I’ve been using Copilot for over a year now, and this is more or less how I use it: To help me quickly blast through boilerplate code so I can more quickly get to the tricky bits.
There’s a more subtle problem with ChatGPT’s code generation, which is that it suffers from ChatGPT’s general “bullshit” problem.
It doesn’t bother me much that bleeding-edge ML technology sometimes gets things wrong. It bothers me a lot when it gives no warnings, cites no sources, and provides no confidence interval.
Yes! Like I said:
Expose the wires. Show the workings-out.
A very astute framing by Ted Chiang—large language models as a form of lossy compression for text.
When we’re dealing with sequences of words, lossy compression looks smarter than lossless compression.
A lot of uses have been proposed for large language models. Thinking about them as blurry JPEGs offers a way to evaluate what they might or might not be well suited for.