Vital inconsistencies stay between our present empirical setting and the final word downside of adapting the Superman mannequin. For instance, future fashions could imitate weak human errors extra simply than present robust fashions imitate present weak mannequin errors, which can make future generalization tougher.
Nonetheless, we imagine that our setup captures a number of the key difficulties in adapting future fashions of Superman, permitting us to start making empirical progress on this problem right this moment. There are lots of promising instructions for future work, together with repairing dissimilarities in our setting, growing higher scalable strategies, and bettering our scientific understanding of when and how you can anticipate good weak-to-strong generalization.
We imagine that is an thrilling alternative for the machine studying analysis group to make progress in alignment. To provoke extra analysis on this space,
- We’re releasing open supply code right this moment to make it straightforward to begin weak-to-strong generalization experiments.
- We’re launching a $10 million grant program to supply graduate college students, lecturers, and different researchers with broad-based work on superhuman synthetic intelligence alignment. We’re notably happy to assist analysis associated to weak-to-strong generalization.
Determining how you can make future superhuman synthetic intelligence programs secure has by no means been extra vital, and it’s now simpler than ever to make empirical progress on the issue. We’re excited to see what breakthroughs researchers uncover.