[dinfinity]

> This, in turn, leaves "AI" implementations with no new human content to feed off of. Now what?

You seem to be under the impression that AI needs more than all recorded human knowledge up until 2024 to reach the same level as an average SO contributor. It doesn't. Because none of the average SO contributors did.

It is unclear what algorithmic improvements are required to leverage the available data to get AI to AGI, but a lack of data is definitely not the bottleneck.

One could say that these AI systems aren't sharing their solutions (or questions) with other AI systems and that the world would benefit from it if they did, though. Perhaps it's a good idea to have some shared space for AI systems where they share the validated solutions they synthesized.

[dragonwriter]

> You seem to be under the impression that AI needs more than all recorded human knowledge up until 2024 to reach the same level as an average SO contributor.

Replacing the average SO cobtributor isn't adequate to replace SO, and AI is able to “replace” SO effectively only since major models have gotten not only SO-as-training-data but web search (including SO) for immediate grounding.

And without SO or something like it with active human contributions it’ll have even more trouble replacing the value SO would provide for new questions and new domains where it will neither have SO traijing data nor SO query-time-search-results to use to synthesize answers.

[dinfinity]

You're not addressing my main point, which is that humans don't need anything close to the amount of relevant data available to current and near future AI to reach SO contributor level. The idea that the lack of new human synthesized Stackoverflow data must be a future bottleneck is thus nonsense.

Don't pretend that the current state of LLM training is somehow indicative of a fundamental problem for AI.