Based on my essay about AI firms.

Huge thanks to Petr and his team for bringing this to life!

Watch on YouTube.

Thanks to Google for sponsoring. We used their Veo 2 model to make this entire video—it generated everything from the photorealistic humans to the claymation octopuses. If you’re a Gemini Advanced user, you can try Veo 2 now in the Gemini app. Just select Veo 2 in the dropdown, and type your video idea in the prompt bar. Get started today by going to gemini.google.com.

To sponsor a future episode, visit dwarkesh.com/advertise.

Zuck on:

* Llama 4, benchmark gaming

* Intelligence explosion, business models for AGI

* DeepSeek/China, export controls, & Trump

* Orion glasses, AI relationships, and preventing reward-hacking from our tech.

Watch on Youtube; listen on Apple Podcasts and Spotify.

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SPONSORS

* Scale is building the infrastructure for safer, smarter AI. Scale’s Data Foundry gives major AI labs access to high-quality data to fuel post-training, while their public leaderboards help assess model capabilities. They also just released Scale Evaluation, a new tool that diagnoses model limitations. If you’re an AI researcher or engineer, learn how Scale can help you push the frontier at scale.com/dwarkesh.

* WorkOS Radar protects your product against bots, fraud, and abuse. Radar uses 80+ signals to identify and block common threats and harmful behavior. Join companies like Cursor, Perplexity, and OpenAI that have eliminated costly free-tier abuse by visiting workos.com/radar.

* Lambda is THE cloud for AI developers, with over 50,000 NVIDIA GPUs ready to go for startups, enterprises, and hyperscalers. By focusing exclusively on AI, Lambda provides cost-effective compute supported by true experts, including a serverless API serving top open-source models like Llama 4 or DeepSeek V3-0324 without rate limits, and available for a free trial at lambda.ai/dwarkesh.

To sponsor a future episode, visit dwarkesh.com/p/advertise.

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TIMESTAMPS

(00:00:00) – How Llama 4 compares to other models

(00:11:34) – Intelligence explosion

(00:26:36) – AI friends, therapists & girlfriends

(00:35:10) – DeepSeek & China

(00:39:49) – Open source AI

(00:54:15) – Monetizing AGI

(00:58:32) – The role of a CEO

(01:02:04) – Is big tech aligning with Trump?

(01:07:10) – 100x productivity

800 years before the Black Death, the very same bacteria ravaged Rome, killing 60%+ of the population in many areas.

Also, back-to-back volcanic eruptions caused a mini Ice Age, leaving Rome devastated by famine and disease.

I chatted with historian Kyle Harper about this and much else:

* Rome as a massive slave society

* Why humans are more disease-prone than other animals

* How agriculture made us physically smaller (Caesar at 5'5" was considered tall)

Watch on Youtube; listen on Apple Podcasts or Spotify.

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SPONSORS

* WorkOS makes it easy to become enterprise-ready. They have APIs for all the most common enterprise requirements—things like authentication, permissions, and encryption—so you can quickly plug them in and get back to building your core product. If you want to make your product enterprise-ready, join companies like Cursor, Perplexity and OpenAI, and head to workos.com.

* Scale’s Data Foundry gives major AI labs access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you’re an AI researcher or engineer, learn how Scale’s Data Foundry and research lab, SEAL, can help you go beyond the current frontier of capabilities at scale.com/dwarkesh

To sponsor a future episode, visit dwarkesh.com/advertise.

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KYLE'S BOOKS

* The Fate of Rome: Climate, Disease, and the End of an Empire

* Plagues upon the Earth: Disease and the Course of Human History

* Slavery in the Late Roman World, AD 275-425

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TIMESTAMPS

(00:00:00) - Plague's impact on Rome's collapse

(00:06:24) - Rome's little Ice Age

(00:11:51) - Why did progress stall in Rome's Golden Age?

(00:23:55) - Slavery in Rome

(00:36:22) - Was agriculture a mistake?

(00:47:42) - Disease's impact on cognitive function

(00:59:46) - Plague in India and Central Asia

(01:05:16) - The next pandemic

(01:16:48) - How Kyle uses LLMs

(01:18:51) - De-extinction of lost species

Ege Erdil and Tamay Besiroglu have 2045+ timelines, think the whole "alignment" framing is wrong, don't think an intelligence explosion is plausible, but are convinced we'll see explosive economic growth (economy literally doubling every year or two).

This discussion offers a totally different scenario than my recent interview with Scott and Daniel.

Ege and Tamay are the co-founders of Mechanize (disclosure - I’m an angel investor), a startup dedicated to fully automating work. Before founding Mechanize, Ege and Tamay worked on AI forecasts at Epoch AI.

Watch on Youtube; listen on Apple Podcasts or Spotify.

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Sponsors

* WorkOS makes it easy to become enterprise-ready. With simple APIs for essential enterprise features like SSO and SCIM, WorkOS helps companies like Vercel, Plaid, and OpenAI meet the requirements of their biggest customers. To learn more about how they can help you do the same, visit workos.com

* Scale’s Data Foundry gives major AI labs access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you’re an AI researcher or engineer, learn about how Scale’s Data Foundry and research lab, SEAL, can help you go beyond the current frontier at scale.com/dwarkesh

* Google's Gemini Pro 2.5 is the model we use the most at Dwarkesh Podcast: it helps us generate transcripts, identify interesting clips, and code up new tools. If you want to try it for yourself, it's now available in Preview with higher rate limits! Start building with it today at aistudio.google.com.

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Timestamps

(00:00:00) - AGI will take another 3 decades

(00:22:27) - Even reasoning models lack animal intelligence 

(00:45:04) - Intelligence explosion

(01:00:57) - Ege & Tamay’s story

(01:06:24) - Explosive economic growth

(01:33:00) - Will there be a separate AI economy?

(01:47:08) - Can we predictably influence the future?

(02:19:48) - Arms race dynamic

(02:29:48) - Is superintelligence a real thing?

(02:35:45) - Reasons not to expect explosive growth

(02:49:00) - Fully automated firms

(02:54:43) - Will central planning work after AGI?

(02:58:20) - Career advice

Scott and Daniel break down every month from now until the 2027 intelligence explosion.

Scott Alexander is author of the highly influential blogs Slate Star Codex and Astral Codex Ten. Daniel Kokotajlo resigned from OpenAI in 2024, rejecting a non-disparagement clause and risking millions in equity to speak out about AI safety.

We discuss misaligned hive minds, Xi and Trump waking up, and automated Ilyas researching AI progress.

I came in skeptical, but I learned a tremendous amount by bouncing my objections off of them. I highly recommend checking out their new scenario planning document, AI 2027

Watch on Youtube; listen on Apple Podcasts or Spotify.

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Sponsors

* WorkOS helps today’s top AI companies get enterprise-ready. OpenAI, Cursor, Perplexity, Anthropic and hundreds more use WorkOS to quickly integrate features required by enterprise buyers. To learn more about how you can make the leap to enterprise, visit workos.com

* Jane Street likes to know what's going on inside the neural nets they use. They just released a black-box challenge for Dwarkesh listeners, and I had a blast trying it out. See if you have the skills to crack it at janestreet.com/dwarkesh

* Scale’s Data Foundry gives major AI labs access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you’re an AI researcher or engineer, learn about how Scale’s Data Foundry and research lab, SEAL, can help you go beyond the current frontier at scale.com/dwarkesh

To sponsor a future episode, visit dwarkesh.com/advertise.

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Timestamps

(00:00:00) - AI 2027

(00:06:56) - Forecasting 2025 and 2026

(00:14:41) - Why LLMs aren't making discoveries

(00:24:33) - Debating intelligence explosion

(00:49:45) - Can superintelligence actually transform science?

(01:16:54) - Cultural evolution vs superintelligence

(01:24:05) - Mid-2027 branch point

(01:32:30) - Race with China

(01:44:47) - Nationalization vs private anarchy

(02:03:22) - Misalignment

(02:14:52) - UBI, AI advisors, & human future

(02:23:00) - Factory farming for digital minds

(02:26:52) - Daniel leaving OpenAI

(02:35:15) - Scott's blogging advice

I recorded an AMA! I had a blast chatting with my friends Trenton Bricken and Sholto Douglas. We discussed my new book, career advice given AGI, how I pick guests, how I research for the show, and some other nonsense.

My book, “The Scaling Era: An Oral History of AI, 2019-2025” is available in digital format now. Preorders for the print version are also open!

Watch on YouTube; listen on Apple Podcasts or Spotify.

Timestamps

(0:00:00) - Book launch announcement

(0:04:57) - AI models not making connections across fields

(0:10:52) - Career advice given AGI

(0:15:20) - Guest selection criteria

(0:17:19) - Choosing to pursue the podcast long-term

(0:25:12) - Reading habits

(0:31:10) - Beard deepdive

(0:33:02) - Who is best suited for running an AI lab?

(0:35:16) - Preparing for fast AGI timelines

(0:40:50) - Growing the podcast

Humans have not succeeded because of our raw intelligence.

Marooned European explorers regularly starved to death in areas where foragers thrived for 1000s of years.

I’ve always found this cultural evolution deeply mysterious.

How do you discover the 10 steps for processing cassava so it won’t give you cyanide poisoning simply by trial and error?

Has the human brain declined in size over the last 10,000 years because we outsourced cultural evolution to a larger collective brain?

The most interesting part of the podcast is Henrich’s explanation of how the Catholic Church unintentionally instigated the Industrial Revolution through the dismantling of intensive kinship systems in medieval Europe.

Watch on Youtube; listen on Apple Podcasts or Spotify.

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Sponsors

Scale partners with major AI labs like Meta, Google Deepmind, and OpenAI. Through Scale’s Data Foundry, labs get access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you’re an AI researcher or engineer, learn about how Scale’s Data Foundry and research lab, SEAL, can help you go beyond the current frontier at scale.com/dwarkesh.

To sponsor a future episode, visit dwarkesh.com/p/advertise.

----------

Joseph’s books

The WEIRDest People in the World

The Secret of Our Success

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Timestamps

(0:00:00) - Humans didn’t succeed because of raw IQ

(0:09:27) - How cultural evolution works

(0:20:48) - Why is human brain size declining?

(0:32:00) - Will AGI have superhuman cultural learning?

(0:42:34) - Why Industrial Revolution happened in Europe

(0:55:30) - Why China, Rome, India got left behind

(1:21:09) - Loss of cultural variance in modern world

(1:31:20) - Is individual genius real?

(1:43:49) - IQ and collective brains

I’m so excited with how this visualization of Notes on China turned out. Petr, thank you for such beautiful watercolor artwork. More to come!

Watch on YouTube.

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Timestamps

(0:00:00) - Intro

(0:00:32) - Scale

(0:05:50) - Vibes

(0:11:14) - Youngsters

(0:14:27) - Tech & AI

(0:15:47) - Hearts & Minds

(0:17:07) - On Travel

Satya Nadella on:

Why he doesn’t believe in AGI but does believe in 10% economic growth;

Microsoft’s new topological qubit breakthrough and gaming world models;

Whether Office commoditizes LLMs or the other way around.

Watch on Youtube; listen on Apple Podcasts or Spotify.

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Sponsors

Scale partners with major AI labs like Meta, Google Deepmind, and OpenAI. Through Scale’s Data Foundry, labs get access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you’re an AI researcher or engineer, learn about how Scale’s Data Foundry and research lab, SEAL, can help you go beyond the current frontier at scale.com/dwarkesh

Linear's project management tools have become the default choice for product teams at companies like Ramp, CashApp, OpenAI, and Scale. These teams use Linear so they can stay close to their products and move fast. If you’re curious why so many companies are making the switch, visit linear.app/dwarkesh

To sponsor a future episode, visit dwarkeshpatel.com/p/advertise.

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Timestamps

(0:00:00) - Intro

(0:05:04) - AI won't be winner-take-all

(0:15:18) - World economy growing by 10%

(0:21:39) - Decreasing price of intelligence

(0:30:19) - Quantum breakthrough

(0:42:51) - How Muse will change gaming

(0:49:51) - Legal barriers to AI

(0:55:46) - Getting AGI safety right

(1:04:59) - 34 years at Microsoft

(1:10:46) - Does Satya Nadella believe in AGI?

This week I welcome on the show two of the most important technologists ever, in any field.

Jeff Dean is Google's Chief Scientist, and through 25 years at the company, has worked on basically the most transformative systems in modern computing: from MapReduce, BigTable, Tensorflow, AlphaChip, to Gemini.

Noam Shazeer invented or co-invented all the main architectures and techniques that are used for modern LLMs: from the Transformer itself, to Mixture of Experts, to Mesh Tensorflow, to Gemini and many other things.

We talk about their 25 years at Google, going from PageRank to MapReduce to the Transformer to MoEs to AlphaChip – and maybe soon to ASI.

My favorite part was Jeff's vision for Pathways, Google’s grand plan for a mutually-reinforcing loop of hardware and algorithmic design and for going past autoregression. That culminates in us imagining *all* of Google-the-company, going through one huge MoE model.

And Noam just bites every bullet: 100x world GDP soon; let’s get a million automated researchers running in the Google datacenter; living to see the year 3000.Watch on Youtube; listen on Apple Podcasts or Spotify.

Sponsors

Scale partners with major AI labs like Meta, Google Deepmind, and OpenAI. Through Scale’s Data Foundry, labs get access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you’re an AI researcher or engineer, learn about how Scale’s Data Foundry and research lab, SEAL, can help you go beyond the current frontier at scale.com/dwarkesh

Curious how Jane Street teaches their new traders? They use Figgie, a rapid-fire card game that simulates the most exciting parts of markets and trading. It’s become so popular that Jane Street hosts an inter-office Figgie championship every year. Download from the app store or play on your desktop at figgie.com

Meter wants to radically improve the digital world we take for granted. They’re developing a foundation model that automates network management end-to-end. To do this, they just announced a long-term partnership with Microsoft for tens of thousands of GPUs, and they’re recruiting a world class AI research team. To learn more, go to meter.com/dwarkesh

To sponsor a future episode, visit dwarkeshpatel.com/p/advertise

Timestamps

00:00:00 - Intro

00:02:44 - Joining Google in 1999

00:05:36 - Future of Moore's Law

00:10:21 - Future TPUs

00:13:13 - Jeff’s undergrad thesis: parallel backprop

00:15:10 - LLMs in 2007

00:23:07 - “Holy s**t” moments

00:29:46 - AI fulfills Google’s original mission

00:34:19 - Doing Search in-context

00:38:32 - The internal coding model

00:39:49 - What will 2027 models do?

00:46:00 - A new architecture every day?

00:49:21 - Automated chip design and intelligence explosion

00:57:31 - Future of inference scaling

01:03:56 - Already doing multi-datacenter runs

01:22:33 - Debugging at scale

01:26:05 - Fast takeoff and superalignment

01:34:40 - A million evil Jeff Deans

01:38:16 - Fun times at Google

01:41:50 - World compute demand in 2030

01:48:21 - Getting back to modularity

01:59:13 - Keeping a giga-MoE in-memory

02:04:09 - All of Google in one model

02:12:43 - What’s missing from distillation

02:18:03 - Open research, pros and cons

02:24:54 - Going the distance

Third and final episode in the Paine trilogy!

Chinese history is full of warlords constantly challenging the capital. How could Mao not only stay in power for decades, but not even face any insurgency?

And how did Mao go from military genius to peacetime disaster - the patriotic hero who inflicted history’s worst human catastrophe on China? How can someone shrewd enough to win a civil war outnumbered 5 to 1 decide "let's have peasants make iron in their backyards" and "let's kill all the birds"?

In her lecture and our Q&A, we cover the first nationwide famine in Chinese history; Mao's lasting influence on other insurgents; broken promises to minorities and peasantry; and what Taiwan means.

Thanks so much to @Substack for running this in-person event!

Note that Sarah is doing an AMA over the next couple days on Youtube; see the pinned comment.

Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform.

Sponsor

Today’s episode is brought to you by Scale AI. Scale partners with the U.S. government to fuel America’s AI advantage through their data foundry. Scale recently introduced Defense Llama, Scale's latest solution available for military personnel. With Defense Llama, military personnel can harness the power of AI to plan military or intelligence operations and understand adversary vulnerabilities.

If you’re interested in learning more on how Scale powers frontier AI capabilities, go to https://scale.com/dwarkesh.