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The Dario Amodei interview. 0:00:00 - What exactly are we scaling? 0:12:36 - Is diffusion cope? 0:29:42 - Is continual learning necessary? 0:46:20 - If AGI is imminent, why not buy more compute? 0:58:49 - How will AI labs actually make profit? 1:31:19 - Will regulations destroy the boons... show more

Dwarkesh Patel

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2,056,457 Aufrufe • vor 4 Monaten •via X (Twitter)

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The Jensen Huang episode. 0:00:00 – Is Nvidia’s biggest moat its grip on scarce supply chains? 0:16:25 – Will TPUs break Nvidia’s hold on AI compute? 0:41:06 – Why doesn’t Nvidia become a hyperscaler? 0:57:36 – Should we be selling AI chips to China? 1:35:06 – Why doesn’t Nvidia make multiple different chip architectures? Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

The Jensen Huang episode. 0:00:00 – Is Nvidia’s biggest moat its grip on scarce supply chains? 0:16:25 – Will TPUs break Nvidia’s hold on AI compute? 0:41:06 – Why doesn’t Nvidia become a hyperscaler? 0:57:36 – Should we be selling AI chips to China? 1:35:06 – Why doesn’t Nvidia make multiple different chip architectures? Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

Dwarkesh Patel

6,197,096 Aufrufe • vor 2 Monaten

The Andrej Karpathy interview 0:00:00 – AGI is still a decade away 0:30:33 – LLM cognitive deficits 0:40:53 – RL is terrible 0:50:26 – How do humans learn? 1:07:13 – AGI will blend into 2% GDP growth 1:18:24 – ASI 1:33:38 – Evolution of intelligence & culture 1:43:43 - Why self driving took so long 1:57:08 - Future of education Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

The Andrej Karpathy interview 0:00:00 – AGI is still a decade away 0:30:33 – LLM cognitive deficits 0:40:53 – RL is terrible 0:50:26 – How do humans learn? 1:07:13 – AGI will blend into 2% GDP growth 1:18:24 – ASI 1:33:38 – Evolution of intelligence & culture 1:43:43 - Why self driving took so long 1:57:08 - Future of education Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

Dwarkesh Patel

10,752,563 Aufrufe • vor 8 Monaten

The Ilya Sutskever episode 0:00:00 – Explaining model jaggedness 0:09:39 - Emotions and value functions 0:18:49 – What are we scaling? 0:25:13 – Why humans generalize better than models 0:35:45 – Straight-shotting superintelligence 0:46:47 – SSI’s model will learn from deployment 0:55:07 – Alignment 1:18:13 – “We are squarely an age of research company” 1:29:23 – Self-play and multi-agent 1:32:42 – Research taste Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify. Enjoy!

The Ilya Sutskever episode 0:00:00 – Explaining model jaggedness 0:09:39 - Emotions and value functions 0:18:49 – What are we scaling? 0:25:13 – Why humans generalize better than models 0:35:45 – Straight-shotting superintelligence 0:46:47 – SSI’s model will learn from deployment 0:55:07 – Alignment 1:18:13 – “We are squarely an age of research company” 1:29:23 – Self-play and multi-agent 1:32:42 – Research taste Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify. Enjoy!

Dwarkesh Patel

4,125,477 Aufrufe • vor 7 Monaten

.Satya Nadella gave me and Dylan Patel an exclusive tour of Fairwater 2, the most powerful AI datacenter in the world. We then chatted through Satya's vision for Microsoft in a world with AGI. 0:00:00 - Fairwater 2 0:04:15 - Business models for AGI 0:13:42 - Copilot 0:20:56 - Whose margins will expand most? 0:37:12 - MAI 0:48:42 - The hyperscale business 1:03:39 - In-house chip & OpenAI partnership 1:10:30 - The CAPEX explosion 1:16:01 - Will the world trust US companies to lead AI? Look up Dwarkesh Podcast on Youtube, Apple Podcasts or Spotify to tune in.

.Satya Nadella gave me and Dylan Patel an exclusive tour of Fairwater 2, the most powerful AI datacenter in the world. We then chatted through Satya's vision for Microsoft in a world with AGI. 0:00:00 - Fairwater 2 0:04:15 - Business models for AGI 0:13:42 - Copilot 0:20:56 - Whose margins will expand most? 0:37:12 - MAI 0:48:42 - The hyperscale business 1:03:39 - In-house chip & OpenAI partnership 1:10:30 - The CAPEX explosion 1:16:01 - Will the world trust US companies to lead AI? Look up Dwarkesh Podcast on Youtube, Apple Podcasts or Spotify to tune in.

Dwarkesh Patel

1,894,605 Aufrufe • vor 7 Monaten

Episode w Dylan Patel and Asianometry out! A bonanza on how the semiconductor industry actually works. & what Xi could do if he becomes scaling pilled, how we can train models with 10,000x GPT-4's compute by end of decade, & much more. This one is very fun. Enjoy! Links below. 0:00:00 – Xi’s path to AGI 0:05:05 – Liang Mong Song 0:09:10 – How semiconductors get better 0:12:01 – China can centralize compute 0:19:35 – Export controls & sanctions 0:33:45 – Huawei’s intense culture 0:39:45 – Why the semiconductor industry is so stratified 0:41:50 – N2 should not exist 0:46:47 – Taiwan invasion hypothetical 0:50:15 – Mind-boggling complexity of semiconductors 1:00:06 – Chip architecture design 1:05:29 – Architectures lead to different AI models? China vs. US 1:11:06 – Being head of compute at an AI lab 1:17:17 – Scaling costs and power demand 1:37:59 – Are we financing an AI bubble?

Episode w Dylan Patel and Asianometry out! A bonanza on how the semiconductor industry actually works. & what Xi could do if he becomes scaling pilled, how we can train models with 10,000x GPT-4's compute by end of decade, & much more. This one is very fun. Enjoy! Links below. 0:00:00 – Xi’s path to AGI 0:05:05 – Liang Mong Song 0:09:10 – How semiconductors get better 0:12:01 – China can centralize compute 0:19:35 – Export controls & sanctions 0:33:45 – Huawei’s intense culture 0:39:45 – Why the semiconductor industry is so stratified 0:41:50 – N2 should not exist 0:46:47 – Taiwan invasion hypothetical 0:50:15 – Mind-boggling complexity of semiconductors 1:00:06 – Chip architecture design 1:05:29 – Architectures lead to different AI models? China vs. US 1:11:06 – Being head of compute at an AI lab 1:17:17 – Scaling costs and power demand 1:37:59 – Are we financing an AI bubble?

Dwarkesh Patel

260,187 Aufrufe • vor 1 Jahr

.Dylan Patel gives a deep dive on the 3 big bottlenecks to scaling AI compute: logic, memory, and power. And walks through the economics of labs, hyperscalers, foundries, and fab equipment manufacturers. Learned a ton about every single level of the stack. 0:00:00 – Why an H100 is worth more today than 3 years ago 0:24:52 – Nvidia secured TSMC allocation early; Google is getting squeezed 0:34:34 – ASML will be the #1 constraint for AI compute scaling by 2030 0:56:06 – Can’t we just use TSMC’s older fabs? 1:05:56 – When will China outscale the West in semis? 1:16:20 – The enormous incoming memory crunch 1:42:53 – Scaling power in the US will not be a problem 1:55:03 – Space GPUs aren't happening this decade 2:14:26 – Why aren’t more hedge funds making the AGI trade? 2:18:49 – Will TSMC kick Apple out from N2? 2:24:35 – Robots and Taiwan risk Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify. Enjoy!

.Dylan Patel gives a deep dive on the 3 big bottlenecks to scaling AI compute: logic, memory, and power. And walks through the economics of labs, hyperscalers, foundries, and fab equipment manufacturers. Learned a ton about every single level of the stack. 0:00:00 – Why an H100 is worth more today than 3 years ago 0:24:52 – Nvidia secured TSMC allocation early; Google is getting squeezed 0:34:34 – ASML will be the #1 constraint for AI compute scaling by 2030 0:56:06 – Can’t we just use TSMC’s older fabs? 1:05:56 – When will China outscale the West in semis? 1:16:20 – The enormous incoming memory crunch 1:42:53 – Scaling power in the US will not be a problem 1:55:03 – Space GPUs aren't happening this decade 2:14:26 – Why aren’t more hedge funds making the AGI trade? 2:18:49 – Will TSMC kick Apple out from N2? 2:24:35 – Robots and Taiwan risk Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify. Enjoy!

Dwarkesh Patel

489,347 Aufrufe • vor 3 Monaten

The Sam+Greg episode. 0:00:00 - The evolution their relationship 0:25:42 - The personal AGI that knows you 0:35:40 - Three futures. Ten trillionaires 0:44:18 - America's hardware problem 0:49:22 - Greg takes the product reins 0:56:00 - Why Sora got cut 1:09:52 - How the AI drama got this toxic 1:11:36 - Sam's worst week 1:17:01 - The Elon Musk trial Sam wants to have Find the Core Memory Podcast on YouTube, Apple Podcasts, Spotify, etc. Come to us, friends.

The Sam+Greg episode. 0:00:00 - The evolution their relationship 0:25:42 - The personal AGI that knows you 0:35:40 - Three futures. Ten trillionaires 0:44:18 - America's hardware problem 0:49:22 - Greg takes the product reins 0:56:00 - Why Sora got cut 1:09:52 - How the AI drama got this toxic 1:11:36 - Sam's worst week 1:17:01 - The Elon Musk trial Sam wants to have Find the Core Memory Podcast on YouTube, Apple Podcasts, Spotify, etc. Come to us, friends.

Ashlee Vance

102,230 Aufrufe • vor 2 Monaten

New episode w Adam Marblestone on what the brain's secret sauce is: how do we learn so much from so little? Also, the answer to Ilya’s question: how does the genome encode desires for high level concepts that are only seen during lifetime? Turns out, they’re deeply connected questions. Timestamps 0:00:00 – The brain’s secret sauce is the reward functions, not the architecture 0:22:20 – What the genome actually encodes 0:42:42 – What kind of RL is the brain doing? 0:50:31 – Is biological hardware a limitation or an advantage? 1:03:59 – Why we need to map the human brain 1:23:28 – What value will automating math have? 1:38:18 – Architecture of the brain Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

New episode w Adam Marblestone on what the brain's secret sauce is: how do we learn so much from so little? Also, the answer to Ilya’s question: how does the genome encode desires for high level concepts that are only seen during lifetime? Turns out, they’re deeply connected questions. Timestamps 0:00:00 – The brain’s secret sauce is the reward functions, not the architecture 0:22:20 – What the genome actually encodes 0:42:42 – What kind of RL is the brain doing? 0:50:31 – Is biological hardware a limitation or an advantage? 1:03:59 – Why we need to map the human brain 1:23:28 – What value will automating math have? 1:38:18 – Architecture of the brain Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

Dwarkesh Patel

746,125 Aufrufe • vor 6 Monaten

New episode w Lewis Bollard - a deep dive on the surprising economics of the meat industry. 0:00:00 – The astonishing efficiency of factory farming 0:07:18 – It was a mistake making this about diet 0:09:54 – Tech that’s sparing 100s of millions of animals/year 0:16:16 – Brainless chickens and higher welfare breeds 0:28:21 – $1 can prevent 10 years of animal suffering 0:37:26 – The situation in China and the developing world 0:41:41 – How the meat lobby got a lock on Congress 0:53:23 – Business structure of the meat industry 0:57:42 – Corporate campaigns are underrated Available on YouTube, Apple Podcasts, Spotify, etc (look up Dwarkesh Podcast).

New episode w Lewis Bollard - a deep dive on the surprising economics of the meat industry. 0:00:00 – The astonishing efficiency of factory farming 0:07:18 – It was a mistake making this about diet 0:09:54 – Tech that’s sparing 100s of millions of animals/year 0:16:16 – Brainless chickens and higher welfare breeds 0:28:21 – $1 can prevent 10 years of animal suffering 0:37:26 – The situation in China and the developing world 0:41:41 – How the meat lobby got a lock on Congress 0:53:23 – Business structure of the meat industry 0:57:42 – Corporate campaigns are underrated Available on YouTube, Apple Podcasts, Spotify, etc (look up Dwarkesh Podcast).

Dwarkesh Patel

240,050 Aufrufe • vor 11 Monaten

I filmed a video version of my post 'Why I Don’t Think AGI Is Right Around The Corner' so I could show it to my YouTube audience. You can watch it too I guess. 0:00:00 - Continual Learning 0:08:06 - Computer Use 0:11:27 - Reasoning 0:12:45 - So what are my predictions?

I filmed a video version of my post 'Why I Don’t Think AGI Is Right Around The Corner' so I could show it to my YouTube audience. You can watch it too I guess. 0:00:00 - Continual Learning 0:08:06 - Computer Use 0:11:27 - Reasoning 0:12:45 - So what are my predictions?

Dwarkesh Patel

113,781 Aufrufe • vor 11 Monaten

How Russia derailed China’s rise for over a century: new lecture and Q&A w Sarah Paine. IMO the Chinese Civil War is 1 of the top 3 most important events of the 20th century. To understand why it transpired as it did, you need to understand Stalin’s role in the whole thing. Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify to catch it there. Enjoy! 0:00:00 – How Russia took advantage of China's weakness 0:23:46 – After Stalin, China's rise 0:34:39 – Russian imperialism 0:46:10 – China and Russia's existential problems 1:05:42 – Q&A: Sino-Soviet split 1:23:29 – Stalin's lessons from WW2

How Russia derailed China’s rise for over a century: new lecture and Q&A w Sarah Paine. IMO the Chinese Civil War is 1 of the top 3 most important events of the 20th century. To understand why it transpired as it did, you need to understand Stalin’s role in the whole thing. Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify to catch it there. Enjoy! 0:00:00 – How Russia took advantage of China's weakness 0:23:46 – After Stalin, China's rise 0:34:39 – Russian imperialism 0:46:10 – China and Russia's existential problems 1:05:42 – Q&A: Sino-Soviet split 1:23:29 – Stalin's lessons from WW2

Dwarkesh Patel

57,358 Aufrufe • vor 8 Monaten

Our new podcast on evals, with Max Niederman, Ege Erdil, and Stephen Yang. 0:00:00 – What's an eval, and how's it different from an RL environment? 0:19:33 – Why are models bad at building an emulator when the task is fully verifiable? 0:42:00 – How does training on bad data teach models to write terrible code? 1:04:00 – Why is continual learning still so bad? 2:25:24 – Why haven't software engineers been replaced when coding is basically solved? Listen to the Mechanize Podcast on YouTube, Spotify, etc. Enjoy!

Our new podcast on evals, with Max Niederman, Ege Erdil, and Stephen Yang. 0:00:00 – What's an eval, and how's it different from an RL environment? 0:19:33 – Why are models bad at building an emulator when the task is fully verifiable? 0:42:00 – How does training on bad data teach models to write terrible code? 1:04:00 – Why is continual learning still so bad? 2:25:24 – Why haven't software engineers been replaced when coding is basically solved? Listen to the Mechanize Podcast on YouTube, Spotify, etc. Enjoy!

Mechanize

38,018 Aufrufe • vor 21 Tagen

It was an honour to host the first ever public dialogue between David Deutsch (David Deutsch) and Steven Pinker (Steven Pinker). They are longstanding admirers of each other's work. I view Steve's defence of the Enlightenment as more empirical, whereas David's is built more on first principles. But beyond their shared rational optimism, what else do they agree – or disagree – about? Topics we discuss are well captured by the timestamps below. Links to YouTube, transcript, Apple Podcasts, & Spotify in tweet below. Enjoy! Timestamps: (0:00:00) - Introduction (0:03:09) - Is AGI even possible? (0:10:17) - Scientific method will constrain runaway superintelligence (0:11:56) - Does AGI need agency to be creative? (0:28:31) - Will AGIs be sentient? (0:37:06) - AGI & AI safety (0:47:44) - P(doom) & subjective probabilities (0:53:21) - Prediction markets (1:01:43) - Universal explainers & The Language Instinct (1:04:43) - Universal explainers & heritability of behavioural traits (1:27:59) - Differential technological development (1:36:09) - What explains the Great Stagnation? (1:46:13) - Should presumed physical limits to growth make us pessimistic?

It was an honour to host the first ever public dialogue between David Deutsch (David Deutsch) and Steven Pinker (Steven Pinker). They are longstanding admirers of each other's work. I view Steve's defence of the Enlightenment as more empirical, whereas David's is built more on first principles. But beyond their shared rational optimism, what else do they agree – or disagree – about? Topics we discuss are well captured by the timestamps below. Links to YouTube, transcript, Apple Podcasts, & Spotify in tweet below. Enjoy! Timestamps: (0:00:00) - Introduction (0:03:09) - Is AGI even possible? (0:10:17) - Scientific method will constrain runaway superintelligence (0:11:56) - Does AGI need agency to be creative? (0:28:31) - Will AGIs be sentient? (0:37:06) - AGI & AI safety (0:47:44) - P(doom) & subjective probabilities (0:53:21) - Prediction markets (1:01:43) - Universal explainers & The Language Instinct (1:04:43) - Universal explainers & heritability of behavioural traits (1:27:59) - Differential technological development (1:36:09) - What explains the Great Stagnation? (1:46:13) - Should presumed physical limits to growth make us pessimistic?

Joseph Noel Walker

111,747 Aufrufe • vor 2 Jahren

.Casey Handmer on how to feed the AIs. 0:00:00 – Why doesn’t China win by default 0:08:28 – Why hyperscalers choose natural gas over solar 0:18:01 – Solar's astonishing learning rates 0:27:02 – How to build 50,000 acre solar-powered data centers 0:40:24 – Environmental regulations blocking clean energy 0:44:04 – Batteries replacing the grid 0:49:14 – GDP is broken, AGI's true value must be measured in total energy use 0:58:45 – Silicon wafers in space with one mind each Available on Apple Podcasts, Spotify, YouTube, etc. Enjoy!

.Casey Handmer on how to feed the AIs. 0:00:00 – Why doesn’t China win by default 0:08:28 – Why hyperscalers choose natural gas over solar 0:18:01 – Solar's astonishing learning rates 0:27:02 – How to build 50,000 acre solar-powered data centers 0:40:24 – Environmental regulations blocking clean energy 0:44:04 – Batteries replacing the grid 0:49:14 – GDP is broken, AGI's true value must be measured in total energy use 0:58:45 – Silicon wafers in space with one mind each Available on Apple Podcasts, Spotify, YouTube, etc. Enjoy!

Dwarkesh Patel

1,408,124 Aufrufe • vor 10 Monaten

The 𝔊𝔴𝔢𝔯𝔫 interview. 0:00:00 – Anonymity 0:01:09 – Automating Steve Jobs 0:04:38 – Isaac Newton's theory of progress 0:06:36 – Grand theory of intelligence 0:10:39 – Seeing scaling early 0:21:04 – AGI Timelines 0:22:54 – What to do in remaining 3 years until AGI 0:26:29 – Influencing the shoggoth with writing 0:30:50 – Human vs artificial intelligence 0:33:52 – Rabbit holes 0:38:48 – Hearing impairment 0:43:00 – Wikipedia editing 0:47:43 – Gwern dot net 0:50:20 – Counterfactual careers 0:54:30 – Borges & literature 1:01:32 – Gwern's process 1:19:17 - Gwern's finances 1:25:05 - Random

The 𝔊𝔴𝔢𝔯𝔫 interview. 0:00:00 – Anonymity 0:01:09 – Automating Steve Jobs 0:04:38 – Isaac Newton's theory of progress 0:06:36 – Grand theory of intelligence 0:10:39 – Seeing scaling early 0:21:04 – AGI Timelines 0:22:54 – What to do in remaining 3 years until AGI 0:26:29 – Influencing the shoggoth with writing 0:30:50 – Human vs artificial intelligence 0:33:52 – Rabbit holes 0:38:48 – Hearing impairment 0:43:00 – Wikipedia editing 0:47:43 – Gwern dot net 0:50:20 – Counterfactual careers 0:54:30 – Borges & literature 1:01:32 – Gwern's process 1:19:17 - Gwern's finances 1:25:05 - Random

Dwarkesh Patel

586,466 Aufrufe • vor 1 Jahr

New blackboard lecture w Reiner Pope How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. 0:00:00 – Building a multiply-accumulate from logic gates 0:16:20 – Muxes and the cost of data movement 0:25:59 – How systolic arrays work 0:39:00 – Clock cycles and pipeline registers 0:51:40 – FPGAs vs ASICs 1:03:14 – Cache vs scratchpad 1:07:16 – Why CPU cores are much bigger than GPU cores 1:11:49 – Brains vs chips 1:15:22 – A GPU is just a bunch of tiny TPUs Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!

New blackboard lecture w Reiner Pope How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. 0:00:00 – Building a multiply-accumulate from logic gates 0:16:20 – Muxes and the cost of data movement 0:25:59 – How systolic arrays work 0:39:00 – Clock cycles and pipeline registers 0:51:40 – FPGAs vs ASICs 1:03:14 – Cache vs scratchpad 1:07:16 – Why CPU cores are much bigger than GPU cores 1:11:49 – Brains vs chips 1:15:22 – A GPU is just a bunch of tiny TPUs Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!

Dwarkesh Patel

931,823 Aufrufe • vor 1 Monat

Shattered Souls 0:00:00 Shattered Souls 0:03:50 Unfolding on its Own Time 0:08:39 Pocket 0:12:42 Boy with a Green Tattoo= 0:16:01 Wizard of the Wild 0:20:22 The Art of Being 0:23:40 Rolling with the River 0:27:06 Once 0:31:12 Patagonia 0:36:24 Carousel Ride 0:40:41 Funkmaster Flex 0:44:25 Logical Tina 0:47:55 Don’t Know if I’ll Make it Back 0:51:40 A Beautiful Solo 0:56:18 Irish Drum and Bass 1:00:46 Unbreakable Decree 1:04:37 When Life Gives You Lemons Make Lemonade 1:08:53 Thoughts 1:13:09 Beyond Desire

Shattered Souls 0:00:00 Shattered Souls 0:03:50 Unfolding on its Own Time 0:08:39 Pocket 0:12:42 Boy with a Green Tattoo= 0:16:01 Wizard of the Wild 0:20:22 The Art of Being 0:23:40 Rolling with the River 0:27:06 Once 0:31:12 Patagonia 0:36:24 Carousel Ride 0:40:41 Funkmaster Flex 0:44:25 Logical Tina 0:47:55 Don’t Know if I’ll Make it Back 0:51:40 A Beautiful Solo 0:56:18 Irish Drum and Bass 1:00:46 Unbreakable Decree 1:04:37 When Life Gives You Lemons Make Lemonade 1:08:53 Thoughts 1:13:09 Beyond Desire

JACOB HADES

750,939 Aufrufe • vor 2 Jahren

Always so much fun to chat with Grant Sanderson AI has been making much faster progress in math than in other fields. As a result, mathematics is showing us, very concretely, what AI progress in other fields will look like. Even within mathematics, there's a jagged landscape. What does it look like? What is the nature of the most important conceptual breakthroughs in the history of mathematics, and how different are they from what AIs are currently able to do? Does AI (on net) increase or decrease human understanding of the field? How big is the overhang from having AIs systematically try to connect ideas already in the literature? And what advice does Grant have for aspiring mathematicians, coders, and other students who are passionate about fields that are being most transformed upon by AI? 0:00:00 – AI is discovering new proofs. Is that AGI? 0:11:32 – The verification loop on conceptual breakthroughs can be a century long 0:26:12 – Will we understand an AI proof of the Riemann hypothesis? 0:38:08 – Can AI find the hidden bridges between fields? 0:53:48 – Why real-world tasks don’t fit into RL environments 1:07:07 – Good writing requires theory of mind that AI still lacks 1:16:02 – Why learning will still depend on human curation Look up Dwarkesh Podcast on Spotify, Apple Podcasts, YouTube, etc.

Always so much fun to chat with Grant Sanderson AI has been making much faster progress in math than in other fields. As a result, mathematics is showing us, very concretely, what AI progress in other fields will look like. Even within mathematics, there's a jagged landscape. What does it look like? What is the nature of the most important conceptual breakthroughs in the history of mathematics, and how different are they from what AIs are currently able to do? Does AI (on net) increase or decrease human understanding of the field? How big is the overhang from having AIs systematically try to connect ideas already in the literature? And what advice does Grant have for aspiring mathematicians, coders, and other students who are passionate about fields that are being most transformed upon by AI? 0:00:00 – AI is discovering new proofs. Is that AGI? 0:11:32 – The verification loop on conceptual breakthroughs can be a century long 0:26:12 – Will we understand an AI proof of the Riemann hypothesis? 0:38:08 – Can AI find the hidden bridges between fields? 0:53:48 – Why real-world tasks don’t fit into RL environments 1:07:07 – Good writing requires theory of mind that AI still lacks 1:16:02 – Why learning will still depend on human curation Look up Dwarkesh Podcast on Spotify, Apple Podcasts, YouTube, etc.

Dwarkesh Patel

282,331 Aufrufe • vor 7 Tagen

New episode with former US Treasury Secretary and current OpenAI board member Larry Summers (Lawrence H. Summers). We discuss: - How he's been learning about AI. - The odds of the technology delivering a much faster economic growth regime (akin to the Industrial Revolution). - How AGI might change economic policymaking. Enjoy! Timestamps: (0:00:00) - Introduction. (0:00:46) - Larry's journey teaching himself about AI & deep learning since joining OpenAI’s board. (0:09:15) - How many hours per week has Larry been spending on OpenAI-related stuff? (0:10:16) - Which bottleneck to AI scaling does Larry think is the most underrated? (0:12:22) - Approximately what share of time do today's AI researchers spend on tasks that AI will be doing for them in five years? (0:15:01) - What explains the remarkable steadiness of US economic growth over the last 150 years? (0:19:42) - How likely is it that AI initiates a new growth regime with average growth that’s ~10x faster than today? (0:21:36) - What are the best economic arguments for believing AI won’t deliver a regime of ever-increasing growth rates? (0:25:33) - How much could AGI boost economic growth in developing countries merely by helping their policymakers make better decisions? (0:28:20) - How much better could monetary policy be if the Fed had AGI? (0:31:40) - How much would having AGI have helped US economic policymakers during the financial crisis & Great Recession? (0:36:07) - Is the CCP infiltrating and stealing the IP of major AI labs in the US and UK? (0:39:35) - At what point should AI be nationalised? (0:42:39) - How would Bill Clinton or Barack Obama be thinking about AI governance? (0:44:27) - If OpenAI restructures to a public benefit corporation, how does that change its incentives? (0:46:18) - What does Daron Acemoglu miss in his analysis of the economic impacts of AI?

New episode with former US Treasury Secretary and current OpenAI board member Larry Summers (Lawrence H. Summers). We discuss: - How he's been learning about AI. - The odds of the technology delivering a much faster economic growth regime (akin to the Industrial Revolution). - How AGI might change economic policymaking. Enjoy! Timestamps: (0:00:00) - Introduction. (0:00:46) - Larry's journey teaching himself about AI & deep learning since joining OpenAI’s board. (0:09:15) - How many hours per week has Larry been spending on OpenAI-related stuff? (0:10:16) - Which bottleneck to AI scaling does Larry think is the most underrated? (0:12:22) - Approximately what share of time do today's AI researchers spend on tasks that AI will be doing for them in five years? (0:15:01) - What explains the remarkable steadiness of US economic growth over the last 150 years? (0:19:42) - How likely is it that AI initiates a new growth regime with average growth that’s ~10x faster than today? (0:21:36) - What are the best economic arguments for believing AI won’t deliver a regime of ever-increasing growth rates? (0:25:33) - How much could AGI boost economic growth in developing countries merely by helping their policymakers make better decisions? (0:28:20) - How much better could monetary policy be if the Fed had AGI? (0:31:40) - How much would having AGI have helped US economic policymakers during the financial crisis & Great Recession? (0:36:07) - Is the CCP infiltrating and stealing the IP of major AI labs in the US and UK? (0:39:35) - At what point should AI be nationalised? (0:42:39) - How would Bill Clinton or Barack Obama be thinking about AI governance? (0:44:27) - If OpenAI restructures to a public benefit corporation, how does that change its incentives? (0:46:18) - What does Daron Acemoglu miss in his analysis of the economic impacts of AI?

Joseph Noel Walker

85,856 Aufrufe • vor 1 Jahr

Are AI benchmarks doomed? Greg Burnham and Tom Adamczewski join Anson Ho to push back on benchmark pessimism and dig into what the next generation of AI benchmarks could look like. (0:00:00) - Preview (0:00:36) - Intro: Are AI benchmarks doomed? (0:03:13) - The costs and benefits of benchmark development (0:11:48) - MirrorCode and scalable benchmarks (0:20:57) - AI speed-up in benchmark development (0:23:28) - The benchmark-reality gap (0:38:26) - Can an AGI benchmark exist? (0:43:18) - Beyond automated scoring (1:00:45) - How AI changes benchmark building in practice

Are AI benchmarks doomed? Greg Burnham and Tom Adamczewski join Anson Ho to push back on benchmark pessimism and dig into what the next generation of AI benchmarks could look like. (0:00:00) - Preview (0:00:36) - Intro: Are AI benchmarks doomed? (0:03:13) - The costs and benefits of benchmark development (0:11:48) - MirrorCode and scalable benchmarks (0:20:57) - AI speed-up in benchmark development (0:23:28) - The benchmark-reality gap (0:38:26) - Can an AGI benchmark exist? (0:43:18) - Beyond automated scoring (1:00:45) - How AI changes benchmark building in practice

Epoch AI

22,037 Aufrufe • vor 2 Monaten