[nphardon]

(In the semiconductor industry) We experienced brutal layoffs arguably due to over-investment into Ai products that produce no revenue. So we've had brutal job loss due to Ai, just not in the way people expected.

Having said that, it's hard to imagine jobs like mine (working on np-complete problems) existing if the LLMs continue advancing at the current rate, and its hard to imagine they wont continue to accelerate since they're writing themselves now, so the limitations of human ability are no longer a bottleneck.

[Jianghong94]

Maybe I'm being naive here, but for AI (heck, for any good algorithm) to work well, you need some at least loosely-clearly defined objectives. I assume it's much more straightforward in semi, but there're many industries, once you get into the details, all kinds of incentives start to disalign and I doubt AI could understand all kinds of nuances.

E.g. once I was tasked to build a new matching algorithm for a trading platform, and upon fully understanding of the specs I realized it can be interpreted as a mixed integer programming problem; the idea got shot down right away because PM don't understand it. There're all kinds of limiting factors once you get into the details.

[zozbot234]

AI can probably tell you how to best explain that idea to the boss. Or even write it up as a memo for you, if you use a more complex model.

[gmadsen]

I think those conversations occur due to changes in timeline of deliverables or certainty of result, would that not be an implementation detail?