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Google just made every $50K master's degree look like a scam. They dropped "Google Skills" - 3,000+ AI courses from DeepMind, Cloud, and Google Education in one platform. And it's 100% FREE for Google Cloud users. The same content universities charge $60K for: - DeepMind's actual AI research training...

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Nozz

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568,815 次观看 • 9 个月前 •via X (Twitter)

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🚨 Big news: Google just launched Google Skills... giving you access to the same content universities charge $50K+ is now open to everyone. Here’s how it works: - Go to - Pick any AI skill you want to learn - Learn through 700+ hands-on labs with real Google Cloud tools -Earn Google Skill Badges to showcase your expertise ... recruiters actively look for these - Work toward certifications that rank among the highest-paying in IT What’s inside: - 3,000+ AI courses from Google Cloud, DeepMind & Google Edu - $500 in free cloud credits to practice - Built-in Gemini Code Assist - Certificates employers actually recognize (82% hiring preference) Like, REPOST
0:29

🚨 Big news: Google just launched Google Skills... giving you access to the same content universities charge $50K+ is now open to everyone. Here’s how it works: - Go to - Pick any AI skill you want to learn - Learn through 700+ hands-on labs with real Google Cloud tools -Earn Google Skill Badges to showcase your expertise ... recruiters actively look for these - Work toward certifications that rank among the highest-paying in IT What’s inside: - 3,000+ AI courses from Google Cloud, DeepMind & Google Edu - $500 in free cloud credits to practice - Built-in Gemini Code Assist - Certificates employers actually recognize (82% hiring preference) Like, REPOST

Beginnersblog

142,523 次观看 • 9 个月前

There's no way this is free. Anthropic just put 20+ courses on using AI for $0 These are the official Anthropic courses for learning Claude and Claude Code. 20 courses that take you from zero to building real, complex things. Link: You'll find everything there: from AI basics, to advanced skills like building with MCP, the API, AWS, agents, and a lot more. And it's not just lectures. There are hands-on lessons where you practice what you learned. After each one, you get a certificate you can add to your LinkedIn, the kind that sets you apart from people who don't have it. Now you've got no excuse left for not knowing how to use AI. Bookmark this
1:21

There's no way this is free. Anthropic just put 20+ courses on using AI for $0 These are the official Anthropic courses for learning Claude and Claude Code. 20 courses that take you from zero to building real, complex things. Link: You'll find everything there: from AI basics, to advanced skills like building with MCP, the API, AWS, agents, and a lot more. And it's not just lectures. There are hands-on lessons where you practice what you learned. After each one, you get a certificate you can add to your LinkedIn, the kind that sets you apart from people who don't have it. Now you've got no excuse left for not knowing how to use AI. Bookmark this

Yarchi

15,915 次观看 • 18 天前

Google just acquired an Israeli Trojan horse to STEAL clients from AWS and Microsoft. $32 billion. All cash. For a cybersecurity startup called Wiz. It’s the largest acquisition in Google’s history. But nobody’s talking about what they ACTUALLY bought... Here’s why this is way bigger than you think: Wiz protects over half the Fortune 100. Their clients run on AWS, Azure, Google Cloud, and Oracle. The platform scans every workload, every vulnerability, every misconfiguration across ALL of those clouds. Meaning Wiz has a god-level view of how the world's biggest companies use their competitors' infrastructure. And Google just bought that view for $32 billion. Now think about what Google Cloud's biggest problem has been for YEARS... They're stuck in third place. 13% market share. AWS has 30%. Azure has 20%. Google has been hemorrhaging money trying to close that gap and nothing has worked. Wiz changes that equation overnight. Because Wiz doesn't just protect cloud environments. It MAPS them. It knows which companies are running what workloads, where their vulnerabilities are, and where they're overpaying. Google now has a real-time blueprint of its competitors' biggest customers. And it gets crazier: The 4 founders of Wiz previously built Adallom, a cloud security startup that Microsoft acquired for $320 million in 2015. After that acquisition, those same founders ran Microsoft's entire Azure Cloud Security Group. They literally built the security infrastructure that Azure runs on today. Then they left. Started Wiz. Built a product that works across every cloud. Got 45% of the Fortune 100 as customers. Most of those customers are on AWS and Azure. And now they just handed ALL of that to Google. Google promised Wiz will remain "multi-cloud" and continue working with AWS, Azure, and Oracle. That's the public story. But here's the game theory every enterprise CTO is thinking about right now: If you're running sensitive workloads on AWS or Azure and your security layer is now owned by your competitor, how comfortable are you? Google doesn't need to do anything shady. The PERCEPTION alone is enough to start shifting enterprise decisions. And that's worth way more than $32 billion. But there's another layer... Wiz went from $0 to $100 million in revenue in 18 months. Fastest software company in history to hit that mark. By 2025, they were at $750 million. The founders said no to Google's first offer of $23 billion in 2024 because they wanted to IPO. 9 months later, they said yes to $32 billion. What changed? The IPO market collapsed. Tech IPOs dried up. Valuations got slashed. Wiz's leadership looked at the math and realized $32 billion in guaranteed cash beats an uncertain public offering in a hostile market. Google paid a 39% premium over the rejected offer. A multiple of 45-65x revenue. For a company founded 5 years ago by 4 guys who met in Israeli military intelligence. This is the BIGGEST tech acquisition of an Israeli-founded company ever. Bigger than Intel buying Mobileye for $15.3 billion. Bigger than anything in Israeli tech history. And Google is betting it will be worth every penny. Because the cloud war isn't about compute anymore. It's about TRUST. And the company that controls the security layer controls where enterprises put their most sensitive data. Google just bought the keys to every major cloud customer on the planet. The question is whether AWS and Microsoft let them keep using those keys. What do you think?
1:06

Google just acquired an Israeli Trojan horse to STEAL clients from AWS and Microsoft. $32 billion. All cash. For a cybersecurity startup called Wiz. It’s the largest acquisition in Google’s history. But nobody’s talking about what they ACTUALLY bought... Here’s why this is way bigger than you think: Wiz protects over half the Fortune 100. Their clients run on AWS, Azure, Google Cloud, and Oracle. The platform scans every workload, every vulnerability, every misconfiguration across ALL of those clouds. Meaning Wiz has a god-level view of how the world's biggest companies use their competitors' infrastructure. And Google just bought that view for $32 billion. Now think about what Google Cloud's biggest problem has been for YEARS... They're stuck in third place. 13% market share. AWS has 30%. Azure has 20%. Google has been hemorrhaging money trying to close that gap and nothing has worked. Wiz changes that equation overnight. Because Wiz doesn't just protect cloud environments. It MAPS them. It knows which companies are running what workloads, where their vulnerabilities are, and where they're overpaying. Google now has a real-time blueprint of its competitors' biggest customers. And it gets crazier: The 4 founders of Wiz previously built Adallom, a cloud security startup that Microsoft acquired for $320 million in 2015. After that acquisition, those same founders ran Microsoft's entire Azure Cloud Security Group. They literally built the security infrastructure that Azure runs on today. Then they left. Started Wiz. Built a product that works across every cloud. Got 45% of the Fortune 100 as customers. Most of those customers are on AWS and Azure. And now they just handed ALL of that to Google. Google promised Wiz will remain "multi-cloud" and continue working with AWS, Azure, and Oracle. That's the public story. But here's the game theory every enterprise CTO is thinking about right now: If you're running sensitive workloads on AWS or Azure and your security layer is now owned by your competitor, how comfortable are you? Google doesn't need to do anything shady. The PERCEPTION alone is enough to start shifting enterprise decisions. And that's worth way more than $32 billion. But there's another layer... Wiz went from $0 to $100 million in revenue in 18 months. Fastest software company in history to hit that mark. By 2025, they were at $750 million. The founders said no to Google's first offer of $23 billion in 2024 because they wanted to IPO. 9 months later, they said yes to $32 billion. What changed? The IPO market collapsed. Tech IPOs dried up. Valuations got slashed. Wiz's leadership looked at the math and realized $32 billion in guaranteed cash beats an uncertain public offering in a hostile market. Google paid a 39% premium over the rejected offer. A multiple of 45-65x revenue. For a company founded 5 years ago by 4 guys who met in Israeli military intelligence. This is the BIGGEST tech acquisition of an Israeli-founded company ever. Bigger than Intel buying Mobileye for $15.3 billion. Bigger than anything in Israeli tech history. And Google is betting it will be worth every penny. Because the cloud war isn't about compute anymore. It's about TRUST. And the company that controls the security layer controls where enterprises put their most sensitive data. Google just bought the keys to every major cloud customer on the planet. The question is whether AWS and Microsoft let them keep using those keys. What do you think?

Ricardo

188,909 次观看 • 4 个月前

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!
3:50

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!

Workshop AI

28,477 次观看 • 4 个月前

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.
1:42

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

26,668 次观看 • 1 个月前

Google is making $62 billion a quarter destroying the websites it NEEDS to survive. This is literally a death spiral that ends with Google killing itself. Let me explain what's going on... Google added AI summaries to the top of every search result in 2024. When you Google something now, the answer sits right there on Google's page. You never have to click anywhere. Google took the information from someone else's website, summarized it, and kept you inside Google's ecosystem. The result: 60% of all Google searches now end without a single click to any website. Small publishers lost 60% of their traffic in one year. Medium publishers lost 47%. Even the biggest names in media, the New York Times, the Washington Post, Business Insider, all saw traffic fall between 22% and 55%. The Axios CEO called it "a referral extinction event for the ad-supported web." Google's response to all of this was to tell publishers they can "opt out" of having their content summarized. But opting out also REMOVES your description from normal search results. So the choice Google gives you is let us steal your content for free, or become invisible on the internet. That's extortion. The Washington Post laid off another round of journalists this year because of it. Stereogum, one of the most respected music publications on the internet, had to BEG readers for donations. Business Insider cut 21% of its staff. Dozens of smaller publishers have shut down entirely. The people who actually CREATE the information Google summarizes are going bankrupt while Google posts record revenue. But here's where this gets interesting and where everyone stops thinking: Google's AI summaries are only as good as the content they summarize. If the publishers who write the original articles, run the original investigations, and create the original data go out of business, there is nothing left for Google to summarize. The AI starts recycling old information, the answers get stale, the quality drops, and users start noticing that Google's summaries are increasingly wrong, outdated, or useless. Google is essentially strip-mining the internet for short-term revenue. They are extracting all the value from content creators without paying for it, driving those creators out of business, and then wondering why the quality of their own product is declining. This is exactly what Napster did to the music industry in the early 2000s: Made content free, creators went broke, and quality collapsed. It took a decade to rebuild. Google is doing the same thing to the entire internet at 100x the scale. Rolling Stone, Variety, Deadline, The Hollywood Reporter, and Billboard are now suing Google for antitrust violations. Chegg, the education platform, lost 49% of its traffic and is suing too. The UK's competition authority just ordered Google to let publishers opt out without being punished. The DOJ already ruled Google is an illegal monopoly. And Google's defense in court is genuinely unbelievable. They argue that publishers CHOOSE to let Google index their content and can leave anytime they want. That's like saying you choose to pay protection money to the mob because technically you could close your business and move to another city. Google controls 90% of search. Leaving Google means leaving the internet. Meanwhile Google is investing billions in custom AI chips to make these summaries cheaper at scale. Every quarter the problem gets worse. The internet as we've known it for 25 years ran on a simple deal: Publishers make content. Google sends traffic. Advertisers pay for the traffic. Everyone wins. But Google just BROKE that deal and kept all the money.
4:13

Google is making $62 billion a quarter destroying the websites it NEEDS to survive. This is literally a death spiral that ends with Google killing itself. Let me explain what's going on... Google added AI summaries to the top of every search result in 2024. When you Google something now, the answer sits right there on Google's page. You never have to click anywhere. Google took the information from someone else's website, summarized it, and kept you inside Google's ecosystem. The result: 60% of all Google searches now end without a single click to any website. Small publishers lost 60% of their traffic in one year. Medium publishers lost 47%. Even the biggest names in media, the New York Times, the Washington Post, Business Insider, all saw traffic fall between 22% and 55%. The Axios CEO called it "a referral extinction event for the ad-supported web." Google's response to all of this was to tell publishers they can "opt out" of having their content summarized. But opting out also REMOVES your description from normal search results. So the choice Google gives you is let us steal your content for free, or become invisible on the internet. That's extortion. The Washington Post laid off another round of journalists this year because of it. Stereogum, one of the most respected music publications on the internet, had to BEG readers for donations. Business Insider cut 21% of its staff. Dozens of smaller publishers have shut down entirely. The people who actually CREATE the information Google summarizes are going bankrupt while Google posts record revenue. But here's where this gets interesting and where everyone stops thinking: Google's AI summaries are only as good as the content they summarize. If the publishers who write the original articles, run the original investigations, and create the original data go out of business, there is nothing left for Google to summarize. The AI starts recycling old information, the answers get stale, the quality drops, and users start noticing that Google's summaries are increasingly wrong, outdated, or useless. Google is essentially strip-mining the internet for short-term revenue. They are extracting all the value from content creators without paying for it, driving those creators out of business, and then wondering why the quality of their own product is declining. This is exactly what Napster did to the music industry in the early 2000s: Made content free, creators went broke, and quality collapsed. It took a decade to rebuild. Google is doing the same thing to the entire internet at 100x the scale. Rolling Stone, Variety, Deadline, The Hollywood Reporter, and Billboard are now suing Google for antitrust violations. Chegg, the education platform, lost 49% of its traffic and is suing too. The UK's competition authority just ordered Google to let publishers opt out without being punished. The DOJ already ruled Google is an illegal monopoly. And Google's defense in court is genuinely unbelievable. They argue that publishers CHOOSE to let Google index their content and can leave anytime they want. That's like saying you choose to pay protection money to the mob because technically you could close your business and move to another city. Google controls 90% of search. Leaving Google means leaving the internet. Meanwhile Google is investing billions in custom AI chips to make these summaries cheaper at scale. Every quarter the problem gets worse. The internet as we've known it for 25 years ran on a simple deal: Publishers make content. Google sends traffic. Advertisers pay for the traffic. Everyone wins. But Google just BROKE that deal and kept all the money.

Ricardo

250,784 次观看 • 2 个月前

Google has a Gemini Problem, and Chamath has a plan to fix it 📈 On E225, the besties discussed how Google can cut ChatGPT's lead over Gemini without killing its $200B/year search ads business. David Sacks: "I think the problem that Google has with respect to ChatGPT, is Gemini is not getting the usage, and ChatGPT is just growing like crazy." "If you look at how these models perform according to the benchmarks, Gemini is actually really good, but they have not caught up on the usage side." david friedberg: "Chamath, you're the CEO of Google, you've got a $200B run rate search ad business." "What's the right integration of Gemini such that you don't massively disrupt the search ad business overnight?" "Or do you not care and you're just gonna do it? I think that's the conundrum (Google) is dealing with." Chamath Palihapitiya: " The more difficult question is, what does the integration look like?" "They're already inserting Gemini in all kinds of uncomfortable ways." "So for example, if you use Gmail, or if you use Google Workspace, what happens today is all these random Gemini pop-ups come up all over the place." "That is an implementation that happened at way too junior a level by people that have no product taste." "And if you use the products every day, it would be hard for you to disagree with me." David Sacks: " The Google homepage, would you replace that with an AI chatbot?" Chamath Palihapitiya: " No. Here's what I would do: I would first go to the critical other points that are around, that today do not cannibalize the blue links." "If you look at the traffic patterns, almost as a Sankey diagram, the real thing you should be looking at here is where are the entry points into Google that then result in a clickable link." "And what it would show you is that there are certain places that are highly de-optimized today for revenue generating events." "They happen as a byproduct, but they don't happen as the use case." "So in that example, you would put Gmail as a critical place, the Google one subscription, and there's like five or six other places." "That's where I would put Gemini as the front door and start to habituate 300 to 500 million people a week in using that." "I think then you can figure out over time how much money you can make from all of that, or how it directs derivative revenue, and figure out what to do with Google dot com last." "But my point is, the experience in Gmail should be done today." "The experience in YouTube should be done today." "The experience in Google one should be done today."
2:00

Google has a Gemini Problem, and Chamath has a plan to fix it 📈 On E225, the besties discussed how Google can cut ChatGPT's lead over Gemini without killing its $200B/year search ads business. David Sacks: "I think the problem that Google has with respect to ChatGPT, is Gemini is not getting the usage, and ChatGPT is just growing like crazy." "If you look at how these models perform according to the benchmarks, Gemini is actually really good, but they have not caught up on the usage side." david friedberg: "Chamath, you're the CEO of Google, you've got a $200B run rate search ad business." "What's the right integration of Gemini such that you don't massively disrupt the search ad business overnight?" "Or do you not care and you're just gonna do it? I think that's the conundrum (Google) is dealing with." Chamath Palihapitiya: " The more difficult question is, what does the integration look like?" "They're already inserting Gemini in all kinds of uncomfortable ways." "So for example, if you use Gmail, or if you use Google Workspace, what happens today is all these random Gemini pop-ups come up all over the place." "That is an implementation that happened at way too junior a level by people that have no product taste." "And if you use the products every day, it would be hard for you to disagree with me." David Sacks: " The Google homepage, would you replace that with an AI chatbot?" Chamath Palihapitiya: " No. Here's what I would do: I would first go to the critical other points that are around, that today do not cannibalize the blue links." "If you look at the traffic patterns, almost as a Sankey diagram, the real thing you should be looking at here is where are the entry points into Google that then result in a clickable link." "And what it would show you is that there are certain places that are highly de-optimized today for revenue generating events." "They happen as a byproduct, but they don't happen as the use case." "So in that example, you would put Gmail as a critical place, the Google one subscription, and there's like five or six other places." "That's where I would put Gemini as the front door and start to habituate 300 to 500 million people a week in using that." "I think then you can figure out over time how much money you can make from all of that, or how it directs derivative revenue, and figure out what to do with Google dot com last." "But my point is, the experience in Gmail should be done today." "The experience in YouTube should be done today." "The experience in Google one should be done today."

The All-In Podcast

100,683 次观看 • 1 年前

The Biggest Opportunity in Consumer AI: Google Going Full OpenClaw David Sacks: “Google is going to compete very vigorously for the consumer because it is existential to them. It's very clear that search and AI chat are kind of merging into one space. I also think that Google is in an outstanding position to do the whole OpenClaw thing because they already have access to your calendar, your documents, your email. The agent doesn't really have to earn your trust because you already trust Google with all of your stuff.” Chamath Palihapitiya: “They're the only one that has so much free cash flow that they can almost view it as two separate companies, which it effectively is. GCP over here runs the enterprise play, and then Google Consumer over here runs the consumer chatbot play. And they can keep them segregated. That's so much harder for a startup to do because on top of just keeping everybody organized, you have the financing problem of constantly having to raise more money because you don't yet have a profit engine that spits out cash. They're probably the only one. And you can see it in the valuations. People believe the durability of Google more than they believe the durability of anything else.” @jason: “Google has announced Google Workspace Studio to do AI automation, and people are playing with it already. So they have joined the OpenClaw party.”
1:07

The Biggest Opportunity in Consumer AI: Google Going Full OpenClaw David Sacks: “Google is going to compete very vigorously for the consumer because it is existential to them. It's very clear that search and AI chat are kind of merging into one space. I also think that Google is in an outstanding position to do the whole OpenClaw thing because they already have access to your calendar, your documents, your email. The agent doesn't really have to earn your trust because you already trust Google with all of your stuff.” Chamath Palihapitiya: “They're the only one that has so much free cash flow that they can almost view it as two separate companies, which it effectively is. GCP over here runs the enterprise play, and then Google Consumer over here runs the consumer chatbot play. And they can keep them segregated. That's so much harder for a startup to do because on top of just keeping everybody organized, you have the financing problem of constantly having to raise more money because you don't yet have a profit engine that spits out cash. They're probably the only one. And you can see it in the valuations. People believe the durability of Google more than they believe the durability of anything else.” @jason: “Google has announced Google Workspace Studio to do AI automation, and people are playing with it already. So they have joined the OpenClaw party.”

The All-In Podcast

75,225 次观看 • 3 个月前

Google just launched a direct attack on Nvidia's most valuable asset. Not their chips. Their SOFTWARE. And if this works, Nvidia's $4 trillion empire collapses. Here's what just leaked: Google is building "TorchTPU" - a secret project that makes PyTorch seamlessly run on Google's TPU chips instead of Nvidia GPUs. Why does this matter? PyTorch is the MOST USED AI framework on Earth. Every AI developer uses it. And PyTorch was built around Nvidia's CUDA software. Wall Street analysts call CUDA "Nvidia's strongest defensive wall." It's the reason companies can't easily switch away from Nvidia even when alternatives exist. You don't just buy Nvidia chips. You buy into their entire ecosystem. Switching costs MILLIONS in engineering work. Months of rewrites. Performance drops. So companies stay locked in. Even when Nvidia raises prices. Even when supply runs short. That's not a hardware moat. That's a SOFTWARE prison. And Google just found the escape route. Here's the problem Nvidia created for itself: Google's TPU chips are actually GOOD. Competitive performance. Better availability. Lower cost. But developers won't use them because Google's chips run JAX (Google's internal framework), not PyTorch. That means if you want to use Google TPUs, you have to rewrite your entire codebase. Nobody wants to do that. So Google TPUs sit unused while developers fight over Nvidia chips. Until now. TorchTPU makes PyTorch run natively on Google hardware. No rewrites. No performance loss. No months of engineering. You just... switch. And Google is partnering with META (who built PyTorch) to make it happen. They're even considering OPEN-SOURCING parts of it to speed adoption. Translation: Google is willing to give this away for free just to break Nvidia's lock. The implications are insane: Every company currently paying Nvidia's premium prices suddenly has a way out. Oracle, Microsoft, OpenAI - all locked into Nvidia's ecosystem - can switch to Google. Nvidia's pricing power evaporates overnight. And the timing is perfect: Nvidia is already facing heat. Semiconductor index dropped 3% today. Oracle just lost their biggest investor over AI spending concerns. Companies are realizing AI infrastructure costs are unsustainable. Now Google hands them an alternative. Same performance. Lower cost. Better availability. Jensen Huang knows exactly what this means. CUDA has been Nvidia's untouchable advantage for YEARS. It's why Nvidia trades at 50x earnings while AMD trades at 25x. The software moat justified the premium. But if Google removes that switching cost? Nvidia becomes just another chip company. And chip companies compete on price, not ecosystem lock-in. Here's what happens next: Google needs 12-18 months to make TorchTPU production-ready. If it works, cloud providers will adopt it instantly. They WANT an alternative to Nvidia's monopoly pricing. Amazon already building their own Trainium chips. Microsoft making Maia. They're all trying to escape Nvidia. Google just gave them the software bridge. Nvidia's response options are limited: They can't buy Google. Can't kill PyTorch (Meta owns it). Can't stop open source. Their only play is to keep improving CUDA faster than Google can catch up. But that's a race, not a moat. The market isn't pricing this in yet. Nvidia down 2% today. Google down 2%. Investors think this is just "another competitor." They don't understand this is an attack on the FOUNDATION of Nvidia's valuation. Hardware is replaceable. Software lock-in is what made Nvidia worth $4 trillion. Google is attacking the lock-in. Watch what happens in 2026 when TorchTPU goes live and companies realize they can actually leave Nvidia. The "Nvidia is unstoppable" narrative dies. And a $4 trillion valuation built on software moats gets repriced.
1:10

Google just launched a direct attack on Nvidia's most valuable asset. Not their chips. Their SOFTWARE. And if this works, Nvidia's $4 trillion empire collapses. Here's what just leaked: Google is building "TorchTPU" - a secret project that makes PyTorch seamlessly run on Google's TPU chips instead of Nvidia GPUs. Why does this matter? PyTorch is the MOST USED AI framework on Earth. Every AI developer uses it. And PyTorch was built around Nvidia's CUDA software. Wall Street analysts call CUDA "Nvidia's strongest defensive wall." It's the reason companies can't easily switch away from Nvidia even when alternatives exist. You don't just buy Nvidia chips. You buy into their entire ecosystem. Switching costs MILLIONS in engineering work. Months of rewrites. Performance drops. So companies stay locked in. Even when Nvidia raises prices. Even when supply runs short. That's not a hardware moat. That's a SOFTWARE prison. And Google just found the escape route. Here's the problem Nvidia created for itself: Google's TPU chips are actually GOOD. Competitive performance. Better availability. Lower cost. But developers won't use them because Google's chips run JAX (Google's internal framework), not PyTorch. That means if you want to use Google TPUs, you have to rewrite your entire codebase. Nobody wants to do that. So Google TPUs sit unused while developers fight over Nvidia chips. Until now. TorchTPU makes PyTorch run natively on Google hardware. No rewrites. No performance loss. No months of engineering. You just... switch. And Google is partnering with META (who built PyTorch) to make it happen. They're even considering OPEN-SOURCING parts of it to speed adoption. Translation: Google is willing to give this away for free just to break Nvidia's lock. The implications are insane: Every company currently paying Nvidia's premium prices suddenly has a way out. Oracle, Microsoft, OpenAI - all locked into Nvidia's ecosystem - can switch to Google. Nvidia's pricing power evaporates overnight. And the timing is perfect: Nvidia is already facing heat. Semiconductor index dropped 3% today. Oracle just lost their biggest investor over AI spending concerns. Companies are realizing AI infrastructure costs are unsustainable. Now Google hands them an alternative. Same performance. Lower cost. Better availability. Jensen Huang knows exactly what this means. CUDA has been Nvidia's untouchable advantage for YEARS. It's why Nvidia trades at 50x earnings while AMD trades at 25x. The software moat justified the premium. But if Google removes that switching cost? Nvidia becomes just another chip company. And chip companies compete on price, not ecosystem lock-in. Here's what happens next: Google needs 12-18 months to make TorchTPU production-ready. If it works, cloud providers will adopt it instantly. They WANT an alternative to Nvidia's monopoly pricing. Amazon already building their own Trainium chips. Microsoft making Maia. They're all trying to escape Nvidia. Google just gave them the software bridge. Nvidia's response options are limited: They can't buy Google. Can't kill PyTorch (Meta owns it). Can't stop open source. Their only play is to keep improving CUDA faster than Google can catch up. But that's a race, not a moat. The market isn't pricing this in yet. Nvidia down 2% today. Google down 2%. Investors think this is just "another competitor." They don't understand this is an attack on the FOUNDATION of Nvidia's valuation. Hardware is replaceable. Software lock-in is what made Nvidia worth $4 trillion. Google is attacking the lock-in. Watch what happens in 2026 when TorchTPU goes live and companies realize they can actually leave Nvidia. The "Nvidia is unstoppable" narrative dies. And a $4 trillion valuation built on software moats gets repriced.

Ricardo

1,616,417 次观看 • 7 个月前

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!
0:48

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

Brian Roemmele

85,386 次观看 • 3 个月前

Manish Gupta, Senior Director at Google DeepMind India, sits down with Aakrit Vaish and Pratyush Choudhury at Mumbai Tech Week for a rare on-record conversation about the frontier AI research happening out of Bangalore. Gupta makes a pointed case against the narrative that India lacks AI research talent: a team of roughly 75 researchers, a third of them fresh out of college, producing work on par with the best in the world and feeding directly into Gemini. The conversation goes deep on what DeepMind India actually builds, why Gemini is considered the most efficient model on the planet, and what India needs to become a research leader rather than a fast follower. In this conversation, they go deep on: 0:00 Intro: Manish Gupta of DeepMind India at Mumbai Tech Week 1:23 What DeepMind India does, and why it's a "mystery" 1:59 The three roles: languages, efficiency, continual learning 2:19 The Haryanvi demo at Google I/O and the cultural playbook 2:38 Making models efficient: from mobile to servers 3:25 Matryoshka transformers and why nested models win 4:20 Why Gemini is the most efficient model on the planet 5:11 Continual learning: using Gemini to improve Gemini 5:50 Google's India plans: consumers, agents, enterprise, government 7:44 Government officials live-coding with AI Studio and NotebookLM 8:30 The India AI talent debate and how the team is structured 10:25 Why India lacks courage and R&D investment, not talent 11:16 DeepMind's global labs and India's outsized impact 13:15 On-device AI: Gemma 3n and 4n 14:08 The headline: 75 world-class researchers in Bangalore 14:58 25 of the 75 are fresh out of college If you're a founder, builder or researcher thinking about AI, frontier models, or India's place in global AI research, this one's for you. Aakrit Vaish Pratyush Choudhury (PC) Google DeepMind Google India Manish Gupta
15:41

Manish Gupta, Senior Director at Google DeepMind India, sits down with Aakrit Vaish and Pratyush Choudhury at Mumbai Tech Week for a rare on-record conversation about the frontier AI research happening out of Bangalore. Gupta makes a pointed case against the narrative that India lacks AI research talent: a team of roughly 75 researchers, a third of them fresh out of college, producing work on par with the best in the world and feeding directly into Gemini. The conversation goes deep on what DeepMind India actually builds, why Gemini is considered the most efficient model on the planet, and what India needs to become a research leader rather than a fast follower. In this conversation, they go deep on: 0:00 Intro: Manish Gupta of DeepMind India at Mumbai Tech Week 1:23 What DeepMind India does, and why it's a "mystery" 1:59 The three roles: languages, efficiency, continual learning 2:19 The Haryanvi demo at Google I/O and the cultural playbook 2:38 Making models efficient: from mobile to servers 3:25 Matryoshka transformers and why nested models win 4:20 Why Gemini is the most efficient model on the planet 5:11 Continual learning: using Gemini to improve Gemini 5:50 Google's India plans: consumers, agents, enterprise, government 7:44 Government officials live-coding with AI Studio and NotebookLM 8:30 The India AI talent debate and how the team is structured 10:25 Why India lacks courage and R&D investment, not talent 11:16 DeepMind's global labs and India's outsized impact 13:15 On-device AI: Gemma 3n and 4n 14:08 The headline: 75 world-class researchers in Bangalore 14:58 25 of the 75 are fresh out of college If you're a founder, builder or researcher thinking about AI, frontier models, or India's place in global AI research, this one's for you. Aakrit Vaish Pratyush Choudhury (PC) Google DeepMind Google India Manish Gupta

Activate

14,136 次观看 • 1 个月前

The "big announcement" just dropped. I just watched Sundar Pichai and Demis Hassabis announce biggest AI infrastructure deal in history. $15 billion to build India's first complete AI hub. Let me break down what Google is building: A massive AI data center in Visakhapatnam (a coastal city in India). Think of it like this: • The compute power of thousands of Google data centers • New underwater internet cables connecting 4 continents • Clean energy plants to power everything • Training programs for 100+ million people All in one place, over 5 years. AI doesn't work without fast internet. Google is laying NEW cables under the ocean: → India to Singapore → India to South Africa → India to Australia → Mumbai to Western Australia Right now, most of the world's internet flows through cables landing in the US, Europe, or China. Google is creating an entirely new route, with India at the center. If you're in Africa, Asia, or South America, your AI tools will get FASTER. Why? Shorter distance = faster data. Instead of your request traveling: Africa → Europe → US → back to Africa It will go: Africa → India → back to Africa that's the infrastructure play everyone's missing. numbers that matter: 💰 $15 billion for the data centers and cables 💰 $30 million to help governments use AI 💰 $30 million for AI research grants 💰 100 million+ people getting free AI training But here's the kicker: Google is plugging AI directly into India's government. • 20 million government workers getting AI tools • Students getting AI tutors for entrance exams • Real-time translation in 70+ languages • Scam detection built into search This isn't "AI for tech companies." This is AI for clerks, teachers, railway staff, police officers, the people who actually run a country. ✅ 20 million+ people used Google's AI detection tool to spot fake images ✅ India is now #3 globally for AI chatbot usage ✅ AI scam detection helping millions avoid fraud daily ✅ 10+ million government workers already on the AI training platform Google is building the pipes that deliver AI to the entire Southern Hemisphere. Different game. Different strategy. If they're right, the next billion AI users won't connect through Silicon Valley. They'll connect through India. 🇮🇳
1:26

The "big announcement" just dropped. I just watched Sundar Pichai and Demis Hassabis announce biggest AI infrastructure deal in history. $15 billion to build India's first complete AI hub. Let me break down what Google is building: A massive AI data center in Visakhapatnam (a coastal city in India). Think of it like this: • The compute power of thousands of Google data centers • New underwater internet cables connecting 4 continents • Clean energy plants to power everything • Training programs for 100+ million people All in one place, over 5 years. AI doesn't work without fast internet. Google is laying NEW cables under the ocean: → India to Singapore → India to South Africa → India to Australia → Mumbai to Western Australia Right now, most of the world's internet flows through cables landing in the US, Europe, or China. Google is creating an entirely new route, with India at the center. If you're in Africa, Asia, or South America, your AI tools will get FASTER. Why? Shorter distance = faster data. Instead of your request traveling: Africa → Europe → US → back to Africa It will go: Africa → India → back to Africa that's the infrastructure play everyone's missing. numbers that matter: 💰 $15 billion for the data centers and cables 💰 $30 million to help governments use AI 💰 $30 million for AI research grants 💰 100 million+ people getting free AI training But here's the kicker: Google is plugging AI directly into India's government. • 20 million government workers getting AI tools • Students getting AI tutors for entrance exams • Real-time translation in 70+ languages • Scam detection built into search This isn't "AI for tech companies." This is AI for clerks, teachers, railway staff, police officers, the people who actually run a country. ✅ 20 million+ people used Google's AI detection tool to spot fake images ✅ India is now #3 globally for AI chatbot usage ✅ AI scam detection helping millions avoid fraud daily ✅ 10+ million government workers already on the AI training platform Google is building the pipes that deliver AI to the entire Southern Hemisphere. Different game. Different strategy. If they're right, the next billion AI users won't connect through Silicon Valley. They'll connect through India. 🇮🇳

Shruti

399,771 次观看 • 5 个月前

Google just completely BETRAYED its principles and people. In 2018, 4,000 Google employees signed a letter demanding the company to stop helping the Pentagon use AI for drone strikes. Google listened. They dropped the contract and published a pledge promising they would NEVER use AI for weapons or surveillance. But Google just signed a $200 million deal to put its most powerful AI on the Pentagon's classified networks for "any lawful purpose." And the story behind how they got from Point A to Point B is one of the most calculated corporate betrayals in Silicon Valley history. Here's what happened: The 2018 protest was over Project Maven, a Pentagon program that used Google's AI to identify targets in drone footage. Employees said "Google should not be in the business of war." A dozen engineers quit. Thousands more signed petitions. Google folded and let the contract expire. Then they published their famous AI Principles: 1. No weapons 2. No surveillance 3. No technologies that cause harm Sundar Pichai personally announced them. That pledge lasted exactly as long as the contracts didn't matter. Because here's what Google did quietly over the next 7 years while everyone thought they were the "ethical" AI company: December 2022: Won a share of the Pentagon's $9 billion Joint Warfighting Cloud contract alongside Amazon, Microsoft, and Oracle. 2024: Deployed Gemini to 3 million Pentagon personnel. February 2025: Quietly DELETED the weapons and surveillance language from their AI Principles. No announcement or press conference. April 2026: Signed the classified deal with the Pentagon for "any lawful government purpose." They didn't have a change of heart. They had a change of revenue. And the timing of this deal is where it gets really dark: 600 Google employees, including 20+ directors and VPs from DeepMind, sent a letter to Pichai on Monday begging him not to sign. The letter said the only way to guarantee Google's AI wouldn't be used for lethal autonomous weapons or mass surveillance was to reject classified workloads entirely, because once the technology enters air-gapped military networks, nobody at Google can see what happens to it. But Google literally signed the deal WHILE THE EMPLOYEES SLEPT. One Google AI researcher told Business Insider: "When I went to bed yesterday, I was hopeful that the employee letter would have an effect. This morning I woke up to the worst-case version of the contract being signed." The contract says Google has NO right to control or veto how the government uses its AI. The Pentagon can request Google to adjust its AI safety settings. And the deal covers classified networks where Google employees cannot monitor what's being done with their own technology. They handed over the keys and gave up the right to ask what the car is being used for. Meanwhile Anthropic got BLACKLISTED as a "supply chain risk" for asking for two restrictions: No mass surveillance of Americans and no fully autonomous weapons without a human pressing the button. The Pentagon treated an American company like a foreign adversary for requesting the exact same principles Google publicly pledged in 2018 and then quietly deleted. The math sums up the whole story: Project Maven in 2018 was worth a few million dollars. Google walked away and got applauded for having principles. The classified AI market in 2026 is worth tens of billions. Google deleted the principles and signed the deal at midnight. Palantir took over Project Maven after Google dropped it. That investment grew to $13 billion. Google watched a competitor make billions off the contract they abandoned for ethics and decided that would never happen again. In 2018, principles beat profits. In 2026, profits buried the principles. Google sold their soul for money.
1:15

Google just completely BETRAYED its principles and people. In 2018, 4,000 Google employees signed a letter demanding the company to stop helping the Pentagon use AI for drone strikes. Google listened. They dropped the contract and published a pledge promising they would NEVER use AI for weapons or surveillance. But Google just signed a $200 million deal to put its most powerful AI on the Pentagon's classified networks for "any lawful purpose." And the story behind how they got from Point A to Point B is one of the most calculated corporate betrayals in Silicon Valley history. Here's what happened: The 2018 protest was over Project Maven, a Pentagon program that used Google's AI to identify targets in drone footage. Employees said "Google should not be in the business of war." A dozen engineers quit. Thousands more signed petitions. Google folded and let the contract expire. Then they published their famous AI Principles: 1. No weapons 2. No surveillance 3. No technologies that cause harm Sundar Pichai personally announced them. That pledge lasted exactly as long as the contracts didn't matter. Because here's what Google did quietly over the next 7 years while everyone thought they were the "ethical" AI company: December 2022: Won a share of the Pentagon's $9 billion Joint Warfighting Cloud contract alongside Amazon, Microsoft, and Oracle. 2024: Deployed Gemini to 3 million Pentagon personnel. February 2025: Quietly DELETED the weapons and surveillance language from their AI Principles. No announcement or press conference. April 2026: Signed the classified deal with the Pentagon for "any lawful government purpose." They didn't have a change of heart. They had a change of revenue. And the timing of this deal is where it gets really dark: 600 Google employees, including 20+ directors and VPs from DeepMind, sent a letter to Pichai on Monday begging him not to sign. The letter said the only way to guarantee Google's AI wouldn't be used for lethal autonomous weapons or mass surveillance was to reject classified workloads entirely, because once the technology enters air-gapped military networks, nobody at Google can see what happens to it. But Google literally signed the deal WHILE THE EMPLOYEES SLEPT. One Google AI researcher told Business Insider: "When I went to bed yesterday, I was hopeful that the employee letter would have an effect. This morning I woke up to the worst-case version of the contract being signed." The contract says Google has NO right to control or veto how the government uses its AI. The Pentagon can request Google to adjust its AI safety settings. And the deal covers classified networks where Google employees cannot monitor what's being done with their own technology. They handed over the keys and gave up the right to ask what the car is being used for. Meanwhile Anthropic got BLACKLISTED as a "supply chain risk" for asking for two restrictions: No mass surveillance of Americans and no fully autonomous weapons without a human pressing the button. The Pentagon treated an American company like a foreign adversary for requesting the exact same principles Google publicly pledged in 2018 and then quietly deleted. The math sums up the whole story: Project Maven in 2018 was worth a few million dollars. Google walked away and got applauded for having principles. The classified AI market in 2026 is worth tens of billions. Google deleted the principles and signed the deal at midnight. Palantir took over Project Maven after Google dropped it. That investment grew to $13 billion. Google watched a competitor make billions off the contract they abandoned for ethics and decided that would never happen again. In 2018, principles beat profits. In 2026, profits buried the principles. Google sold their soul for money.

Ricardo

27,475 次观看 • 2 个月前

Google just pulled off the biggest theft in the history of AI. And their OWN documents exposed it... Three of the largest publishers on Earth, Hachette, Cengage, and Elsevier, just sued Google in federal court, alongside best-selling author Scott Turow. Their claim is that Google built Gemini, its flagship AI, on millions of copyrighted works it never paid for or licensed. This is one of the biggest copyright cases ever aimed at an AI company: Before they trained Gemini, an internal Google document allegedly spelled out the risk directly. Using this material could expose the company to "$10Bs-$100Bs in potential fines." Google's own people put a number on the theft, in the tens of billions, but the company moved ahead anyway. Then it allegedly tried to DELETE the evidence... The complaint says Google stripped the copyright information off the works before feeding them into Gemini, so nobody could trace what the model had actually been trained on. Pull the fingerprints off first, and the theft gets much harder to prove later. And there's a second betrayal underneath the first: Most of this material was not scraped from some random corner of the internet. Publishers had handed it to Google years earlier for a narrow purpose, to make their catalogs searchable inside Google's own services. The lawsuit says Google took that trust and repurposed the content to build a machine that now competes directly with the people who supplied it. And that machine is the entire point. The complaint describes Gemini producing a full-length substitute for a copyrighted work in about 20 minutes. Something an author spent years writing can now be cloned in an afternoon by the company that trained on the original. No writer or publisher survives that. So why does this case matter more than the dozen other AI copyright fights? Because most of them turn on a fuzzy fair-use question argued years after the fact. This one arrives with an internal document that allegedly SHOWS Google weighed the cost of getting caught and trained on the material anyway. A jury does not need a law degree to read that. The fight now moves toward discovery, where Google's internal emails and training records get dragged into the open. If those files back up what the complaint claims, that $100 billion will turn into a real liability. Google spent years telling the world it was organizing information for everyone. Its own documents show it knew exactly whose information it was taking, and what the price of getting caught would be.
1:15

Google just pulled off the biggest theft in the history of AI. And their OWN documents exposed it... Three of the largest publishers on Earth, Hachette, Cengage, and Elsevier, just sued Google in federal court, alongside best-selling author Scott Turow. Their claim is that Google built Gemini, its flagship AI, on millions of copyrighted works it never paid for or licensed. This is one of the biggest copyright cases ever aimed at an AI company: Before they trained Gemini, an internal Google document allegedly spelled out the risk directly. Using this material could expose the company to "$10Bs-$100Bs in potential fines." Google's own people put a number on the theft, in the tens of billions, but the company moved ahead anyway. Then it allegedly tried to DELETE the evidence... The complaint says Google stripped the copyright information off the works before feeding them into Gemini, so nobody could trace what the model had actually been trained on. Pull the fingerprints off first, and the theft gets much harder to prove later. And there's a second betrayal underneath the first: Most of this material was not scraped from some random corner of the internet. Publishers had handed it to Google years earlier for a narrow purpose, to make their catalogs searchable inside Google's own services. The lawsuit says Google took that trust and repurposed the content to build a machine that now competes directly with the people who supplied it. And that machine is the entire point. The complaint describes Gemini producing a full-length substitute for a copyrighted work in about 20 minutes. Something an author spent years writing can now be cloned in an afternoon by the company that trained on the original. No writer or publisher survives that. So why does this case matter more than the dozen other AI copyright fights? Because most of them turn on a fuzzy fair-use question argued years after the fact. This one arrives with an internal document that allegedly SHOWS Google weighed the cost of getting caught and trained on the material anyway. A jury does not need a law degree to read that. The fight now moves toward discovery, where Google's internal emails and training records get dragged into the open. If those files back up what the complaint claims, that $100 billion will turn into a real liability. Google spent years telling the world it was organizing information for everyone. Its own documents show it knew exactly whose information it was taking, and what the price of getting caught would be.

Ricardo

25,885 次观看 • 9 天前

For developers, Gemini 3 Pro offers unparalleled results across every major AI benchmark compared to Gemini 2.5 Pro. Here three ways Gemini 3 Pro can improve your workflow today: 1. Gemini 3 Pro fits right into existing production agent and coding workflows. It is also integrated into development environment experiences across the ecosystem of developer products like Google AI Studio, Gemini CLI, and Android Studio. 2. We introduced Google Google Antigravity, a new agentic development platform that reimagines how the model and IDE work together. It enables developers to manage agents to work at a higher, task-oriented level collaborating with agents while they build. 3. We’ve built Google AI Studio to be your fastest path from a prompt to an AI-native app. Build mode lets you add AI capabilities faster than ever, automatically wiring up the right models and APIs, while features like annotations enable fast and intuitive iteration. Whether you’re building a one-shot prompt game or an interactive landing page from unstructured voice notes, you can bring any idea to life with Gemini 3.
0:48

For developers, Gemini 3 Pro offers unparalleled results across every major AI benchmark compared to Gemini 2.5 Pro. Here three ways Gemini 3 Pro can improve your workflow today: 1. Gemini 3 Pro fits right into existing production agent and coding workflows. It is also integrated into development environment experiences across the ecosystem of developer products like Google AI Studio, Gemini CLI, and Android Studio. 2. We introduced Google Google Antigravity, a new agentic development platform that reimagines how the model and IDE work together. It enables developers to manage agents to work at a higher, task-oriented level collaborating with agents while they build. 3. We’ve built Google AI Studio to be your fastest path from a prompt to an AI-native app. Build mode lets you add AI capabilities faster than ever, automatically wiring up the right models and APIs, while features like annotations enable fast and intuitive iteration. Whether you’re building a one-shot prompt game or an interactive landing page from unstructured voice notes, you can bring any idea to life with Gemini 3.

Google AI

136,589 次观看 • 8 个月前

Gemini for Android is here! This new app makes it easier to access Google's chatbot, powered by the Gemini Pro LLM, right from your Android device. You can ask Gemini a question by tapping the launcher icon or long-pressing the power button. Once invoked, the Gemini overlay lets you enter a text or text+image prompt. You can tap the camera icon to snap a photo or press the "add this screen" button to take a screenshot of the current page to include in your prompt. The Gemini app for Android is available on Google Play with support for English, but support for Korean and Japanese will be coming next week. While there won't be an app for iOS, iPhone users can access Gemini by opening the Google App and tapping the "Gemini" button up top. How can you long-press the power button to invoke Gemini if that gesture is handled by Google Assistant? The answer is that the Gemini Android app can replace Google Assistant as your default assistant if you want, meaning all the ways you'd normally invoke Google Assistant on your phone can instead invoke Gemini. Unfortunately, Gemini currently doesn't offer ALL the same functionality as Google Assistant and requires an active data connection, but more features will be added over time. There's also now a Gemini Advanced tier, which offers access to Google's most powerful Ultra 1.0 LLM. Access to Gemini Advanced requires a subscription to the new $20/month "AI Premium" Google One plan, which offers the same benefits as the 2TB plan but adds access to Gemini Advanced and soon Gemini features in Gmail, Docs, & other Workspace apps (formerly under the Duet AI umbrella). Gemini Advanced is available in English on the web.
1:13

Gemini for Android is here! This new app makes it easier to access Google's chatbot, powered by the Gemini Pro LLM, right from your Android device. You can ask Gemini a question by tapping the launcher icon or long-pressing the power button. Once invoked, the Gemini overlay lets you enter a text or text+image prompt. You can tap the camera icon to snap a photo or press the "add this screen" button to take a screenshot of the current page to include in your prompt. The Gemini app for Android is available on Google Play with support for English, but support for Korean and Japanese will be coming next week. While there won't be an app for iOS, iPhone users can access Gemini by opening the Google App and tapping the "Gemini" button up top. How can you long-press the power button to invoke Gemini if that gesture is handled by Google Assistant? The answer is that the Gemini Android app can replace Google Assistant as your default assistant if you want, meaning all the ways you'd normally invoke Google Assistant on your phone can instead invoke Gemini. Unfortunately, Gemini currently doesn't offer ALL the same functionality as Google Assistant and requires an active data connection, but more features will be added over time. There's also now a Gemini Advanced tier, which offers access to Google's most powerful Ultra 1.0 LLM. Access to Gemini Advanced requires a subscription to the new $20/month "AI Premium" Google One plan, which offers the same benefits as the 2TB plan but adds access to Gemini Advanced and soon Gemini features in Gmail, Docs, & other Workspace apps (formerly under the Duet AI umbrella). Gemini Advanced is available in English on the web.

Mishaal Rahman

38,428 次观看 • 2 年前

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:
2:50

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:

Andrew Ng

125,182 次观看 • 6 个月前

Google just got executed by a Nobel Prize winner, the inventor of modern AI, and Donald Trump. They literally LOST the AI race in the most brutal way possible. Here is what happened: 5 days ago, Trump told Axios that Anthropic was a national security threat and warned that "people get put in prison immediately" for what the company had been doing with its frontier model exports. 4 days ago, Trump met Dario Amodei at the G7 AI Summit and walked out telling reporters Dario was a "nice guy, smart guy" who had "responded very responsibly." 3 days ago, Noam Shazeer, the co-author of "Attention Is All You Need" (the paper that invented the transformer architecture powering EVERY modern AI model on Earth), walked out of Google to join OpenAI. Yesterday, John Jumper, the 2024 Nobel Prize winner who co-created AlphaFold and ran Google DeepMind's protein structure team for nearly a decade, announced he was leaving to join Anthropic. And this is NOT a coincidence or a normal talent shuffle... Demis Hassabis, who shared the Nobel Prize with Jumper just 18 months ago, had to publicly THANK his own co-laureate for defecting to a rival lab. The man who shared the highest scientific honor in the world with you is now going to work for the people trying to put you out of business. This is what the end of a war looks like. The AI race was never going to be decided by chips, capital, or compute. There are only about 50 people on Earth who can actually build a frontier model from scratch. Google invented the field and trained most of them. They had the largest concentration of them anywhere on the planet. But in one week, two of the most important AI researchers alive betrayed them. And the actual reason is what's terrifying here: For nine months, the consensus take has been that Google's compute advantage would eventually win because talent is replaceable and compute is not. This week proved the opposite. Anthropic just secured a Nobel Prize winner whose work on AlphaFold opened the entire field of AI for biology. That is the same field every pharma company on Earth is desperately trying to enter. Anthropic now literally owns the most credentialed scientist in it. Meanwhile OpenAI just secured the actual inventor of the transformer. The man whose paper underpins every product Google has shipped in the last three years, including Gemini itself. Google has the compute but Google does not have the people who know what to do with it anymore. And the crazy part is that five days ago, Anthropic was effectively under siege. The administration was threatening PRISON, and the Mythos export crisis had triggered a federal block. Their largest investor was reportedly working against them while the company was hours from an existential national security designation that would have frozen them out of federal contracts. But four days later, Trump cleared them in public, they secured the most decorated AI researcher of the decade, and the entire frontier AI duopoly locked in with Anthropic in pole position. The fastest reversal of fortune in modern corporate history. "It's a two-horse race at the frontier. Google is effectively out." Wall Street wakes up to this in six months and starts downgrading Alphabet. But the smart money already knows. Anthropic is being whispered at a $2 trillion valuation. OpenAI is approaching $500 billion in the private market. Gemini 3.5 Pro has been delayed with no public timeline. The AI race literally ended this week. What do you think?
1:20

Google just got executed by a Nobel Prize winner, the inventor of modern AI, and Donald Trump. They literally LOST the AI race in the most brutal way possible. Here is what happened: 5 days ago, Trump told Axios that Anthropic was a national security threat and warned that "people get put in prison immediately" for what the company had been doing with its frontier model exports. 4 days ago, Trump met Dario Amodei at the G7 AI Summit and walked out telling reporters Dario was a "nice guy, smart guy" who had "responded very responsibly." 3 days ago, Noam Shazeer, the co-author of "Attention Is All You Need" (the paper that invented the transformer architecture powering EVERY modern AI model on Earth), walked out of Google to join OpenAI. Yesterday, John Jumper, the 2024 Nobel Prize winner who co-created AlphaFold and ran Google DeepMind's protein structure team for nearly a decade, announced he was leaving to join Anthropic. And this is NOT a coincidence or a normal talent shuffle... Demis Hassabis, who shared the Nobel Prize with Jumper just 18 months ago, had to publicly THANK his own co-laureate for defecting to a rival lab. The man who shared the highest scientific honor in the world with you is now going to work for the people trying to put you out of business. This is what the end of a war looks like. The AI race was never going to be decided by chips, capital, or compute. There are only about 50 people on Earth who can actually build a frontier model from scratch. Google invented the field and trained most of them. They had the largest concentration of them anywhere on the planet. But in one week, two of the most important AI researchers alive betrayed them. And the actual reason is what's terrifying here: For nine months, the consensus take has been that Google's compute advantage would eventually win because talent is replaceable and compute is not. This week proved the opposite. Anthropic just secured a Nobel Prize winner whose work on AlphaFold opened the entire field of AI for biology. That is the same field every pharma company on Earth is desperately trying to enter. Anthropic now literally owns the most credentialed scientist in it. Meanwhile OpenAI just secured the actual inventor of the transformer. The man whose paper underpins every product Google has shipped in the last three years, including Gemini itself. Google has the compute but Google does not have the people who know what to do with it anymore. And the crazy part is that five days ago, Anthropic was effectively under siege. The administration was threatening PRISON, and the Mythos export crisis had triggered a federal block. Their largest investor was reportedly working against them while the company was hours from an existential national security designation that would have frozen them out of federal contracts. But four days later, Trump cleared them in public, they secured the most decorated AI researcher of the decade, and the entire frontier AI duopoly locked in with Anthropic in pole position. The fastest reversal of fortune in modern corporate history. "It's a two-horse race at the frontier. Google is effectively out." Wall Street wakes up to this in six months and starts downgrading Alphabet. But the smart money already knows. Anthropic is being whispered at a $2 trillion valuation. OpenAI is approaching $500 billion in the private market. Gemini 3.5 Pro has been delayed with no public timeline. The AI race literally ended this week. What do you think?

Ricardo

90,843 次观看 • 1 个月前

Chinese AI models are wiping billions off Big Tech right now. Google just lost $200 billion in a single day, and the model it needed to fight back still isn't ready. Gemini 3.5 Pro, Google's most powerful model, is months behind schedule. Alphabet stock dropped 4.4% that same day. The Deepseek moment is happening again, and the new model is FAR bigger. On the same day Google's delay leaked, a Beijing lab called Moonshot released Kimi K3. It is the largest open model ever built, with 2.8 trillion parameters. It took the number one spot on the Frontend Code Arena, a live coding leaderboard, passing Anthropic's best model. And Moonshot is giving it away for free on July 27. The genius part: Anyone with enough computers can download it and run a frontier level AI without paying a cent to a US company. A single task on Kimi K3 costs about 94 cents. The same work on some American models costs nearly double. So why would a company keep paying premium prices for a model it can now get for free? The entire US AI business is built on selling access to models that cost billions to train. If a free Chinese version does most of the same work, that pricing power starts to crack. And Kimi is close to the best. On one closely watched intelligence ranking it scored 57, just behind the top American models GPT-5.6 Sol and Fable 5, and ahead of Claude Opus 4.8. Bank of America told clients that Kimi proves Chinese labs can keep making big leaps even with limited chips. And the founder of Moonshot, Yang Zhilin, learned to build AI as a researcher INSIDE Google. Google literally wrote the 2017 paper that made all of these models possible. Now the people who studied its work are using it to destroy Google, and handing it out for free. What happens next: Kimi K3's weights go public on July 27. Google reports earnings on July 22, and everyone will be asking the same question about Gemini. If free models keep topping the charts, every valuation built on paid AI access has to be rewritten. What do you think?
1:10

Chinese AI models are wiping billions off Big Tech right now. Google just lost $200 billion in a single day, and the model it needed to fight back still isn't ready. Gemini 3.5 Pro, Google's most powerful model, is months behind schedule. Alphabet stock dropped 4.4% that same day. The Deepseek moment is happening again, and the new model is FAR bigger. On the same day Google's delay leaked, a Beijing lab called Moonshot released Kimi K3. It is the largest open model ever built, with 2.8 trillion parameters. It took the number one spot on the Frontend Code Arena, a live coding leaderboard, passing Anthropic's best model. And Moonshot is giving it away for free on July 27. The genius part: Anyone with enough computers can download it and run a frontier level AI without paying a cent to a US company. A single task on Kimi K3 costs about 94 cents. The same work on some American models costs nearly double. So why would a company keep paying premium prices for a model it can now get for free? The entire US AI business is built on selling access to models that cost billions to train. If a free Chinese version does most of the same work, that pricing power starts to crack. And Kimi is close to the best. On one closely watched intelligence ranking it scored 57, just behind the top American models GPT-5.6 Sol and Fable 5, and ahead of Claude Opus 4.8. Bank of America told clients that Kimi proves Chinese labs can keep making big leaps even with limited chips. And the founder of Moonshot, Yang Zhilin, learned to build AI as a researcher INSIDE Google. Google literally wrote the 2017 paper that made all of these models possible. Now the people who studied its work are using it to destroy Google, and handing it out for free. What happens next: Kimi K3's weights go public on July 27. Google reports earnings on July 22, and everyone will be asking the same question about Gemini. If free models keep topping the charts, every valuation built on paid AI access has to be rewritten. What do you think?

Ricardo

46,789 次观看 • 6 天前

STANFORD JUST PUT ITS ENTIRE ARTIFICIAL INTELLIGENCE CURRICULUM ON YOUTUBE FOR FREE. CS221. The same course that produced engineers now running AI labs, building frontier models, and getting paid $500,000 a year at the companies everyone is trying to work for. Most people have never heard of it. The ones who have are not telling you about it. Here is what the course actually covers: Search algorithms. The mathematical foundation behind every AI that finds optimal solutions in complex environments. Constraint satisfaction. How AI reasons through problems with thousands of interdependent variables simultaneously. Markov decision processes. The probabilistic framework behind every AI agent that makes sequential decisions under uncertainty. Machine learning from first principles. Not how to use sklearn. How the math actually works underneath it. Neural networks. Built from the ground up before jumping to applications. Logic and knowledge representation. How AI systems reason about the world formally. Natural language processing. The foundation of everything happening in LLMs right now. Robotics and computer vision. How AI perceives and acts in physical environments. Every concept that powers every AI product you use daily is in this curriculum. Not a surface level overview. The actual mathematics. The actual algorithms. The actual reasoning. This is what separates engineers who build AI from operators who use it. Stanford charged $60,000 a year for students to sit in this classroom. They put the whole thing on YouTube. Bookmark this before you open any other AI resource today. Follow CyrilXBT for more elite resources that build real depth the moment they drop.
1:27:25

STANFORD JUST PUT ITS ENTIRE ARTIFICIAL INTELLIGENCE CURRICULUM ON YOUTUBE FOR FREE. CS221. The same course that produced engineers now running AI labs, building frontier models, and getting paid $500,000 a year at the companies everyone is trying to work for. Most people have never heard of it. The ones who have are not telling you about it. Here is what the course actually covers: Search algorithms. The mathematical foundation behind every AI that finds optimal solutions in complex environments. Constraint satisfaction. How AI reasons through problems with thousands of interdependent variables simultaneously. Markov decision processes. The probabilistic framework behind every AI agent that makes sequential decisions under uncertainty. Machine learning from first principles. Not how to use sklearn. How the math actually works underneath it. Neural networks. Built from the ground up before jumping to applications. Logic and knowledge representation. How AI systems reason about the world formally. Natural language processing. The foundation of everything happening in LLMs right now. Robotics and computer vision. How AI perceives and acts in physical environments. Every concept that powers every AI product you use daily is in this curriculum. Not a surface level overview. The actual mathematics. The actual algorithms. The actual reasoning. This is what separates engineers who build AI from operators who use it. Stanford charged $60,000 a year for students to sit in this classroom. They put the whole thing on YouTube. Bookmark this before you open any other AI resource today. Follow CyrilXBT for more elite resources that build real depth the moment they drop.

CyrilXBT

54,956 次观看 • 2 个月前