these

You still take the full responsibility, I don't think leveraging AI reviews removes any layer of responsibility. The challenge is building the feedback loop (or the agent that builds the feedback loop) to make the review process actually catch what it needs to catch.

If AI can improve/speed up writing code, why shouldn't it improve/speed up code review?

Is n to the 1.9992 practically speaking subquadratic? Technically, yes, but is there a practically useful result here?

I don't really get it, seems like a gate keeping exercise for the academic community.

Of course OpenAI and others will hype any LLM led/assisted research results, and the media will find juicy headlines to write about it. But in the end they are publishing findings, and the academic community can gauge the developments and decide what they want to do with them. To me that seems like research working as expected.

> That’s assuming that you actually get those 50 people to work without blockers, stepping on each other, or other coordination issues. The coordination complexity alone is astounding.

This is a question of exceptional management, which needs to be present both in the Claude and human cases, and is scarce. Not everyone given the Claude tokens would be able to deliver the same result.

This seems like a great way to facilitate data gathering for improving LLMs coding performance.

If previously you needed to take action 1, 2, 3 to go from state A to B, all you saw was the change from A, B. Now you see intermediates 1, 2, 3 and can train the models to skip straight to B with the added context of the intermediate states.

Has anyone managed to get this to work in LM Studio? They've got a option in the UI, but it never seems to allow me to enable it.