This is my conversation with Michael Nielsen, scientist, author, and research fellow at the Astera Institute.

Timestamps:
- (00:00:00) intro
- (00:01:06) cultivating optimism amid existential risks
- (00:07:16) asymmetric leverage
- (00:12:09) are "unbiased" models even feasible?
- (00:18:44) AI and the scientific method
- (00:23:23) unlocking AI's full power through better interfaces
- (00:30:33) sponsor: Splits
- (00:31:18) AIs, independent agents or intelligent tools?
- (00:35:47) autonomous military and weapons
- (00:42:14) finding alignment
- (00:48:28) aiming for specific moral outcomes with AI?
- (00:54:42) freedom/progress vs safety
- (00:57:46) provable beneficiary surveillance
- (01:04:16) psychological costs
- (01:12:40) the ingenuity gap

Links:
- Michael Nielsen: https://michaelnielsen.org/
- Michael Nielsen on X: https://x.com/michael_nielsen
- Michael's essay on being a wise optimist about science and technology: https://michaelnotebook.com/optimism/
- Michael's Blog: https://michaelnotebook.com/
- The Ingenuity Gap (Tad Homer-Dixon): https://homerdixon.com/books/the-ingenuity-gap/

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.

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.

This is my conversation with Alexander Long, Founder & CEO of Pluralis Research.

Timestamps:
- (00:00:00) intro
- (00:00:55) collaborative training
- (00:09:49) economics of training
- (00:13:10) what is protocol learning?
- (00:20:48) protocol learning design and politics
- (00:33:39) sponsor: Splits
- (00:34:22) hardware requirements
- (00:41:53) adapting to the landscape
- (00:49:53) open and closed models
- (00:52:52) market structure with fully open models
- (00:56:34) research and risks
- (01:02:19) labor and national security
- (01:10:58) looking to the future
- (01:14:20) outro

Links:
- Alexander on X: https://x.com/_alexanderlong
- Alexander on Github: https://github.com/AlexanderJLong
- Article 2: Protocol Learning, Protocol Models and the Great Convergence: https://www.pluralisresearch.com/p/article-2-protocol-learning-protocol
- Decentralized Training Looms: https://www.pluralisresearch.com/p/decentralized-ai-looms

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.