The speaker argues that AI performance on tasks with reasonably reliable verification and feedback is sufficient to make AI research and development proceed quickly.

“being well on but not amazingly on and often are like doing a bit of weird shit because we can't train as well in those tasks but we do some online training people find various hacks they work around it and so basically everything that we can verify reasonably well with some feedback loop the ais are doing pretty well on and that's sufficient to make r and d go quite fast and to continue but there are some parts of it of developing uh aligned and safe ais that are more subtle hard to check depend on you know detailed in the weeds things and i would even say that”