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[return to "Scaling long-running autonomous coding"]
1. halfca+mm[view] [source] 2026-01-20 04:05:44
>>srames+(OP)
So AI makes it cheaper to remix anything already-seen, or anything with a stable pattern, if you’re willing to throw enough resources at it.

AI makes it cheap (eventually almost free) to traverse the already-discovered and reach the edge of uncharted territory. If we think of a sphere, where we start at the center, and the surface is the edge of uncharted territory, then AI lets you move instantly to the surface.

If anything solved becomes cheap to re-instantiate, does R&D reach a point where it can’t ever pay off? Why would one pay for the long-researched thing when they can get it for free tomorrow? There will be some value in having it today, just like having knowledge about a stock today is more valuable than the same knowledge learned tomorrow. But does value itself go away for anything digital, and only remain for anything non-copyable?

The volume of a sphere grows faster than the surface area. But if traversing the interior is instant and frictionless, what does that imply?

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2. ramraj+jr[view] [source] 2026-01-20 05:07:17
>>halfca+mm
The fundamental idea that modern LLMs can only ever remix, even if its technically true (doubt), in my opinion only says to me that all knowledge is only ever a remix, perhaps even mathematically so. Anyone who still keeps implying these are statistical parrots or whatever is just going to regret these decisions in the future.
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3. heavys+Ss[view] [source] 2026-01-20 05:23:59
>>ramraj+jr
Yeah, Yann LeCun is just some luddite lol
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4. Curiou+Wi1[view] [source] 2026-01-20 13:08:38
>>heavys+Ss
You don't understand Yann's argument. It's similar to Richard Sutton's, in that these things aren't thinking, they're emulating thinking, and the weak implicit world models that get built in the weights are insufficient for true "AGI."

This is orthogonal to the issue of whether all ideas are essentially "remixes." For the record I agree that they are.

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