Conversation

, and Jim Keller

239

Jim Keller basically defined x86-64 whilst at AMD and comments on the complexity of variety of computer chips and technology involved in Tesla tech.

notes that he's the software to Jim's hardware, that one of his proudest achievements was in getting CS231n started at Stanford. Majority of audience have read his work or heard his lectures.

asks what's missing in current AI tech and whether Tesla use open source existing stacks or custom. Jim notes the efficiencies gained by specializing and removing overheads between components. Elon/

@karpathy

note this can give 10x the power at a tenth the cost.

Specifically that bottlenecks between the hardware and software can destroy much of the gains in a pipeline / integration - essentially Amdahl's law but across a pipeline.

Zaremba et al. (as I know him 🤣) asks the timeline for self driving cars.

makes a bold statement of two years for full self driving, three years for an order of magnitude better than humans. These gains are not binary, they can still be incremental even in driving.

Question regarding slaughter bots - "any competent drone company could do it".

@shivon

notes that biological and chemical attacks are right now quite possible with minimal work but that society has guarded against it.

argues regulation is two years for study, ...

two years for discussing how to do oversight, then first rule six years later.

argues the backlash from the first large scale AI disaster scenario where we had no preventative regulation will hamper progress far more than having had AI regulation in the first place.

Q: re how invasive neural link tech would need to be.

thinks it will be invasive but similar to lasik. Without it equivalent to your ears against a factory's wall - no good information. Sees this as necessary to maintain competitive advantage vs rapid progress of AI.

Even if half of all new produced vehicles are autonomous, it's 2%/year that would be pushed to unemployed.