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We went inside Amazon's AI chip lab. Tucked inside an ordinary-looking office in Austin, Texas is a business taking on Nvidia. Amazon figured out how to design cutting-edge AI chips for its AWS customers, including some of AI's biggest stars, like Anthropic. Here's the breakdown: 0:00 Inside Amazon 1:12... show more

Jon Erlichman

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17,019 views • 1 month ago •via X (Twitter)

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World Premiere of Amazon — Market. Power! Monopoly? This documentary will show you how Amazon uses its size and power to raise prices, for you, the consumer. The documentary follows four sellers on Amazon, two in Europe, two in the US, and their journey to survive on the platform. It begins with an explanation of Amazon's pricing policies and the complex way Amazon enforces them. Watch this foundational beginning section carefully and your mind will be blown later in the documentary when you see what goes on behind the scenes, when you click buy. This is an extremely important documentary. Amazon responds to fair criticism and it is my hope, that with your support that we can change Amazon's policies. So sellers can set their own prices. And so you can pay less when you shop online. Timestamps ---Amazon in Europe--- 1:56 How Amazon's pricing systems work 5:24 Does Amazon follow its own pricing rules? 9:26 Europe's investigations into Amazon's market power 14:00 What happens when you sell off-Amazon for less? ---Amazon in the US--- 17:28 Amazon in the USA 20:15 The Brain Flakes 20:37 Calculating the revenues of sellers on Amazon 22:56 Is Amazon a Monopoly? 24:13 How Amazon uses its marketplace to subsidize its money-losing businesses 26:01 The ads on Amazon and how they drive up prices 27:00 How sellers are forced to use Amazon's other services ---Amazon in Europe--- 28:50 Competing with Amazon to be seen in search 29:53 What data analysis says about Amazon following its own rules 32:07 European investigations into Amazon's conduct 33:57 Is it possible to sell online without Amazon? 35:20 How Europe curbed Amazon's pricing behavior ---Amazon in the US--- 37:52 Does Amazon's Basics brand copy its sellers' products? 38:41 The Everyday Sling 40:27 Does Amazon use private data to decide what products to copy? ---Amazon in Europe--- 44:46 Is Amazon a monopoly that should be broken up? 46:52 Credits 47:08 Do you have an Amazon Prime account? I'd like to thank all who made this film possible. A special thank you and respect goes out to the sellers who appeared. It takes a lot of guts and conviction to stand up to one of the world's most powerful companies. To support their businesses, please click into the replies where you will find links to their (off-Amazon!) websites, as well as links to this documentary on other video viewing platforms! Thank you and enjoy!

molson 🧠⚙️

997,317 views • 2 years ago

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

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Matt Turck

56,883 views • 1 month ago

My conversation with Ben Thompson. Ben has been writing Stratechery for over a decade and remains one of my favorite business thinkers. We covered a lot. Every important company in the industry and the forces acting on all of them. - Why he thinks it would be problematic for the US to win the AI race - Will we run out of money to fund AI - Google becoming Berkshire Hathaway - Why ads are amazing - TSMC, Intel, and Samsung - Nvidia's invisible price cuts + biggest competitors - Microsoft, Amazon, Apple, and Meta I love talking to Ben about everything happening in markets and technology. Enjoy! TIMESTAMPS 0:00 Intro 0:59 America and the AI Race 8:26 AI’s Funding Problem 15:31 AI’s Capabilities and Limits 20:30 Aggregation Theory, AI, and Ads 31:10 Compute, TSMC, and Intel 47:31 Amazon and Apple’s AI Moats 54:43 The Frontier AI Players 74:07 Nvidia and Commoditized Intelligence 82:52 What Survives an AI Bubble?

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Patrick OShaughnessy

1,461,873 views • 8 days ago

This is cool, Elon Musk says SpaceX will allow their customers to use any GPU or TPU they want in SpaceX AI Satellites. "We do intend with our SpaceX AI Satellites to allow people to put whatever GPU or TPU they want. So Nvidia GPUS can be put on it, Google TPUs can be put on it, Amazon Trainium, or any other chips people want to put on. It will be such that you can run anyone’s AI, hardware or software on the SpaceX AI Satellites." An open platform design is so smart.

This is cool, Elon Musk says SpaceX will allow their customers to use any GPU or TPU they want in SpaceX AI Satellites. "We do intend with our SpaceX AI Satellites to allow people to put whatever GPU or TPU they want. So Nvidia GPUS can be put on it, Google TPUs can be put on it, Amazon Trainium, or any other chips people want to put on. It will be such that you can run anyone’s AI, hardware or software on the SpaceX AI Satellites." An open platform design is so smart.

Nic Cruz Patane

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ashen

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Neil Movva (Neil Movva) started his career at Nvidia, working on GPUs and kernels, and has an unusually deep understanding of inference, from software to chips to power. We spend a lot of time on each of those layers, how they connect, and where the important tradeoffs are. What makes this conversation special is how detailed it is (like a 401-level class), yet Neil makes it remarkably clear and easy to follow. Today he runs Sail Research, a company building infrastructure for agents to make tokens as cheap as possible. We discuss: - Latency versus throughput - Why there are no bad chips, only bad pricing - The end of kernel engineering - Buying chips and power no one else wants - New chip architectures - Nvidia lore + his contrarian view of the company - Open source and the frontier labs I learned a ton. Enjoy! TIMESTAMPS 0:00 Intro 0:38 Building a “Token Factory” 4:21 The Future of Background Agents 13:09 Nvidia and the GPU Stack 23:27 Chips, Memory, and Transformers 36:14 The Future of AI Training Data 44:32 Chip Scarcity and Compute Arbitrage 52:44 Reinventing the AI Data Center 59:01 Power and the “Scavenger Strategy” 1:10:10 Open vs. Closed AI

Patrick OShaughnessy

3,307,673 views • 1 day ago

AI is increasingly discovering new ways to attack cryptographic algorithms today, I spoke with Ethereum researcher Justin Drake on what this means for the future 0:35 HAWK signature scheme flaw 2:08 security risks 4:13 Ethereum's post-quantum roadmap 7:29 why verification is expensive 11:12 formal verification 11:59 Ethereum in a post-AI world 14:03 attackers vs. defenders 16:32 inside the Ethereum Foundation 18:15 what AI labs should prioritize

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sophia dew

22,680 views • 28 days ago

Everyone argues about whether AI replaces physicians. Kimberly Powell of NVIDIA Healthcare has a different way into the question. AI automates tasks, but the task is not the job. And the more AI we deploy, the more disease we find to treat, so demand for clinicians is going up, not down. The only way to meet it is automation. We covered a lot this week on Lifers: (00:00) Lead In (00:44) Intro (01:24) Kimberly joins NVIDIA (05:13) Early healthcare adoption (08:41) Augment not replace (14:35) Inside the future hospital (16:27) Sponsors: Granola | Baker Health (18:38) Why healthcare matters (23:25) Agents unlock workflows (28:53) Clinicians adapting to AI (33:43) Safety and risk reward (40:19) Agents across industry (44:14) Five year predictions (49:53) AI hireable and ROI (54:02) Personal tech habits (55:59) AI etiquette and hacks (58:52) Wrap

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Christina Farr

23,351 views • 8 days ago

AMD might have disrupted Nvidia's entire cloud GPU rental business. In January at CES, AMD CEO Lisa Su demonstrated a $1,499 mini PC running the same class of AI model that currently costs companies $2,500 to $3,000 every month to rent from Nvidia-powered cloud servers. AMD's own branded version opened pre-orders this month at $3,999. Third party manufacturers have been selling the same chip since 2025 starting at $1,499. Here is exactly why this is dangerous for Nvidia. Nvidia's $75 billion quarterly revenue is built almost entirely on one business model, companies rent access to Nvidia GPUs through cloud providers like AWS and Lambda Labs to run AI. They pay monthly. Nvidia gets paid every time someone runs an AI model in the cloud. That recurring rental income is what turned Nvidia into a $5 trillion company. The AMD box eliminates that monthly fee permanently. One AI consultant switched from $2,800 per month in Nvidia cloud rental costs to $8 per month in electricity. The hardware paid for itself in 11 days. Over 8 months he generated $47,000 running the same AI workloads that previously left him paying Nvidia's ecosystem $2,800 every single month. Multiply that across thousands of enterprise customers and the revenue erosion becomes structural. Every business that buys this box stops paying cloud rental fees forever. Lawyers, doctors, banks, accountants, and financial advisors, businesses with sensitive data that cannot legally go to a cloud server represent billions in annual cloud GPU fees that Nvidia is now at risk of losing permanently. The threat is also closing in from the top. Google signed deals worth tens of billions with Anthropic and Meta to replace Nvidia with its own chips. Amazon built its own AI chips across AWS. Apple trained its AI on Google's chips, not Nvidia's. Custom silicon has grown from 21% of the AI chip market in 2025 to 28% in 2026. Nvidia's rental model only worked because serious AI compute had no alternative.

AMD might have disrupted Nvidia's entire cloud GPU rental business. In January at CES, AMD CEO Lisa Su demonstrated a $1,499 mini PC running the same class of AI model that currently costs companies $2,500 to $3,000 every month to rent from Nvidia-powered cloud servers. AMD's own branded version opened pre-orders this month at $3,999. Third party manufacturers have been selling the same chip since 2025 starting at $1,499. Here is exactly why this is dangerous for Nvidia. Nvidia's $75 billion quarterly revenue is built almost entirely on one business model, companies rent access to Nvidia GPUs through cloud providers like AWS and Lambda Labs to run AI. They pay monthly. Nvidia gets paid every time someone runs an AI model in the cloud. That recurring rental income is what turned Nvidia into a $5 trillion company. The AMD box eliminates that monthly fee permanently. One AI consultant switched from $2,800 per month in Nvidia cloud rental costs to $8 per month in electricity. The hardware paid for itself in 11 days. Over 8 months he generated $47,000 running the same AI workloads that previously left him paying Nvidia's ecosystem $2,800 every single month. Multiply that across thousands of enterprise customers and the revenue erosion becomes structural. Every business that buys this box stops paying cloud rental fees forever. Lawyers, doctors, banks, accountants, and financial advisors, businesses with sensitive data that cannot legally go to a cloud server represent billions in annual cloud GPU fees that Nvidia is now at risk of losing permanently. The threat is also closing in from the top. Google signed deals worth tens of billions with Anthropic and Meta to replace Nvidia with its own chips. Amazon built its own AI chips across AWS. Apple trained its AI on Google's chips, not Nvidia's. Custom silicon has grown from 21% of the AI chip market in 2025 to 28% in 2026. Nvidia's rental model only worked because serious AI compute had no alternative.

Bull Theory

26,765 views • 2 months ago

Early on, Jonathan Ross foresaw the unprecedented demand for compute of the 2020s. After pioneering Google's TPUs, he founded Groq, a "Language" Processing Unit dedicated for inference. After joining NVIDIA, he is betting on the GPU+LPU combo to power the agentic chains of AI calling AI calling AI. This interview is part of my larger series on dedicated AI chips, so drop any suggestions/questions below. Thank you NVIDIA for hosting us at your HQ! 00:00 Intro 01:00 The Google TPU & Groq origin story 02:41 How is Groq different from a GPU? 04:43 Static scheduling makes Groq faster 05:47 Does Groq work with Mixture-of-Experts? 09:27 Are LPUs limited to text models? 11:03 Diffusion models 13:41 NVIDIA Vera Rubin: the GPU+LPU combo 15:26 Will Groq still be sold as a standalone chip? 16:49 How does agentic AI impact inference economics? 19:21 Will AI replace CUDA kernel engineers? 21:08 Will AI democratize hardware design? 26:11 Jevon's paradox: An endless demand for compute 29:04 What should kids learn in the AI age?

Early on, Jonathan Ross foresaw the unprecedented demand for compute of the 2020s. After pioneering Google's TPUs, he founded Groq, a "Language" Processing Unit dedicated for inference. After joining NVIDIA, he is betting on the GPU+LPU combo to power the agentic chains of AI calling AI calling AI. This interview is part of my larger series on dedicated AI chips, so drop any suggestions/questions below. Thank you NVIDIA for hosting us at your HQ! 00:00 Intro 01:00 The Google TPU & Groq origin story 02:41 How is Groq different from a GPU? 04:43 Static scheduling makes Groq faster 05:47 Does Groq work with Mixture-of-Experts? 09:27 Are LPUs limited to text models? 11:03 Diffusion models 13:41 NVIDIA Vera Rubin: the GPU+LPU combo 15:26 Will Groq still be sold as a standalone chip? 16:49 How does agentic AI impact inference economics? 19:21 Will AI replace CUDA kernel engineers? 21:08 Will AI democratize hardware design? 26:11 Jevon's paradox: An endless demand for compute 29:04 What should kids learn in the AI age?

Julia Turc

46,967 views • 2 months ago

Chris Camillo made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Chris Camillo made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Milk Road Stocks

41,351 views • 1 month ago

Chris Camillo just made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Chris Camillo just made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Milk Road Macro

55,169 views • 3 months ago

“This Is the Worst It’ll Ever Be”—State of Dealership AI and What Dealers Should Be Asking My conversation with Eric Rea, CEO of Podium: 0:15 What fueled Podium's rapid growth? 1:07 How did Podium get started? 3:00 How is AI transforming dealerships? 5:42 What makes Jerry AI special? 8:11 Customizing AI for dealers how? 13:08 Will AI replace BDC teams? 16:27 Future AI applications in auto? 26:00 How AI revolutionizes service departments? 32:25 Biggest voice AI challenges today?

“This Is the Worst It’ll Ever Be”—State of Dealership AI and What Dealers Should Be Asking My conversation with Eric Rea, CEO of Podium: 0:15 What fueled Podium's rapid growth? 1:07 How did Podium get started? 3:00 How is AI transforming dealerships? 5:42 What makes Jerry AI special? 8:11 Customizing AI for dealers how? 13:08 Will AI replace BDC teams? 16:27 Future AI applications in auto? 26:00 How AI revolutionizes service departments? 32:25 Biggest voice AI challenges today?

Car Dealership Guy

95,524 views • 1 year ago

This is the best presentation ever given about Amazon's retail business. If you own the stock, if you're thinking about owning the stock, if you are a prime member, or if you care about the future of ecommerce, you need to watch this video. In it, I make 12 predictions about Amazon's future and tell you why I'm qualified to do so. 1. How will the new CEO run Amazon? 2. Will Amazon be getting better or worse? 3. Will Amazon be able to take over the 3rd party warehousing market? 4. Will Amazon's Temu competitor "Amazon Haul" work? 5. What will Amazon's competitive landscape look like with China's Temu, TikTok, and Shein? 6. Will Chinese sellers take over on Amazon? 7. What do Walmart, Target, and eBay have to say about all this? 8. What's the future of e-commerce search amidst conversational AI? 9. Will Amazon lose its monopoly case against the FTC? 10. Will Amazon be broken up? 11. Will Amazon be able to continue to grow Prime customers? 12. Will fraud on the Amazon platform rise? And then finally, I will tell you how US e-commerce sellers can adapt to this future (it's bleak right now, but there are some unexpected glimmers of hope). I have a e-com crystal ball and I am not afraid to use it to tell you my contrarian but right predictions for where Amazon (and America) are headed. Buckle up and watch the best Amazon retail presentation you have ever seen. In the next tweet, I will provide a Yootube link as well as links to the AMZ Innovate conference (which I have zero financial relationship with) and links to my company's websites where you can buy our products FOR LESS THAN AMAZON and support me and my team for keeping it real about this giant company that accounts for ~80% of revenue. Thank you and enjoy! 👇

This is the best presentation ever given about Amazon's retail business. If you own the stock, if you're thinking about owning the stock, if you are a prime member, or if you care about the future of ecommerce, you need to watch this video. In it, I make 12 predictions about Amazon's future and tell you why I'm qualified to do so. 1. How will the new CEO run Amazon? 2. Will Amazon be getting better or worse? 3. Will Amazon be able to take over the 3rd party warehousing market? 4. Will Amazon's Temu competitor "Amazon Haul" work? 5. What will Amazon's competitive landscape look like with China's Temu, TikTok, and Shein? 6. Will Chinese sellers take over on Amazon? 7. What do Walmart, Target, and eBay have to say about all this? 8. What's the future of e-commerce search amidst conversational AI? 9. Will Amazon lose its monopoly case against the FTC? 10. Will Amazon be broken up? 11. Will Amazon be able to continue to grow Prime customers? 12. Will fraud on the Amazon platform rise? And then finally, I will tell you how US e-commerce sellers can adapt to this future (it's bleak right now, but there are some unexpected glimmers of hope). I have a e-com crystal ball and I am not afraid to use it to tell you my contrarian but right predictions for where Amazon (and America) are headed. Buckle up and watch the best Amazon retail presentation you have ever seen. In the next tweet, I will provide a Yootube link as well as links to the AMZ Innovate conference (which I have zero financial relationship with) and links to my company's websites where you can buy our products FOR LESS THAN AMAZON and support me and my team for keeping it real about this giant company that accounts for ~80% of revenue. Thank you and enjoy! 👇

molson 🧠⚙️

48,128 views • 1 year ago

New podcast episode: Dylan Patel's hot takes on NVIDIA, Intel, AMD, Oracle, Huawei, OpenAI, xAI, Amazon, and more. (0:29) Nvidia and Intel: Unlikely Allies (2:11) Investment and Capital in Semiconductors (4:27) The Impact on AMD and ARM (5:21) China’s AI Chip Race: Huawei’s Rise (22:32) Nvidia’s Strategy & Moat (29:44) Nvidia’s Moat: How They Built It (39:40) Jensen Huang’s Leadership and Company Culture (46:37) The Future of Nvidia (56:11) The Hyperscalers: Amazon, Oracle, and the Cloud Wars (1:16:03) xAI’s Colossus 2 (1:22:06) Recommendations to Start-Ups (1:34:49) The State of the GPU Market Today Erik Torenberg Sarah Wang Guido Appenzeller

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a16z

123,157 views • 11 months ago

I sat down with Jordi Visser at Bitcoin Investor Week to discuss why software stocks are losing their moats, how AI is driving deflation, and why capital is rotating toward scarce assets. We explore hyperscalers, data centers, AI agents, and why bitcoin may emerge as the only true growth asset in a world of abundant intelligence. YouTube: Spotify: Apple: TIMESTAMP: 0:00 - Intro 0:56 – Cathie Wood’s AI take & why Jordi disagrees 4:30 – Why Big Tech may struggle to monetize AI 6:57 – Deflation vs disinflation in an AI-driven economy 10:08 – What investors should actually do right now 14:12 – The scarcity trade & why bitcoin stands out 16:25 – How investors can use AI to gain an edge 19:16 – Where to follow Jordi Visser & his work

I sat down with Jordi Visser at Bitcoin Investor Week to discuss why software stocks are losing their moats, how AI is driving deflation, and why capital is rotating toward scarce assets. We explore hyperscalers, data centers, AI agents, and why bitcoin may emerge as the only true growth asset in a world of abundant intelligence. YouTube: Spotify: Apple: TIMESTAMP: 0:00 - Intro 0:56 – Cathie Wood’s AI take & why Jordi disagrees 4:30 – Why Big Tech may struggle to monetize AI 6:57 – Deflation vs disinflation in an AI-driven economy 10:08 – What investors should actually do right now 14:12 – The scarcity trade & why bitcoin stands out 16:25 – How investors can use AI to gain an edge 19:16 – Where to follow Jordi Visser & his work

Anthony Pompliano 🌪

44,385 views • 6 months ago

Why Galaxy Might Be the Most Undervalued Crypto x AI Stock w/ Duncan What do Meta, Amazon, Google, and Microsoft …have in common? They’re spending $330B on AI infra this year. And one crypto company is building the AI infrastructure to power them. Tune in to know more ⏱ TIME POINTS ⏱ 00:00 – Intro 00:58 – Where Are We in the Bull Market? 03:11 – Is the 4-Year Cycle Dead? 06:25 – How Public Markets Are Changing Crypto 12:13 – Figure Markets 12:48 – KGeN 13:18 – Why Duncan Loves $GLXY 16:10 – The AI Data Center Opportunity 27:23 – Risks of Building at AI Scale 33:33 – What’s Galaxy’s Endgame? 36:05 – AI & Robots: What’s Coming and When 43:46 – How to Invest in Humanoid Robots 47:50 – What Could Slow Down Robot Adoption? 50:18 – Where Duncan Finds Alpha 53:29 – Final Thoughts

Why Galaxy Might Be the Most Undervalued Crypto x AI Stock w/ Duncan What do Meta, Amazon, Google, and Microsoft …have in common? They’re spending $330B on AI infra this year. And one crypto company is building the AI infrastructure to power them. Tune in to know more ⏱ TIME POINTS ⏱ 00:00 – Intro 00:58 – Where Are We in the Bull Market? 03:11 – Is the 4-Year Cycle Dead? 06:25 – How Public Markets Are Changing Crypto 12:13 – Figure Markets 12:48 – KGeN 13:18 – Why Duncan Loves $GLXY 16:10 – The AI Data Center Opportunity 27:23 – Risks of Building at AI Scale 33:33 – What’s Galaxy’s Endgame? 36:05 – AI & Robots: What’s Coming and When 43:46 – How to Invest in Humanoid Robots 47:50 – What Could Slow Down Robot Adoption? 50:18 – Where Duncan Finds Alpha 53:29 – Final Thoughts

Milk Road

59,357 views • 11 months ago

Project Genesis is the closest thing we’ve seen to the Manhattan Project for science since 1939, what will this mean for America's AI dominance? - AWS planning $50B in U.S. government AI infrastructure + a 2.2 GW Indiana megacenter. - Google’s Ironwood TPU lands 4× performance and million-token multimodal context. - Amazon deploying 500,000 Tranium 2 chips for Anthropic-scale workloads. - Google is now rivaling NVIDIA by letting companies like Meta train frontier models directly on Google Cloud instead of buying GPUs.

Project Genesis is the closest thing we’ve seen to the Manhattan Project for science since 1939, what will this mean for America's AI dominance? - AWS planning $50B in U.S. government AI infrastructure + a 2.2 GW Indiana megacenter. - Google’s Ironwood TPU lands 4× performance and million-token multimodal context. - Amazon deploying 500,000 Tranium 2 chips for Anthropic-scale workloads. - Google is now rivaling NVIDIA by letting companies like Meta train frontier models directly on Google Cloud instead of buying GPUs.

Peter H. Diamandis, MD

41,936 views • 9 months ago

METR investigated what a rogue AI could secretly get away with inside a frontier AI lab, in close collaboration with OpenAI, GDM, Anthropic and Meta. Including sending a red-teamer into Anthropic to playact 'evil Claude' for 3 weeks. Here's what stands out to me from their new 320-page report: 00:00 What could an unreleased AI get away with? 01:54 Motive: Why grab more compute? 05:46 Opportunity: YOLO mode and jailbreaks 11:02 Means: Brilliant idiots in data centres 15:45 We have to test unreleased models... 18:29 ...especially if AI R&D is coming in 2028

METR investigated what a rogue AI could secretly get away with inside a frontier AI lab, in close collaboration with OpenAI, GDM, Anthropic and Meta. Including sending a red-teamer into Anthropic to playact 'evil Claude' for 3 weeks. Here's what stands out to me from their new 320-page report: 00:00 What could an unreleased AI get away with? 01:54 Motive: Why grab more compute? 05:46 Opportunity: YOLO mode and jailbreaks 11:02 Means: Brilliant idiots in data centres 15:45 We have to test unreleased models... 18:29 ...especially if AI R&D is coming in 2028

Rob Wiblin

40,047 views • 3 months ago