Design@Large Series: How Might We Learn?

About How Might We Learn?
When people talk about the most rewarding, high-growth periods of their lives, a pattern emerges: they learned a lot, but learning wasn’t the point. Instead, they were immersed in some purpose with real personal meaning-like a startup, a research project, or a burning question-and they learned whatever was important along the way.
If these experiences are so rewarding, why are they so rare? Why can’t we learn everything by “just diving in”? Why does learning so often fail to work as we hope, leaving us with brittle, fragmentary understanding? In this talk, Andy Matuschak will propose some paths forward and suggest how AI could help us create powerful new kinds of enabling environments.
About the Speaker
Andy Matuschak is an independent researcher focused on inventing mediums that expand human intellectual and creative capacity. His recent work has centered on rethinking the book to actively help people remember, understand, and use what they read. Before establishing his own lab, Andy led Khan Academy’s R&D team and helped build iOS at Apple.

[@ward_heimdal]

Andy's worth reading. He's exceptionally insightfwl.

[@mabeteekay1403]

Nice talk , on the Social connection part , i think ai would help very much , imagine learning about a software engineer related concept and ai just recommends a Github repository to learn more and connect with other developers , potentially connecting you with industry giants , i mean that its peak immersive learning , mix that with memory systems like space repetition , you retain a lot ,and in turn you ask it more question based on the repository and in the context of what you are learning , and it deepens the context even more , this leads to grokking the material . i think this kind of AI would benefit a lot of people , but yes , it must be local , catered to your needs . AMAZING talk , Peace.

[@palimondo]

Talk starts at 4:05

[@ashish3354]

10:37