Dwarkesh Podcast Dwarkesh Patel

I chatted with Tony Blair about:
- What he learned from Lee Kuan Yew
- Intelligence agencies track record on Iraq & Ukraine
- What he tells the dozens of world leaders who come seek advice from him
- How much of a PM’s time is actually spent governing
- What will AI’s July 1914 moment look like from inside the Cabinet?
Enjoy!
Watch the video on YouTube. Read the full transcript here.
Follow me on Twitter for updates on future episodes.
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Timestamps
(00:00:00) – A prime minister’s constraints
(00:04:12) – CEOs vs. politicians
(00:10:31) – COVID, AI, & how government deals with crisis
(00:21:24) – Learning from Lee Kuan Yew
(00:27:37) – Foreign policy & intelligence
(00:31:12) – How much leadership actually matters
(00:35:34) – Private vs. public tech
(00:39:14) – Advising global leaders
(00:46:45) – The unipolar moment in the 90s


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Here is my conversation with Francois Chollet and Mike Knoop on the $1 million ARC-AGI Prize they're launching today.
I did a bunch of socratic grilling throughout, but Francois’s arguments about why LLMs won’t lead to AGI are very interesting and worth thinking through.
It was really fun discussing/debating the cruxes. Enjoy!
Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. Read the full transcript here.
Timestamps
(00:00:00) – The ARC benchmark
(00:11:10) – Why LLMs struggle with ARC
(00:19:00) – Skill vs intelligence
(00:27:55) - Do we need “AGI” to automate most jobs?
(00:48:28) – Future of AI progress: deep learning + program synthesis
(01:00:40) – How Mike Knoop got nerd-sniped by ARC
(01:08:37) – Million $ ARC Prize
(01:10:33) – Resisting benchmark saturation
(01:18:08) – ARC scores on frontier vs open source models
(01:26:19) – Possible solutions to ARC Prize


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Chatted with my friend Leopold Aschenbrenner on the trillion dollar nationalized cluster, CCP espionage at AI labs, how unhobblings and scaling can lead to 2027 AGI, dangers of outsourcing clusters to Middle East, leaving OpenAI, and situational awareness.
Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. Read the full transcript here.
Follow me on Twitter for updates on future episodes. Follow Leopold on Twitter.
Timestamps
(00:00:00) – The trillion-dollar cluster and unhobbling
(00:20:31) – AI 2028: The return of history
(00:40:26) – Espionage & American AI superiority
(01:08:20) – Geopolitical implications of AI
(01:31:23) – State-led vs. private-led AI
(02:12:23) – Becoming Valedictorian of Columbia at 19
(02:30:35) – What happened at OpenAI
(02:45:11) – Accelerating AI research progress
(03:25:58) – Alignment
(03:41:26) – On Germany, and understanding foreign perspectives
(03:57:04) – Dwarkesh’s immigration story and path to the podcast
(04:07:58) – Launching an AGI hedge fund
(04:19:14) – Lessons from WWII
(04:29:08) – Coda: Frederick the Great


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Chatted with John Schulman (cofounded OpenAI and led ChatGPT creation) on how posttraining tames the shoggoth, and the nature of the progress to come...
Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. Read the full transcript here. Follow me on Twitter for updates on future episodes.
Timestamps
(00:00:00) - Pre-training, post-training, and future capabilities
(00:16:57) - Plan for AGI 2025
(00:29:19) - Teaching models to reason
(00:40:50) - The Road to ChatGPT
(00:52:13) - What makes for a good RL researcher?
(01:00:58) - Keeping humans in the loop
(01:15:15) - State of research, plateaus, and moats
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Mark Zuckerberg on:
- Llama 3
- open sourcing towards AGI
- custom silicon, synthetic data, & energy constraints on scaling
- Caesar Augustus, intelligence explosion, bioweapons, $10b models, & much more
Enjoy!
Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. Human edited transcript with helpful links here.
Timestamps
(00:00:00) - Llama 3
(00:08:32) - Coding on path to AGI
(00:25:24) - Energy bottlenecks
(00:33:20) - Is AI the most important technology ever?
(00:37:21) - Dangers of open source
(00:53:57) - Caesar Augustus and metaverse
(01:04:53) - Open sourcing the $10b model & custom silicon
(01:15:19) - Zuck as CEO of Google+
Sponsors
If you’re interested in advertising on the podcast, fill out this form.
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Had so much fun chatting with my good friends Trenton Bricken and Sholto Douglas on the podcast.
No way to summarize it, except: 
This is the best context dump out there on how LLMs are trained, what capabilities they're likely to soon have, and what exactly is going on inside them.
You would be shocked how much of what I know about this field, I've learned just from talking with them.
To the extent that you've enjoyed my other AI interviews, now you know why.
So excited to put this out. Enjoy! I certainly did :)
Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. 
There's a transcript with links to all the papers the boys were throwing down - may help you follow along.
Follow Trenton and Sholto on Twitter.
Timestamps
(00:00:00) - Long contexts
(00:16:12) - Intelligence is just associations
(00:32:35) - Intelligence explosion & great researchers
(01:06:52) - Superposition & secret communication
(01:22:34) - Agents & true reasoning
(01:34:40) - How Sholto & Trenton got into AI research
(02:07:16) - Are feature spaces the wrong way to think about intelligence?
(02:21:12) - Will interp actually work on superhuman models
(02:45:05) - Sholto’s technical challenge for the audience
(03:03:57) - Rapid fire


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