The sentiment of the comments here seems rather pessimistic. A perspective that balances both sides might be that the rate of mass adoption of some technology often lags behind the frontier capabilities, so I wouldn’t expect AI to take over a majority of those jobs in GPDval in a couple of years, but it’ll probably happen eventually.
There are still fundamental limitations in both the model and products using the model that restrict what AI is capable of, so it’s simultaneously true that AI can do cutting edge work in certain domains for hours while vastly underperforming in other domains for very small tasks. The trajectory of improvement of AI capabilities is also an unknown, where it’s easy to overestimate exponential trends due to unexpected issues arising but also easy to underestimate future innovations.
I don’t see the trajectory slowing down just yet with more compute and larger models being used, and I can imagine AI agents will increasingly give their data to further improve larger models.
There are still fundamental limitations in both the model and products using the model that restrict what AI is capable of, so it’s simultaneously true that AI can do cutting edge work in certain domains for hours while vastly underperforming in other domains for very small tasks. The trajectory of improvement of AI capabilities is also an unknown, where it’s easy to overestimate exponential trends due to unexpected issues arising but also easy to underestimate future innovations.
I don’t see the trajectory slowing down just yet with more compute and larger models being used, and I can imagine AI agents will increasingly give their data to further improve larger models.