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Anthropic Co-Founder Tom Brown: Why Anthropic Models Are The Best at Coding "The benchmarks are so easy to game. All the other big AI labs have teams whose job it is to make the benchmark scores good. We don't have such a team. That is the biggest factor." Anthropic's...

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Overlap: Business & Tech

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We built a tool that generates AI clones of people and Y Combinator used it in their official podcast today! 🎉 Check out the clip below to see AI clones of Garry Tan, Jared (Jared Friedman), Harj Taggar, and Diana talking about AI. Very meta Here's a 🧵on how we built it:
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We built a tool that generates AI clones of people and Y Combinator used it in their official podcast today! 🎉 Check out the clip below to see AI clones of Garry Tan, Jared (Jared Friedman), Harj Taggar, and Diana talking about AI. Very meta Here's a 🧵on how we built it:

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Co-founder disputes can be startup killers— but it doesn't have to be that way. On the Lightcone Podcast, Garry, Harj, Jared, and Diana share their experiences navigating co-founder conflict and their advice for how you can manage these challenges at your own startup.
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Co-founder disputes can be startup killers— but it doesn't have to be that way. On the Lightcone Podcast, Garry, Harj, Jared, and Diana share their experiences navigating co-founder conflict and their advice for how you can manage these challenges at your own startup.

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2025 was the year AI stopped feeling chaotic and started feeling buildable. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down the surprises of the year, from shifting model dominance to why the real opportunity is moving back to the application layer, and why the next wave of AI startups may be just getting started. 00:50 - Anthropic models are most preferred in the latest YC batch 05:36 - Why aren’t there more AI consumer apps? 07:01 - Swapping models in and out is becoming the norm 09:08 - The big AI bubble question 14:37 - Space as the solve for data centers and energy 17:29 - Interest in starting model companies 21:01 - Vibe coding became a big category 22:23 - AI economy has stabilized 23:38 - The AI 2027 piece 25:49 - Founders still need to hire teams
30:22

2025 was the year AI stopped feeling chaotic and started feeling buildable. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down the surprises of the year, from shifting model dominance to why the real opportunity is moving back to the application layer, and why the next wave of AI startups may be just getting started. 00:50 - Anthropic models are most preferred in the latest YC batch 05:36 - Why aren’t there more AI consumer apps? 07:01 - Swapping models in and out is becoming the norm 09:08 - The big AI bubble question 14:37 - Space as the solve for data centers and energy 17:29 - Interest in starting model companies 21:01 - Vibe coding became a big category 22:23 - AI economy has stabilized 23:38 - The AI 2027 piece 25:49 - Founders still need to hire teams

Y Combinator

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Anthropic Co-founder, Tom Brown: We're heading into the biggest infrastructure buildout in human history -- bigger than Apollo or the Manhattan Project AGI compute spending is rising at ~3x per year That trajectory is locked in for next year; 2027-2028 are less certain
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Anthropic Co-founder, Tom Brown: We're heading into the biggest infrastructure buildout in human history -- bigger than Apollo or the Manhattan Project AGI compute spending is rising at ~3x per year That trajectory is locked in for next year; 2027-2028 are less certain

Haider.

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MIT's new State of AI in Business report went viral for claiming that 95% of enterprise AI projects fail. But the real story isn't that AI doesn't work — it's just big companies can't build it. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down what the study really says, why in-house enterprise AI efforts keep stalling, and how startups are filling the gap with products that learn, integrate, and actually deliver value. 2:08 - The enterprise AI adoption gap and why the failure rate is high 3:32 - Even Apple can be bad at software 4:30 - Why getting enterprise software to actually work is so hard 11:08 - The Reducto case study 13:39 - The type of enterprise employee you should find as a founder 14:39 - Meet founders who’ve been acquired by enterprises 15:25 - Enterprise/startup tension and symbiosis
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MIT's new State of AI in Business report went viral for claiming that 95% of enterprise AI projects fail. But the real story isn't that AI doesn't work — it's just big companies can't build it. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down what the study really says, why in-house enterprise AI efforts keep stalling, and how startups are filling the gap with products that learn, integrate, and actually deliver value. 2:08 - The enterprise AI adoption gap and why the failure rate is high 3:32 - Even Apple can be bad at software 4:30 - Why getting enterprise software to actually work is so hard 11:08 - The Reducto case study 13:39 - The type of enterprise employee you should find as a founder 14:39 - Meet founders who’ve been acquired by enterprises 15:25 - Enterprise/startup tension and symbiosis

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Anthropic is doubling down and sending resources to customers that are most likely to have a sustainable future with the company, which according to co-founder Jared Kaplan, doesn’t include code-generation startup Windsurf:
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Anthropic is doubling down and sending resources to customers that are most likely to have a sustainable future with the company, which according to co-founder Jared Kaplan, doesn’t include code-generation startup Windsurf:

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🚨THIS IS SCARY: ANTHROPIC SAYS THE WORLD SHOULD HIT PAUSE ON AI Earlier, Anthropic CEO Dario Amodei: "The other extreme position is 'this is really scary, we should just pause.. stop building the technology'" Now, Anthropic says: "Our AI is getting scary good at improving us. We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development." Are we so close to that "extreme position" than most realise?
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🚨THIS IS SCARY: ANTHROPIC SAYS THE WORLD SHOULD HIT PAUSE ON AI Earlier, Anthropic CEO Dario Amodei: "The other extreme position is 'this is really scary, we should just pause.. stop building the technology'" Now, Anthropic says: "Our AI is getting scary good at improving us. We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development." Are we so close to that "extreme position" than most realise?

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YC's Diana Hu: 'Good Enough' vs. Top 1% Software of Engineers "There's going to be a generation of software engineers that are good enough because it's so easy to retool there with code gen tools. The barrier to enter is so low. But to be exceptional, like the top 1%, you're going to need to get into deliberate practice." Diana on Y Combinator's Lightcone Podcast
1:50

YC's Diana Hu: 'Good Enough' vs. Top 1% Software of Engineers "There's going to be a generation of software engineers that are good enough because it's so easy to retool there with code gen tools. The barrier to enter is so low. But to be exceptional, like the top 1%, you're going to need to get into deliberate practice." Diana on Y Combinator's Lightcone Podcast

Overlap: Business & Tech

82,895 görüntüleme • 1 yıl önce

Since the start of the year, OpenCode (YC W21) — an open source alternative to Claude Code and Codex that works with any model — exploded to 4.6 million weekly active users, 13 million monthly actives, and roughly $40M in annualized revenue. In this episode of The Lightcone, Harj Taggar, Jared Friedman, and Diana talk with Jay V (Jay), OpenCode’s CEO, about what’s driving this wild growth, the Anthropic clampdown that inadvertently fueled it, and the almost 20 year founder journey that led him here. 00:44 — OpenCode’s Explosive Growth 01:16 — 20x Growth, 13M Users, and 7 Trillion Tokens 03:39 — The Anthropic Controversy That Changed Everything 05:43 — Bringing AI Coding Agents to the World 06:39 — When Open Source Models Became Good Enough 08:56 — What Millions of Developers Are Actually Using 13:31 — Why OpenCode Is Huge Outside the US 15:27 — Why Fortune 500 Companies Choose OpenCode 16:36 — The Economics of AI Tokens 20:02 — How Enterprises Are Using Coding Agents 22:58 — AI’s New Unit Economics 24:56 — Why Model Choice Matters 29:55 — The Product Decisions Behind OpenCode 34:21 — A 16-Year Overnight Success 41:16 — Why Jay Never Gave Up
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Since the start of the year, OpenCode (YC W21) — an open source alternative to Claude Code and Codex that works with any model — exploded to 4.6 million weekly active users, 13 million monthly actives, and roughly $40M in annualized revenue. In this episode of The Lightcone, Harj Taggar, Jared Friedman, and Diana talk with Jay V (Jay), OpenCode’s CEO, about what’s driving this wild growth, the Anthropic clampdown that inadvertently fueled it, and the almost 20 year founder journey that led him here. 00:44 — OpenCode’s Explosive Growth 01:16 — 20x Growth, 13M Users, and 7 Trillion Tokens 03:39 — The Anthropic Controversy That Changed Everything 05:43 — Bringing AI Coding Agents to the World 06:39 — When Open Source Models Became Good Enough 08:56 — What Millions of Developers Are Actually Using 13:31 — Why OpenCode Is Huge Outside the US 15:27 — Why Fortune 500 Companies Choose OpenCode 16:36 — The Economics of AI Tokens 20:02 — How Enterprises Are Using Coding Agents 22:58 — AI’s New Unit Economics 24:56 — Why Model Choice Matters 29:55 — The Product Decisions Behind OpenCode 34:21 — A 16-Year Overnight Success 41:16 — Why Jay Never Gave Up

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The Anthropic CEO says AI is about to trigger a biotech renaissance and cure diseases we have accepted as permanent. Here are the two stocks best positioned to capture it.
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The Anthropic CEO says AI is about to trigger a biotech renaissance and cure diseases we have accepted as permanent. Here are the two stocks best positioned to capture it.

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Anthropic CEO: “At Anthropic, we essentially have Claude designing the next version of Claude itself.” Meanwhile, Anthropic says every new model is given code that trains a small AI model and asked to make it faster. Claude Opus 4 achieved a 3x speedup. Mythos Preview reached 52x. Recursive self-improvement is starting to look real The models are helping build what comes next.
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Anthropic CEO: “At Anthropic, we essentially have Claude designing the next version of Claude itself.” Meanwhile, Anthropic says every new model is given code that trains a small AI model and asked to make it faster. Claude Opus 4 achieved a 3x speedup. Mythos Preview reached 52x. Recursive self-improvement is starting to look real The models are helping build what comes next.

CG

343,231 görüntüleme • 2 ay önce

This is the best take I have heard around the existing AI landscape today Fantastic explanation around the constraints at OpenAI and Anthropic, focus on enterprise business models, and the doomerism narrative in AI From former AI czar David Sacks "Even though Anthropic's revenue has followed this exponential graph very predictably, it cannot do that ever. The reason is that as you hit new levels of scale, you encounter new problems. You are simply going to run out of compute, electricity, data centers, and infrastructure. There are limits to the physical world you are going to hit. And there is already evidence that Anthropic is hitting some of those limits."
4:27

This is the best take I have heard around the existing AI landscape today Fantastic explanation around the constraints at OpenAI and Anthropic, focus on enterprise business models, and the doomerism narrative in AI From former AI czar David Sacks "Even though Anthropic's revenue has followed this exponential graph very predictably, it cannot do that ever. The reason is that as you hit new levels of scale, you encounter new problems. You are simply going to run out of compute, electricity, data centers, and infrastructure. There are limits to the physical world you are going to hit. And there is already evidence that Anthropic is hitting some of those limits."

Boring_Business

236,448 görüntüleme • 4 ay önce

Arthur Mensch confirmed on CNBC this week that OpenAI and Anthropic are calling Mistral asking for compute. The two companies racing to build the most powerful AI in the world are dependent on a European competitor they have been trying to outrun. Let that land for a second. The narrative you have been sold is that the US is running away with AI. That OpenAI and Anthropic have such a commanding lead that the rest of the world is playing catch-up. That narrative is missing something physical. The International Energy Agency projected this year that US data center electricity demand will double by 2030. The US grid is already at capacity. Europe has the power. Europe has the land. And right now the company fielding calls from the most funded AI labs on earth is a four-year-old French startup. Mensch said Mistral is prioritizing its own customers first. The surge in agentic usage is generating far more tokens than anyone planned for and existing capacity is spoken for. The US labs are in the queue. But they are in the queue. Most people following AI are watching benchmark scores and funding rounds. The actual constraint right now is electricity and physical space. And on that dimension, the scoreboard looks nothing like the one most people are reading. Watch the full podcast on YouTube at CNBC International
1:06

Arthur Mensch confirmed on CNBC this week that OpenAI and Anthropic are calling Mistral asking for compute. The two companies racing to build the most powerful AI in the world are dependent on a European competitor they have been trying to outrun. Let that land for a second. The narrative you have been sold is that the US is running away with AI. That OpenAI and Anthropic have such a commanding lead that the rest of the world is playing catch-up. That narrative is missing something physical. The International Energy Agency projected this year that US data center electricity demand will double by 2030. The US grid is already at capacity. Europe has the power. Europe has the land. And right now the company fielding calls from the most funded AI labs on earth is a four-year-old French startup. Mensch said Mistral is prioritizing its own customers first. The surge in agentic usage is generating far more tokens than anyone planned for and existing capacity is spoken for. The US labs are in the queue. But they are in the queue. Most people following AI are watching benchmark scores and funding rounds. The actual constraint right now is electricity and physical space. And on that dimension, the scoreboard looks nothing like the one most people are reading. Watch the full podcast on YouTube at CNBC International

Ihtesham Ali

47,162 görüntüleme • 2 ay önce

Tom Brown (Tom Brown) co-founded Anthropic after helping build GPT-3 at OpenAI. A self-taught engineer, he went from getting a B-minus in linear algebra to becoming one of the key people behind AI's scaling breakthroughs. Today, Anthropic's Claude is the go-to choice for developers, and his team is overseeing what he calls "humanity's largest infrastructure buildout ever." On the Lightcone Podcast, he discusses his unconventional path from YC founder to AI researcher, the discovery of scaling laws that changed everything, and his advice for young engineers entering AI today. 0:00 - From Failure to Success 2:30 - Early Startup Days at Linked Language 4:12 - The Grouper Dating Experiment 6:10 - Making the Leap to OpenAI 8:42 - First Product Launch Challenges 10:12 - Self-Teaching AI Research 12:44 - Building GPT-3 Infrastructure 15:44 - The Anthropic Spinoff 18:23 - Early Days of Building Claude 20:21 - The ChatGPT Wake-Up Call 22:08 - Claude 3.5 Sonnet Breakthrough 24:13 - Why Benchmarks Don't Tell the Whole Story 26:20 - Claude Code's Secret Sauce 28:51 - Building for the AI Agent 31:11 - The Largest Infrastructure Buildout Ever 32:46 - Multi-Chip Strategy 34:38 - Advice for the Next Generation
35:56

Tom Brown (Tom Brown) co-founded Anthropic after helping build GPT-3 at OpenAI. A self-taught engineer, he went from getting a B-minus in linear algebra to becoming one of the key people behind AI's scaling breakthroughs. Today, Anthropic's Claude is the go-to choice for developers, and his team is overseeing what he calls "humanity's largest infrastructure buildout ever." On the Lightcone Podcast, he discusses his unconventional path from YC founder to AI researcher, the discovery of scaling laws that changed everything, and his advice for young engineers entering AI today. 0:00 - From Failure to Success 2:30 - Early Startup Days at Linked Language 4:12 - The Grouper Dating Experiment 6:10 - Making the Leap to OpenAI 8:42 - First Product Launch Challenges 10:12 - Self-Teaching AI Research 12:44 - Building GPT-3 Infrastructure 15:44 - The Anthropic Spinoff 18:23 - Early Days of Building Claude 20:21 - The ChatGPT Wake-Up Call 22:08 - Claude 3.5 Sonnet Breakthrough 24:13 - Why Benchmarks Don't Tell the Whole Story 26:20 - Claude Code's Secret Sauce 28:51 - Building for the AI Agent 31:11 - The Largest Infrastructure Buildout Ever 32:46 - Multi-Chip Strategy 34:38 - Advice for the Next Generation

Y Combinator

96,516 görüntüleme • 1 yıl önce