Dithering!

That’s not necessarily true either. You can make inference deterministic by setting the RNG seed and having the model select the highest likelihood token/ sequence instead of choosing at random.

That’s demonstrably incorrect. Different instructions give different outcomes.

Perhaps not fine-tuning weights but they can certainly use feedback from PR comments to optimise guardrails etc. And it’s definitely possible to have an agent experiment with that. And yes the Devs are the guinea pigs in that context!

You don’t need to train a foundation model from scratch. You can fine tune an existing coding model or only a LORA layer on a budget.

You could also just use the feedback to optimise system prompts, skills/ guidance or verification tools.

I presume they’re gathering this as training data and hope to later get rid of OP.

That’s why cursor went for $60bn. Anyone can make a harness. The real value is that it gathers data on which changes are accepted/ integrated.

Can’t believe the strength of opinion on this post! I assume it’s people frustrated that you dare post a pun in a (non-American) dialect… or perhaps you’ve touched a raw nerve in Oldham!

I meant it as a joke but I could imagine them getting one email from Germany about GDPR and then deciding to geoblock the whole country instead of complying (and ignoring the fact it applies elsewhere in Europe too).

Maybe they really couldn’t be bothered with writing an Impressum!