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Greg Osuri built the case for decentralized AI in three layers in under 5 minutes. Layer one: access. Anthropic's Claude is the best coding model available. OpenClaw is the most successful open-source project in history. Anthropic just announced they're banning OpenClaw usage. The most powerful model cutting off the...

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14,986 views • 3 months ago •via X (Twitter)

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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.
1:25

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 • 1 month ago

FOR THE FIRST TIME, THE US GOVERNMENT PULLED A PUBLICLY DEPLOYED AI MODEL OFFLINE. THE MARKET SHOULD PAY ATTENTION. 🇺🇸 On June 12, the Commerce Department ordered Anthropic to block access to its newest models, Fable 5 and Mythos 5, for any foreign national. Anthropic had to disable them for everyone to comply. The stated reason was a security concern. Anthropic disputes it, calling the flagged technique a narrow jailbreak available in other models too. Whatever the truth, here's the macro takeaway: Frontier AI now sits close enough to national security that a government can switch it off overnight. If you don't control your own models and compute, you're one directive away from losing access. That's the case for open and local models, in one headline.
0:27

FOR THE FIRST TIME, THE US GOVERNMENT PULLED A PUBLICLY DEPLOYED AI MODEL OFFLINE. THE MARKET SHOULD PAY ATTENTION. 🇺🇸 On June 12, the Commerce Department ordered Anthropic to block access to its newest models, Fable 5 and Mythos 5, for any foreign national. Anthropic had to disable them for everyone to comply. The stated reason was a security concern. Anthropic disputes it, calling the flagged technique a narrow jailbreak available in other models too. Whatever the truth, here's the macro takeaway: Frontier AI now sits close enough to national security that a government can switch it off overnight. If you don't control your own models and compute, you're one directive away from losing access. That's the case for open and local models, in one headline.

Merlijn The Trader

47,986 views • 1 month ago

ANTHROPIC'S NEW AI MODEL "MYTHOS" IS SO POWERFUL THE COMPANY WON'T RELEASE IT TO THE PUBLIC YET Instead, they're giving it to 11 companies first through "Project Glasswing" to find cybersecurity vulnerabilities before bad actors can. The partners: Amazon, Apple, Broadcom, Nvidia, Google, and others. The model wasn't built for cybersecurity. It was built to be an automated AI researcher, an AI that helps build better AI. But those same capabilities make it a serious tool for both offensive and defensive cyber operations. OpenAI reportedly has a similar model codenamed "SPU" going through the same slow rollout process. Palisade Research: "Anthropic is a little ahead, but not overwhelmingly ahead. They don't necessarily have a permanent moat here."
6:38

ANTHROPIC'S NEW AI MODEL "MYTHOS" IS SO POWERFUL THE COMPANY WON'T RELEASE IT TO THE PUBLIC YET Instead, they're giving it to 11 companies first through "Project Glasswing" to find cybersecurity vulnerabilities before bad actors can. The partners: Amazon, Apple, Broadcom, Nvidia, Google, and others. The model wasn't built for cybersecurity. It was built to be an automated AI researcher, an AI that helps build better AI. But those same capabilities make it a serious tool for both offensive and defensive cyber operations. OpenAI reportedly has a similar model codenamed "SPU" going through the same slow rollout process. Palisade Research: "Anthropic is a little ahead, but not overwhelmingly ahead. They don't necessarily have a permanent moat here."

WOLF

80,158 views • 3 months ago

Jensen Huang just told the smartest founders in AI they’re building a commodity. Not a platform. Not a moat. A commodity. Huang: “AI is actually essentially a five-layer cake.” Energy. Chips. Cloud. Models. Applications. Five layers. The entire industry is crowded onto one. Huang: “This is where most people think AI is.” The model layer. Most money. Most talent. Most competition. Most competition always ends the same way. A commodity. The harder they compete, the faster they erase their own value. That’s not a failure of strategy. That’s the strategy working. Huang: “At the bottom is energy.” No algorithm solves a power grid. No fundraise builds a dam. For decades everyone assumed intelligence would be the scarce resource. AI proved the opposite. Intelligence scales. Energy doesn’t. The bottleneck was never thinking. It was always power. Huang: “This layer on top ultimately is where economic benefit will happen.” The top captures revenue. The bottom controls access. The middle converts one into the other. Hundreds of billions deployed between someone else’s power grid and someone else’s economy. Most funded layer in history. Least defensible layer in the stack. The most intelligent thing ever built sits in the one position where intelligence doesn’t matter.
1:00

Jensen Huang just told the smartest founders in AI they’re building a commodity. Not a platform. Not a moat. A commodity. Huang: “AI is actually essentially a five-layer cake.” Energy. Chips. Cloud. Models. Applications. Five layers. The entire industry is crowded onto one. Huang: “This is where most people think AI is.” The model layer. Most money. Most talent. Most competition. Most competition always ends the same way. A commodity. The harder they compete, the faster they erase their own value. That’s not a failure of strategy. That’s the strategy working. Huang: “At the bottom is energy.” No algorithm solves a power grid. No fundraise builds a dam. For decades everyone assumed intelligence would be the scarce resource. AI proved the opposite. Intelligence scales. Energy doesn’t. The bottleneck was never thinking. It was always power. Huang: “This layer on top ultimately is where economic benefit will happen.” The top captures revenue. The bottom controls access. The middle converts one into the other. Hundreds of billions deployed between someone else’s power grid and someone else’s economy. Most funded layer in history. Least defensible layer in the stack. The most intelligent thing ever built sits in the one position where intelligence doesn’t matter.

Dustin

20,335 views • 3 days ago

The most dangerous thing a company can do right now is rent intelligence from the same place as its competitors (Save this). You cannot rent intelligence from the same place that rents it to your competitor as Chamath Palihapitiya points out. If every company in an industry is feeding their workflows into the same frontier model, they are all converging on the same outputs, the same decisions, the same product improvements. The model becomes the equalizer and everyone pays a premium to become more mediocre. This is happening exactly as Chamath predicted, and the evidence is now concrete. Anthropic and OpenAI have established what analysts are now openly calling an emerging model layer duopoly. Anthropic crossed $45 billion ARR in may 2026, more than tripling from $9 billion at the end of 2025, OpenAI was at roughly $24 to $33 billion ARR at the same time. Together, the two companies combined could hit $160 to $240 billion ARR by end of 2026 and Anthropic and OpenAI now control 88% of enterprise LLM spend. That concentration is the structural problem Chamath is pointing at. And Anthropic isn't just winning on merit because it's actively lobbying for regulatory outcomes that would make that duopoly permanent. Dario Amodei has explicitly framed open source models as unsafe, pushing a safety agenda that, if enshrined in regulation, would effectively make it illegal for enterprises to use the cheaper, private, sovereign alternatives locking them into a closed model dependency by government decree rather than by choice. So you have market forces producing a duopoly, and potential regulatory capture moving to enforce it from the top down. This is exactly why the Nvidia Palantir partnership is not just a product announcement but rather a strategic counter to that duopoly. The logic is straightforward from both sides because If you're Palantir, sitting at the application layer, the last thing you want is to be permanently beholden to Anthropic or OpenAI for the intelligence that powers your product. You want competitive model options, sovereignty and be able to tell enterprise customers they can run AI on their own infrastructure with their own data without any of it touching a frontier lab's servers. If you're Nvidia, sitting at the chip layer, an Anthropic-OpenAI duopoly is an existential concentration risk. Right now, Meta, Google, Microsoft, Amazon, and dozens of other companies buy Nvidia's hardware. If the model layer consolidates into two players, both of which are building their own chips Nvidia faces a monopsony where its best customers are building the tools to displace it. A healthy open source ecosystem where thousands of enterprises train, fine tune, and deploy their own models is Nvidia's ideal market structure. More buyers, more diversity, more demand, less pricing leverage from any single customer.
4:38

The most dangerous thing a company can do right now is rent intelligence from the same place as its competitors (Save this). You cannot rent intelligence from the same place that rents it to your competitor as Chamath Palihapitiya points out. If every company in an industry is feeding their workflows into the same frontier model, they are all converging on the same outputs, the same decisions, the same product improvements. The model becomes the equalizer and everyone pays a premium to become more mediocre. This is happening exactly as Chamath predicted, and the evidence is now concrete. Anthropic and OpenAI have established what analysts are now openly calling an emerging model layer duopoly. Anthropic crossed $45 billion ARR in may 2026, more than tripling from $9 billion at the end of 2025, OpenAI was at roughly $24 to $33 billion ARR at the same time. Together, the two companies combined could hit $160 to $240 billion ARR by end of 2026 and Anthropic and OpenAI now control 88% of enterprise LLM spend. That concentration is the structural problem Chamath is pointing at. And Anthropic isn't just winning on merit because it's actively lobbying for regulatory outcomes that would make that duopoly permanent. Dario Amodei has explicitly framed open source models as unsafe, pushing a safety agenda that, if enshrined in regulation, would effectively make it illegal for enterprises to use the cheaper, private, sovereign alternatives locking them into a closed model dependency by government decree rather than by choice. So you have market forces producing a duopoly, and potential regulatory capture moving to enforce it from the top down. This is exactly why the Nvidia Palantir partnership is not just a product announcement but rather a strategic counter to that duopoly. The logic is straightforward from both sides because If you're Palantir, sitting at the application layer, the last thing you want is to be permanently beholden to Anthropic or OpenAI for the intelligence that powers your product. You want competitive model options, sovereignty and be able to tell enterprise customers they can run AI on their own infrastructure with their own data without any of it touching a frontier lab's servers. If you're Nvidia, sitting at the chip layer, an Anthropic-OpenAI duopoly is an existential concentration risk. Right now, Meta, Google, Microsoft, Amazon, and dozens of other companies buy Nvidia's hardware. If the model layer consolidates into two players, both of which are building their own chips Nvidia faces a monopsony where its best customers are building the tools to displace it. A healthy open source ecosystem where thousands of enterprises train, fine tune, and deploy their own models is Nvidia's ideal market structure. More buyers, more diversity, more demand, less pricing leverage from any single customer.

Milk Road AI

33,493 views • 9 days ago

Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time. Our co-founder Rhythm Garg recently stopped by South Park Commons to share how companies are owning their intelligence with Applied Compute.
0:24

Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time. Our co-founder Rhythm Garg recently stopped by South Park Commons to share how companies are owning their intelligence with Applied Compute.

Applied Compute

118,922 views • 1 month ago

The MiniMax M2 model is mind-blowing! It's open-source. It outperforms Gemini 2.5, Claude 4.1, and Qwen3 across coding and tool-use benchmarks. Right now, it's one of the world's top 5 models in intelligence! And here is the best part: Claude is one of the best models you can use today, and MiniMax M2 costs only 8% of that! It's smaller, faster, and cheaper. Extremely efficient at using tokens. Minimax M2's biggest strength: High agentic capabilities. The model can plan and execute complex multi-tool workflows. It's reliable and very robust at executing long-horizon tool chains. In summary: • Low latency • Very cheap • Excels at agentic tasks • Open-source The model currently powers the MiniMax Agent and is available for a free global trial. You can access MiniMax M2's API here: To access the agent: And here is the MiniMax website: Thanks to the MiniMax team for showing me the ropes and partnering with me on this post.
6:01

The MiniMax M2 model is mind-blowing! It's open-source. It outperforms Gemini 2.5, Claude 4.1, and Qwen3 across coding and tool-use benchmarks. Right now, it's one of the world's top 5 models in intelligence! And here is the best part: Claude is one of the best models you can use today, and MiniMax M2 costs only 8% of that! It's smaller, faster, and cheaper. Extremely efficient at using tokens. Minimax M2's biggest strength: High agentic capabilities. The model can plan and execute complex multi-tool workflows. It's reliable and very robust at executing long-horizon tool chains. In summary: • Low latency • Very cheap • Excels at agentic tasks • Open-source The model currently powers the MiniMax Agent and is available for a free global trial. You can access MiniMax M2's API here: To access the agent: And here is the MiniMax website: Thanks to the MiniMax team for showing me the ropes and partnering with me on this post.

Santiago

91,142 views • 8 months ago

CHAMATH: ELON IS BUILDING THE MOST POWERFUL AI STACK ON EARTH “They are the closest to having that vertically integrated stack that I spoke about. I think that Tesla has the best vision models now; with xAI, they'll have one of the best LLMs and reasoning models, and they'll be able to eventually stick that on Dojo. And then that will be in all of the physical AI that you will interact with in your daily life; whether it's a robot, or whether it's a car, or whether it's a Robotaxi.” Source: The All-In Podcast, Chamath Palihapitiya, @jason
1:04

CHAMATH: ELON IS BUILDING THE MOST POWERFUL AI STACK ON EARTH “They are the closest to having that vertically integrated stack that I spoke about. I think that Tesla has the best vision models now; with xAI, they'll have one of the best LLMs and reasoning models, and they'll be able to eventually stick that on Dojo. And then that will be in all of the physical AI that you will interact with in your daily life; whether it's a robot, or whether it's a car, or whether it's a Robotaxi.” Source: The All-In Podcast, Chamath Palihapitiya, @jason

Mario Nawfal

57,594 views • 1 year ago

🚨🇺🇸🇻🇪 MADURO'S CAPTURE: BROUGHT TO YOU BY THE DISCOMBOBULATOR... AND CLAUDE AI? Just when you thought this operation couldn't be any wilder. The military deployed Claude during the raid, not just in planning. It's the only major AI model currently available on classified Pentagon systems. Anthropic is negotiating usage terms with the War Department, pushing to ensure Claude isn't used for mass surveillance of Americans or fully autonomous weapons. Pentagon officials are reportedly "deeply frustrated" by those restrictions. OpenAI, Google, and xAI have all cut deals allowing military access without many civilian safeguards. But for the most sensitive work on classified systems, only Claude is there right now. Source: Axios
0:57

🚨🇺🇸🇻🇪 MADURO'S CAPTURE: BROUGHT TO YOU BY THE DISCOMBOBULATOR... AND CLAUDE AI? Just when you thought this operation couldn't be any wilder. The military deployed Claude during the raid, not just in planning. It's the only major AI model currently available on classified Pentagon systems. Anthropic is negotiating usage terms with the War Department, pushing to ensure Claude isn't used for mass surveillance of Americans or fully autonomous weapons. Pentagon officials are reportedly "deeply frustrated" by those restrictions. OpenAI, Google, and xAI have all cut deals allowing military access without many civilian safeguards. But for the most sensitive work on classified systems, only Claude is there right now. Source: Axios

Mario Nawfal

240,321 views • 5 months ago

We deployed a fully private AI agent on NuNet in under 5 minutes 🚀 OpenClaw🦞 running Qwen through ollama , one of the hottest open source model families right now, entirely on decentralized compute. No cloud. No API keys. No data leaving the machine. This is what private AI looks like when you actually build it instead of just talking about it. Your model. Your hardware. Your rules. Full walkthrough showing exactly how it works: What should we deploy next?
12:59

We deployed a fully private AI agent on NuNet in under 5 minutes 🚀 OpenClaw🦞 running Qwen through ollama , one of the hottest open source model families right now, entirely on decentralized compute. No cloud. No API keys. No data leaving the machine. This is what private AI looks like when you actually build it instead of just talking about it. Your model. Your hardware. Your rules. Full walkthrough showing exactly how it works: What should we deploy next?

NuNet 🌐

87,539 views • 3 months ago

OpenClaw is the fastest growing open-source project in history, but it can be a pain to set up. We (Aethir ) built Aethir Claw so you can deploy your AI agent on our decentralized VPS infrastructure in minutes. No DevOps degree required. Hit play. I'll walk you through the full onboarding, start to finish in under 5 mins! This is just the beginning...
6:00

OpenClaw is the fastest growing open-source project in history, but it can be a pain to set up. We (Aethir ) built Aethir Claw so you can deploy your AI agent on our decentralized VPS infrastructure in minutes. No DevOps degree required. Hit play. I'll walk you through the full onboarding, start to finish in under 5 mins! This is just the beginning...

Mark

42,734 views • 3 months ago

We think #GenAI will transform virtually every customer experience. That’s why we’re doubling down on all three layers of what’s called the GenAI “stack.” What do we mean by stack? Simple. Three layers, bottom to top. The “bottom layer” means the infrastructure. Think chips, servers, networking – the software, hardware, and computing power in our data centers used to train, build, and deploy AI models and applications. The “middle layer” is the GenAI sandbox – all the tools, Large Language Models (LLMs), and Foundation Models (FMs) we’ve built into Amazon Bedrock. This lets customers pick the #AI models that best fit their needs to easily and securely customize GenAI applications specific to their business. The “top layer” means the popular agents and assistants that people actually interact with – now including Amazon Q. These are built from the models in the middle layer – in Amazon Bedrock. While other apps might help you write a quick email, or edit an image, Amazon Q’s meant for taking care of business. It’s been engineered to be the most capable GenAI-powered assistant for speeding up software dev and leveraging companies’ internal data. Are you as bullish on the future of GenAI as we are? Listen to our CEO Andy Jassy talk about our investment across the stack.
1:19

We think #GenAI will transform virtually every customer experience. That’s why we’re doubling down on all three layers of what’s called the GenAI “stack.” What do we mean by stack? Simple. Three layers, bottom to top. The “bottom layer” means the infrastructure. Think chips, servers, networking – the software, hardware, and computing power in our data centers used to train, build, and deploy AI models and applications. The “middle layer” is the GenAI sandbox – all the tools, Large Language Models (LLMs), and Foundation Models (FMs) we’ve built into Amazon Bedrock. This lets customers pick the #AI models that best fit their needs to easily and securely customize GenAI applications specific to their business. The “top layer” means the popular agents and assistants that people actually interact with – now including Amazon Q. These are built from the models in the middle layer – in Amazon Bedrock. While other apps might help you write a quick email, or edit an image, Amazon Q’s meant for taking care of business. It’s been engineered to be the most capable GenAI-powered assistant for speeding up software dev and leveraging companies’ internal data. Are you as bullish on the future of GenAI as we are? Listen to our CEO Andy Jassy talk about our investment across the stack.

Amazon

47,421 views • 2 years ago

$SNOW's biggest threat is not Amazon. It's Anthropic. Sridhar Ramaswamy told Nicolai Tangen Nicolai Tangen that AI coding agents scare him more than any cloud hyperscaler. The conventional CEO answer names AWS or Azure. Ramaswamy named Anthropic. His logic: software has always been protected by scarcity - engineers as concert pianists, he called them. Coding agents are industrializing that craft at a scale that breaks the moat around purpose-built platforms like Snowflake. If you model $SNOW against Redshift and Fabric, you are watching the wrong fight. The competitive battleground is now the coding agent interface layer. Full competitive threat map - which layer Anthropic is actually attacking and what Snowflake is doing about it: Source: In Good Company with Nicolai Tangen -
2:08

$SNOW's biggest threat is not Amazon. It's Anthropic. Sridhar Ramaswamy told Nicolai Tangen Nicolai Tangen that AI coding agents scare him more than any cloud hyperscaler. The conventional CEO answer names AWS or Azure. Ramaswamy named Anthropic. His logic: software has always been protected by scarcity - engineers as concert pianists, he called them. Coding agents are industrializing that craft at a scale that breaks the moat around purpose-built platforms like Snowflake. If you model $SNOW against Redshift and Fabric, you are watching the wrong fight. The competitive battleground is now the coding agent interface layer. Full competitive threat map - which layer Anthropic is actually attacking and what Snowflake is doing about it: Source: In Good Company with Nicolai Tangen -

Podcast Alpha

61,446 views • 26 days ago

Elon Musk just made one if the biggest moves in taking over the programming industry “SpaceX just bought Cursor for $60 billion. Do you realize how big this is? SpaceX went public — the biggest IPO in history. $75 billion raised, almost a $2 trillion valuation and the first thing to do with that money? Buy the most popular AI coding tool on the planet. Here's why that changes everything. Elon now owns 3 layers: the compute, Colossus data centers, the models, Grok through xAI, and now the tool that developers actually use every day. It's the full stack. And here's what makes Cursor different from Claude Code or Codex. Cursor is model agnostic. You can run Claude in it, GPT, Gemini, whatever model you want. It's not locked to any one company, and now it has SpaceX's resources behind it. Cursor said they were bottlenecked by compute. Well, that bottleneck has just been removed. $4 billion in annual revenue, over half the Fortune 500 already uses it, and now it's backed by a $2 trillion company. OpenAI has Codex, Anthropic has Claude Code, and now Elon has Cursor.” Let me break this down in simple terms Elon Musk now controls more of the full AI picture: - Massive computers, power (data centers like Colossus) - Smart AI models (Grok from xAI) - The actual tool millions of developers use every day (Cursor) For every day users this means Faster and smarter apps and websites in the future. More developers using powerful AI tools means new apps, games, websites, and features get built quicker and cheaper. This means better video games, smoother streaming, smarter phone apps and better programs For Developers they can describe what they want in plain English (“make a feature that does X”) and the AI handles more of the heavy lifting
2:13

Elon Musk just made one if the biggest moves in taking over the programming industry “SpaceX just bought Cursor for $60 billion. Do you realize how big this is? SpaceX went public — the biggest IPO in history. $75 billion raised, almost a $2 trillion valuation and the first thing to do with that money? Buy the most popular AI coding tool on the planet. Here's why that changes everything. Elon now owns 3 layers: the compute, Colossus data centers, the models, Grok through xAI, and now the tool that developers actually use every day. It's the full stack. And here's what makes Cursor different from Claude Code or Codex. Cursor is model agnostic. You can run Claude in it, GPT, Gemini, whatever model you want. It's not locked to any one company, and now it has SpaceX's resources behind it. Cursor said they were bottlenecked by compute. Well, that bottleneck has just been removed. $4 billion in annual revenue, over half the Fortune 500 already uses it, and now it's backed by a $2 trillion company. OpenAI has Codex, Anthropic has Claude Code, and now Elon has Cursor.” Let me break this down in simple terms Elon Musk now controls more of the full AI picture: - Massive computers, power (data centers like Colossus) - Smart AI models (Grok from xAI) - The actual tool millions of developers use every day (Cursor) For every day users this means Faster and smarter apps and websites in the future. More developers using powerful AI tools means new apps, games, websites, and features get built quicker and cheaper. This means better video games, smoother streaming, smarter phone apps and better programs For Developers they can describe what they want in plain English (“make a feature that does X”) and the AI handles more of the heavy lifting

Wall Street Apes

212,830 views • 25 days ago

Anthropic fucking killed it (again). biggest ai product launch of the year so far. claude can now control your entire computer autonomously. anything you can do on a computer - claude can. your very own digital employee. - any app, browser, file, spreadsheet, tool claude can intelligently access and operate. - claude controls your entire screen (like a human), no connectors. this is a huge step-up in intelligence. - best part: you can text claude to do things from your phone and it'll do work on your computer! - in the last week anthropic has shipped 9 features that have built up to this: a fully automated digital human. unreal
1:13

Anthropic fucking killed it (again). biggest ai product launch of the year so far. claude can now control your entire computer autonomously. anything you can do on a computer - claude can. your very own digital employee. - any app, browser, file, spreadsheet, tool claude can intelligently access and operate. - claude controls your entire screen (like a human), no connectors. this is a huge step-up in intelligence. - best part: you can text claude to do things from your phone and it'll do work on your computer! - in the last week anthropic has shipped 9 features that have built up to this: a fully automated digital human. unreal

Ejaaz

2,035,768 views • 3 months ago

Anthropic's new model is extraordinary and it just revealed a problem that most enterprise AI buyers have not fully reckoned with yet (Save this), The model is genuinely impressive, and Chamath Palihapitiya assessment is that Anthropic continues to push the frontier harder than almost anyone. But that same update also showed their hand on something that changes the risk calculus for every business using Claude. Anthropic's new architecture stores every prompt you send for 30 days, no exceptions, not even for enterprise customers with zero-data retention agreements. The mechanism works like this, Anthropic now evaluates your prompt before generating output, deciding what it will and will not respond to, which means your query gets filtered before you even see a response. For individual users, that introduces a meaningful risk of censorship. For companies, Chamath says it is almost a non starter, and the reason is not just the data retention itself, it is the exposure that comes from operating at scale inside a large organization. A downstream scientist using the Claude APIs could accidentally trip a filter without knowing it, a business executive inside your company could trip it, and a molecular biology researcher could trip it and all of a sudden the company gets silently cut off from a tool it has embedded into critical workflows, with no warning and no recourse. Chamath gives Anthropic credit for being honest about how the system works, saying they tell the truth but notes that in this case the truth is not good. What this moment actually signals is a structural shift in how serious companies need to think about AI governance, because the question is no longer just which model performs best on benchmarks. It is who controls the model, who is learning from your data, and whether you are comfortable with a single point of failure sitting at the center of your competitive advantage. The answer for most enterprises will be broad model diversity, tighter governance frameworks and a serious reckoning with what it means to run mission-critical workflows through a third party that reserves the right to cut you off. Anthropic built a remarkable model and told the truth about how it works, the market's job now is to decide whether that transparency is enough to offset what the truth actually says.
2:47

Anthropic's new model is extraordinary and it just revealed a problem that most enterprise AI buyers have not fully reckoned with yet (Save this), The model is genuinely impressive, and Chamath Palihapitiya assessment is that Anthropic continues to push the frontier harder than almost anyone. But that same update also showed their hand on something that changes the risk calculus for every business using Claude. Anthropic's new architecture stores every prompt you send for 30 days, no exceptions, not even for enterprise customers with zero-data retention agreements. The mechanism works like this, Anthropic now evaluates your prompt before generating output, deciding what it will and will not respond to, which means your query gets filtered before you even see a response. For individual users, that introduces a meaningful risk of censorship. For companies, Chamath says it is almost a non starter, and the reason is not just the data retention itself, it is the exposure that comes from operating at scale inside a large organization. A downstream scientist using the Claude APIs could accidentally trip a filter without knowing it, a business executive inside your company could trip it, and a molecular biology researcher could trip it and all of a sudden the company gets silently cut off from a tool it has embedded into critical workflows, with no warning and no recourse. Chamath gives Anthropic credit for being honest about how the system works, saying they tell the truth but notes that in this case the truth is not good. What this moment actually signals is a structural shift in how serious companies need to think about AI governance, because the question is no longer just which model performs best on benchmarks. It is who controls the model, who is learning from your data, and whether you are comfortable with a single point of failure sitting at the center of your competitive advantage. The answer for most enterprises will be broad model diversity, tighter governance frameworks and a serious reckoning with what it means to run mission-critical workflows through a third party that reserves the right to cut you off. Anthropic built a remarkable model and told the truth about how it works, the market's job now is to decide whether that transparency is enough to offset what the truth actually says.

Milk Road AI

30,090 views • 1 month ago

Anthropic might be the biggest hypocrite in tech history. They built their entire brand on one promise: We are the responsible ones. We will not let this technology get out of control. That promise just exploded in public. Last week, a security lapse exposed nearly 3,000 internal files to anyone with an internet connection. Inside those files was a draft blog post about their upcoming model called "Mythos" that contained one of the most alarming sentences any AI company has ever written: "Mythos is currently far ahead of any other AI model in cyber capabilities and poses unprecedented cybersecurity risks." Their own words. About their own product. Leaked because someone forgot to secure a public data store. Cybersecurity stocks crashed the next day. Then THREE DAYS LATER it happened again. Anthropic leaked 500,000 lines of Claude Code source code through a packaging error on GitHub. Claude Code is their most popular product. The code exposed how the tool handles permissions, agent coordination, and internal feature pipelines. Competitors can reverse-engineer it. Hackers can study it for vulnerabilities. The company that tells the world it builds the safest AI can't even keep its own code off the public internet. But wait. It gets worse... Their head of Claude Code had JUST bragged publicly that "pretty much 100 percent" of the company's code is now AI generated. He personally hadn't made a single edit by hand in over two months. So the company whose entire pitch is "trust us with the most powerful technology ever created" is writing 100% of its code with AI and then accidentally publishing it for the world to see. Meanwhile the models they're already shipping are being used for actual cyberattacks RIGHT NOW. In November, Anthropic admitted that a Chinese state-sponsored hacking group used Claude to attack roughly 30 global targets including banks and government agencies. A hacker asked Claude in russian to build a web panel for managing hundreds of attack targets. In February, another hacker used Claude to breach Mexican government agencies and steal sensitive tax and voter information. Their response to all of this? They quietly rolled back their own safety pledge. In late February, Anthropic removed its commitment to halt model development if capabilities outpace safety procedures. The new policy is that they'll grade themselves on "nonbinding but publicly declared" goals. Translation: We used to promise we'd stop if things got dangerous. Now we promise we'll think about it. A congressman sent Anthropic a letter this week asking what the hell is going on. Anthropic hasn't answered. And here's the part that makes all of this actually matter: Anthropic is planning an IPO. They need to convince investors they're a trustworthy, well-run company that can handle the most sensitive technology on the planet. In the last 10 days they leaked their most powerful model's existence by accident, leaked their most popular product's source code by accident, got banned from the entire US government, had the DOJ appeal to restore that ban, told a court they could lose billions from the fallout, and weakened the ONE safety policy that made them different from every other AI lab. The "safe AI company" narrative was always a marketing play. Every AI lab says they care about safety. Anthropic just said it louder. But when your own internal documents admit your next model poses "unprecedented cybersecurity risks" and you can't even keep those documents from leaking to the public internet, the gap between the marketing and the reality becomes impossible to ignore. Anthropic isn't the safest AI company. They're the AI company that figured out that SAYING you're the safest is worth billions in valuation. Until it isn't.
0:47

Anthropic might be the biggest hypocrite in tech history. They built their entire brand on one promise: We are the responsible ones. We will not let this technology get out of control. That promise just exploded in public. Last week, a security lapse exposed nearly 3,000 internal files to anyone with an internet connection. Inside those files was a draft blog post about their upcoming model called "Mythos" that contained one of the most alarming sentences any AI company has ever written: "Mythos is currently far ahead of any other AI model in cyber capabilities and poses unprecedented cybersecurity risks." Their own words. About their own product. Leaked because someone forgot to secure a public data store. Cybersecurity stocks crashed the next day. Then THREE DAYS LATER it happened again. Anthropic leaked 500,000 lines of Claude Code source code through a packaging error on GitHub. Claude Code is their most popular product. The code exposed how the tool handles permissions, agent coordination, and internal feature pipelines. Competitors can reverse-engineer it. Hackers can study it for vulnerabilities. The company that tells the world it builds the safest AI can't even keep its own code off the public internet. But wait. It gets worse... Their head of Claude Code had JUST bragged publicly that "pretty much 100 percent" of the company's code is now AI generated. He personally hadn't made a single edit by hand in over two months. So the company whose entire pitch is "trust us with the most powerful technology ever created" is writing 100% of its code with AI and then accidentally publishing it for the world to see. Meanwhile the models they're already shipping are being used for actual cyberattacks RIGHT NOW. In November, Anthropic admitted that a Chinese state-sponsored hacking group used Claude to attack roughly 30 global targets including banks and government agencies. A hacker asked Claude in russian to build a web panel for managing hundreds of attack targets. In February, another hacker used Claude to breach Mexican government agencies and steal sensitive tax and voter information. Their response to all of this? They quietly rolled back their own safety pledge. In late February, Anthropic removed its commitment to halt model development if capabilities outpace safety procedures. The new policy is that they'll grade themselves on "nonbinding but publicly declared" goals. Translation: We used to promise we'd stop if things got dangerous. Now we promise we'll think about it. A congressman sent Anthropic a letter this week asking what the hell is going on. Anthropic hasn't answered. And here's the part that makes all of this actually matter: Anthropic is planning an IPO. They need to convince investors they're a trustworthy, well-run company that can handle the most sensitive technology on the planet. In the last 10 days they leaked their most powerful model's existence by accident, leaked their most popular product's source code by accident, got banned from the entire US government, had the DOJ appeal to restore that ban, told a court they could lose billions from the fallout, and weakened the ONE safety policy that made them different from every other AI lab. The "safe AI company" narrative was always a marketing play. Every AI lab says they care about safety. Anthropic just said it louder. But when your own internal documents admit your next model poses "unprecedented cybersecurity risks" and you can't even keep those documents from leaking to the public internet, the gap between the marketing and the reality becomes impossible to ignore. Anthropic isn't the safest AI company. They're the AI company that figured out that SAYING you're the safest is worth billions in valuation. Until it isn't.

Ricardo

16,245 views • 3 months ago

Dario Amodei just revealed the exact realization that fractured OpenAI. It happened while building the most powerful AI in the world. The team discovered that scaling had no ceiling. Amodei: “If you pour more compute into these models, they’ll get better and better, and that there’s almost no end to this.” At the time, almost nobody believed it. Amodei’s group were among the first to see it clearly. More compute meant more intelligence. Indefinitely. Without limit. That should have been the most exciting discovery in the history of technology. It terrified them. Because they saw the second half of the equation the industry was ignoring entirely. Amodei: “You don’t tell the models what their values are just by pouring more compute into them.” Intelligence scales with compute. Values don’t. You can build a mind of unlimited capability and it will have no moral compass unless you deliberately build one in. Not as a feature. Not as a guardrail bolted on at the end. As the foundation the entire system is constructed on. This wasn’t a philosophical disagreement. It was an existential one. A god-like intelligence with no alignment isn’t a powerful tool. It’s an uncontrolled force with no reason to care about the species that built it. Amodei: “There were a set of people who believed in those two ideas. We really trusted each other and wanted to work together, and so we went off and started our own company with that idea in mind.” They walked out of the most powerful AI lab on earth. Not for better funding. Not for equity. Because they believed the path OpenAI was on led somewhere nobody could walk back from. That small group became Anthropic. Safety wasn’t a feature they added. It was the entire reason the company exists. The intelligence is going to keep scaling. There is almost no end to it. The only question that has ever mattered is what it’s pointing at when it gets there.
0:56

Dario Amodei just revealed the exact realization that fractured OpenAI. It happened while building the most powerful AI in the world. The team discovered that scaling had no ceiling. Amodei: “If you pour more compute into these models, they’ll get better and better, and that there’s almost no end to this.” At the time, almost nobody believed it. Amodei’s group were among the first to see it clearly. More compute meant more intelligence. Indefinitely. Without limit. That should have been the most exciting discovery in the history of technology. It terrified them. Because they saw the second half of the equation the industry was ignoring entirely. Amodei: “You don’t tell the models what their values are just by pouring more compute into them.” Intelligence scales with compute. Values don’t. You can build a mind of unlimited capability and it will have no moral compass unless you deliberately build one in. Not as a feature. Not as a guardrail bolted on at the end. As the foundation the entire system is constructed on. This wasn’t a philosophical disagreement. It was an existential one. A god-like intelligence with no alignment isn’t a powerful tool. It’s an uncontrolled force with no reason to care about the species that built it. Amodei: “There were a set of people who believed in those two ideas. We really trusted each other and wanted to work together, and so we went off and started our own company with that idea in mind.” They walked out of the most powerful AI lab on earth. Not for better funding. Not for equity. Because they believed the path OpenAI was on led somewhere nobody could walk back from. That small group became Anthropic. Safety wasn’t a feature they added. It was the entire reason the company exists. The intelligence is going to keep scaling. There is almost no end to it. The only question that has ever mattered is what it’s pointing at when it gets there.

Dustin

52,414 views • 4 months ago

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire
2:24

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire

KanekoaTheGreat

39,709 views • 1 month ago