If you can code, build a small AI with the fast.ai course. This will (hopefully) be fun while also showing you particular holes in your knowledge to improve, rather than a vague feeling of “learn more”.
If you want to follow along with more technical papers, you need to know the math of machine learning: linear algebra, multivariable calculus, and probability theory. For Agent Foundations work, you’ll need more logic and set theory type stuff.
MIRI has some recommendations for textbooks here. There’s also the Study Guide and this sequence on leveling up.
3blue1brown’s Youtube has good videos for a lot of this, if that’s the medium you like.
If you like non-standard fiction, some people like Project Lawful.
At the end of the day, it’s not a super well-defined field that has clear on-ramps into the deeper ends. You just gotta start somewhere, and follow your curiosity. Have fun!
If you can code, build a small AI with the fast.ai course. This will (hopefully) be fun while also showing you particular holes in your knowledge to improve, rather than a vague feeling of “learn more”.
If you want to follow along with more technical papers, you need to know the math of machine learning: linear algebra, multivariable calculus, and probability theory. For Agent Foundations work, you’ll need more logic and set theory type stuff.
MIRI has some recommendations for textbooks here. There’s also the Study Guide and this sequence on leveling up.
3blue1brown’s Youtube has good videos for a lot of this, if that’s the medium you like.
If you like non-standard fiction, some people like Project Lawful.
At the end of the day, it’s not a super well-defined field that has clear on-ramps into the deeper ends. You just gotta start somewhere, and follow your curiosity. Have fun!
Vanessa Kosoy has a list specifically for her alignment agenda but is probably applicable to agent foundations in general: https://www.alignmentforum.org/posts/fsGEyCYhqs7AWwdCe/learning-theoretic-agenda-reading-list