#51 – Jeffrey Quesnelle on Nous Research, large language models, and the human mind
Description
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.
United States
