitches about AI slop, and everyone knows the writing is still bad. How does that even work if the turing test is obviously solved?

      More to the point though, if you grill SOTA models on counterfactuals, causal world-models etc, you'll trip them up in a way that actually will not work on ESL students and children. Certainly there's no way to find a person that struggles with that and is also capable of cheerful fluent erudite discussion about astrophysics with perfect grammar. Yes, it's getting harder obviously.. but detecting machines with determined, focused and intelligent interrogation remains pretty easy. If nothing else, the models are cooperative where people wouldn't be and that's a signal too.

      The best progress we've made is that most people do agree that this doesn't practically matter very much, i.e. we generally recognize the stakes were always overstated. But the constant vague appeals to common-sense that "of course it's a solved problem!" always feels naive or fake.

      1. ex-aws-dude · 1790899761 · focus · HN ↗

         Well the whole lesson learned was that the Turing Test as it was defined was way too easy, it was a bad criteria for GI because it underestimates how easily humans find meaning/patterns in things.

         I mean you could show people random markov chain gibberish in 1996 and they would swear they found intelligent meaning in it

         <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Markovian_Parallax_Denigrate" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Markovian_Parallax_Denigrate

         1. zahlman · 1790936401 · focus · HN ↗

            Those examples look to me more like entirely randomly selected words than Markov chain output. Even a relatively simple and naive Markov chain would usually manage to put some kind of verb after &quot;you&#x27;d&quot;, rather than a noun like &quot;dendrite&quot;, because it would overwhelmingly be followed by a verb (or some modifier like &quot;never&quot;) in the training corpus.

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