The speaker expects AI systems' main difficulty in AI research and development to be the intuition needed to select and design large-scale de-risking experiments and choose hyperparameters under uncertainty.

“bug and that seems like very doable and you could do a bunch of stuff there's a bunch of things you could do along these lines that I think would work reasonably well and so I think that on that specific point I think it's doable and then the main thing is that I think there's like some cases where like you need there's other intuition about like which exact large scale like de-risking experiments do you need to run how should you orient them how should you like pick hyper parameters in uncertain cases or like things that are like analogous to hyper parameters and that's I think the thing that they as might most struggle with but I currently expect”