A few confounding factors come up right away: one of professors removed final project which increased grades; due to less appealing CS career, you do not get the best students anymore: another professor is not a fan of curving so perhaps he just accidentally gave harder tests; math prep for CS courses happened over the last 15 years not last 2 where LLMs have become ubiquitous; many failed because they were caught using LLMs when not allowed...

So really, two professors' gut feel about what the reasons are and not backed by much.

If humanity is over-reliant on frontier labs' models to perform work, the result is a dependence on the actual intelligence of these models -- not on human intelligence. This could be a small reason, on top of many others, why investors are throwing hundreds of billions of dollars a bit "carelessly" to these labs. It's fascinating seeing the models do the "hard work" (the deep, challenging thinking) for you.

The conundrum which tricks me though - is this a net negative or a positive? If humans are less intelligent, but their output is 2-3 times more intelligent (with AI), what's the result? At what point do we, as humans, stop comprehending anything and give all intelligent work to the neural nets?

And if that does happen, could we live in a society where no work, or at least a significantly less amount of work, is needed? To me, it seems like a dystopian net positive.

It might seem far-fetched to ask these, but I think these questions are getting more prevalent by the day.

Indeed, for work and software most are already beholden to Microsoft and Google. This is something wayy more.