This is my conversation with Jeffrey Quesnelle, cofounder of Nous Research.

Timestamps:
- (00:00:00) intro
- (00:01:08) working with new technologies
- (00:06:15) Nous Research origin story
- (00:14:08) open frontiers in research
- (00:26:07) fourier transforms for gradient compression
- (00:32:58) math behind distributed training
- (00:38:18) sponsor: Splits
- (00:39:02) neural networks history and fundamentals
- (00:51:29) the human mind and AI, hyperdimensional representation
- (01:01:15) intuition and reasoning
- (01:15:00) parallels with reinforcement learning
- (01:19:15) the cat is out of the bag
- (01:47:11) deeper mysteries

Links:
- Jeffrey Quesnelle: https://jeffq.com/
- Jeffrey Quesnelle on X: https://x.com/theemozilla
- Nous Research: https://nousresearch.com/
- Psyche: https://nousresearch.com/nous-psyche/

Thank you to our sponsor for making this podcast possible:
- Splits: https://splits.org

Into the Bytecode:
- Sina Habibian on X: https://twitter.com/sinahab
- Sina Habibian on Farcaster: https://warpcast.com/sinahab
- Into the Bytecode: https://intothebytecode.com

Disclaimer:
This podcast is for informational purposes only. It is not financial advice nor a recommendation to buy or sell securities. The host and guests may hold positions in the projects discussed.