Comment by qarl
10 hours ago
The "auto-complete" thing is a false framing.
Complete this sentence: "You can solve world hunger by..."
Intelligence is required to finish sentences. It's not just a Markov chain.
10 hours ago
The "auto-complete" thing is a false framing.
Complete this sentence: "You can solve world hunger by..."
Intelligence is required to finish sentences. It's not just a Markov chain.
Leaving aside the fact we have solutions for things like climate change and will not implement them, regardless of who or what recommends them... My keyboard offers "You can solve world hunger by using a Ted Bungie algorithm." Which sounds reasonable on its face until I research Ted Bungie and the algorithms he developed.
Granted, my phone keyboard lacks a substantial dictionary, offers words instead of tokens, has a very small context window, and doesn't randomize outputs (Ted Bungie is its primary recommendation every time), but those are basically parameters to the existing autocomplete.
Fair point. In that case, it’s imperative you share this* with your local representative: https://chatgpt.com/share/6ab29440-6944-83ea-853f-8060dc58da...
*This un actionable summary of existing discourse. The real world doesn’t produce traces or take HTTP requests.
You're straw manning me.
Obviously there is no solution to world hunger right now. Nevertheless - finishing sentences is not pattern matching - and it's extremely obvious that whatever is going on inside LLMs is not pattern matching.
Language is absolutely pattern matching, and the whole thing is that the more patterns you put in, the more the transformer can pull out what’s useful. Agents are this effective because people figured out that training on tasks being completed gets the models to complete tasks - that’s pattern matching.
And it can only go so far, where those patterns are feasibly captured, eg internet discussions and coding and mathematics. It won’t measure up to the scaling laws of the physical world.
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