Jeffrey Quesnelle on Nous Research, large language models, and the human mind

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.