cross-posted from: https://piefed.world/c/tech/p/1394707/study-reveals-how-generative-ai-is-eroding-the-development-pathway-for-software-develope
In-depth interviews with 14 junior and senior developers in Korea reveal four structural changes
cross-posted from: https://piefed.world/c/tech/p/1394707/study-reveals-how-generative-ai-is-eroding-the-development-pathway-for-software-develope
In-depth interviews with 14 junior and senior developers in Korea reveal four structural changes
I worry the same thing happening in all fields, especially medical. we train the models on experts, then give the newbies the model… so when and how do we improve and retrain these models, and ok what data?
The thing about medical is that it’s so big - no one expert can cover even a small fraction of “medical”. So, unless you have a whole team of specialists there on-hand, you just might benefit from having some “automated experts” available when you need the pattern recognition they can offer.
Except the medical expert in field A can’t be the human in the loop to verify the AI medical slopPut for field B is correct, cuz the medical expert isn’t an expert in field B. A team of human specialists will be better in the long run.
For the 0.1% of the population who can afford to assemble a team of human specialists in a timely fashion when they need them…
For the rest of us, cyborg M.D.s with brain augmentation (they called this a PubMed search in the 1990s, it’s faster and more effective today) are better than the un-augmented M.D.s we can afford.
Psychotic.
The thing about software is that it’s so big - no one expert can cover even a small fraction of “software”. If you’re a kernel driver developer, you might benefit from having some “automated experts” available in CSS/HTML for the pattern recognition they can offer.
I find it amusing how most experts think AI is great for every field except theirs.