Comment by sarchertech

Almost none of what you said about the past is true. Automated looms, and all of the other automated machinery that replaced artisans over the course of the industrial revolution produced items of much better quality than what human craftsman could produce by the time it started to be used commercially because of precision and repeatability. They did have quantitative measurements of quality for textiles and other goods and the automated processes exceeded human craftsman at those metrics.

Software is also not remotely similar to textiles. A subtle bug in the textile output itself won’t cause potentially millions of dollars in damages, they way a bug in an automated loom itself or software can.

No current technology is anywhere close to being able to automate 50% of PRs on any non trivial application (that’s not close to the same as saying that 50% of PRs merged at your startup happens to have an agent as author). To assume that current models will be able to get near 100% without massive model improvements is just that—an assumption.

My point about synthetic data is that we need orders of magnitude more data with current technology and the only way we will get there is with synthetic data. Which is much much harder to do with software applications than with chess games.

The point isn’t that we need a quantitative measure of software in order for AI to be useful, but that we need a quantitative measure in order for synthetic data to be useful to give us our orders of magnitude more training data.