Andrej Karpathy: Tesla AI, Self-Driving, Optimus, Aliens, and AGI | Lex Fridman Podcast #333

Anyone seriously interested in this question should listen to the Lex Friedman interview of Andrej Karpathy: [VIDEO]

Andrej Karpathy was recently on Lex Fridman's podcast and covered this to some extent. He has the same perspective on this topic and expanded on it quite a bit. Great listen overall IMHO - [VIDEO] I like his idea of finding 0-days in physics. :)

My understanding is the transformer layer in the LLM is basically doing something akin to message passing, it’s like a mini computer. In predicting the next word, it has to understand a lot about a lot of different kinds of topics My understanding is kinda fuzzy because I haven’t coded it up myself, but this was the takeaway I got from this explanation (starts at 36:21) [VIDEO]

At 1:03:30 - [VIDEO] > I think there's definitely scope in building a better search engine today. Google have all the tools, all the people, (...) all the data, it's just not obvious that they're capable as an organization to innovate on their search engine right now, and if they don't, someone else will. There's absolutely scope to build a better search engine based on these tools.

If you want to get an idea, why not listen to some engineers that have worked with him? There are plenty of those around, for example, Andrej Karpathy talked a bit about working with Elon recently - [VIDEO]

As pointed out in [1], it seems machine learning takes the same path as physics already did. In the mid-20th century there was a "break" in physics, before individuals were making ground breaking discoveries in their private/personal labs (think Newton, Maxwell, Curie, Roentgen, Planck, Einstein, and many others) later huge collaborations (LHC/CERN, Icecube, EHT, et al.) are required, since the machinery, simulations, models are so complex, that groups of people are needed to create, comprehend and use them. 1. [VIDEO] Lex Fridman podcast with Andrej Karpathy P.S. To counteract that (unintentionally actually, likely because of a simple optimization of instruments' duty cycle) in astronomy people come up with a concept of "observatory" (Like Hubble, JWST) instead of "experiment" (like LHC, HESS telescopes) where outside people can submit their proposals, and if selected get observational time. Along with raw data authors of the proposals get required expertise from the collaboration to process and analyze that data.

Yeah, check out the Lex Friedman podcast episode #333 around minute 52 where Andrew Karpathy talks about the OpenAI project "World of Bits" that did this. [VIDEO]

>your boyfriend’s only in a wheelchair because he doesn’t want to kneel five times a day Within the roast context, this is a good line. Humor was one of the tests Karpathy would use as a benchmark for AI: [VIDEO]