Simon Willison talking about the recently unveiled Jev:

Something I’ve found a little uncomfortable about Jev is how it very much represents a regression even further towards black box machine learning systems.

LLMs are black boxes already—you can ask them to justify their decisions, but you can’t guarantee that what they say is useful or accurate.

Jev doesn’t even give you that: put in all the text you want, the only thing you’re going to get back is a floating point number. […]

This also means that concerns about bias should be front and center. I really hope nobody uses Jev to rank job applicants—that floating point number could conceal all manner of unseen bias baked into the models

Somebody send me the prediction market bet on whether people are already building exactly this. I’m interested in making a very large wager that they are…

Simon Willison:

Almost anyone can prompt an LLM to generate a thousand-line patch and submit it for code review. That’s no longer valuable. What’s valuable is contributing code that is proven to work.

I, for one, can’t wait to be out of this “look I can have a robot write code for me” moment and instead move on to the “should I have a robot write code for me” aftermath.

[Insert meme here of Ian Malcom on Jurassic park “you were so preoccupied with whether you could you didn’t stop to think if you _should_”.]