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Joined 1 year ago
Joined 1 year ago
I used to work at startup that did video encoding. We had tons of computer vision scientists that refused to learn decent C++ coding practices. Their stuff never worked right and they didn't really contribute much. We also had a few scientists who were decent coders and pretty much all progress came from them.
I see the same with some data scientists. They want to do pure data science and refuse to do the coding to actually get their data. So they have to be spoon fed all the time and their progress is super slow.
I used to do that but it's a dangerous game. If you don't make sure to still be very visible to management further up, you end up with a stalled career or being laid off.
"don't even bother to check it."
I have to admit it gets really exhausting to review the AI output. It comes in so fast and more and more it's quite good. So it's very tempting to get more relaxed about reviews. I guess in a sense manual coding gave you some mental downtime while writing code. With AI you don't get that anymore. It's always full speed.
Neither do Anthropic and OpenAI.
I highly doubt that New Mexico will get 25. Although it would be nice since I live in New Mexico.