#51 – Jeffrey Quesnelle on Nous Research, large language models, and the human mind
Into the Bytecode - Un pódcast de Sina Habibian
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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 mysteriesLinks:- 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.orgInto the Bytecode:- Sina Habibian on X: https://twitter.com/sinahab- Sina Habibian on Farcaster: https://warpcast.com/sinahab- Into the Bytecode: https://intothebytecode.comDisclaimer: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.
