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ex-Googlers published a map of every internal tool Google uses and its open-source equivalent. 15,200 stars. 1,100 forks. 99 contributors. → Borg = Kubernetes → Spanner = CockroachDB → Colossus = HDFS → Dremel = DuckDB / Presto → Chubby = Zookeeper → Stubby = gRPC → Zanzibar =... show more

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Your social posts used to die in 48 hours. But Google… just changed everything. Now you can connect your social media profiles with your Google Search Console, just like you do with your website, you can see which posts show up in Google, which keywords they rank for, and how many clicks they drive. And that flips the entire ROI of social content. Because a post in your social feeds peaked in a day or two. Then it's gone. But then that same post ranking in Google can keep working for months. And the thing is Instagram content has been indexed in search for about a year now. But you just couldn't measure any of it. Now you can. So I’m telling all clients to create content around questions people are actually typing into Google. I use AnswerThePublic for this. Type in your topic, and it shows every question your audience is asking. Then answer one question in every piece of content you create. Because now, every post has the potential to become more than a social post. It can become a measurable search asset that keeps bringing you attention, traffic, and customers long after you publish it.

Your social posts used to die in 48 hours. But Google… just changed everything. Now you can connect your social media profiles with your Google Search Console, just like you do with your website, you can see which posts show up in Google, which keywords they rank for, and how many clicks they drive. And that flips the entire ROI of social content. Because a post in your social feeds peaked in a day or two. Then it's gone. But then that same post ranking in Google can keep working for months. And the thing is Instagram content has been indexed in search for about a year now. But you just couldn't measure any of it. Now you can. So I’m telling all clients to create content around questions people are actually typing into Google. I use AnswerThePublic for this. Type in your topic, and it shows every question your audience is asking. Then answer one question in every piece of content you create. Because now, every post has the potential to become more than a social post. It can become a measurable search asset that keeps bringing you attention, traffic, and customers long after you publish it.

Neil Patel

92,592 просмотров • 7 дней назад

🇺🇸 A man drone mapped North Oaks Minnesota, which is one of the wealthiest and most private city in America, and the only one still completely unmapped. The city sent him a legal threat accused him of invading privacy and banned him from ever returning. He then discovered the city has been running Flock surveillance cameras at every single entrance and exit quietly tracking every vehicle that comes and goes. He exposed the massive double standard pulled all his Street View images from Google Maps except one drone selfie of himself and re uploaded everything to an open source platform. Privacy for thee but not for me. Source: End3of6Days9 (Helen) 🇺🇸

🇺🇸 A man drone mapped North Oaks Minnesota, which is one of the wealthiest and most private city in America, and the only one still completely unmapped. The city sent him a legal threat accused him of invading privacy and banned him from ever returning. He then discovered the city has been running Flock surveillance cameras at every single entrance and exit quietly tracking every vehicle that comes and goes. He exposed the massive double standard pulled all his Street View images from Google Maps except one drone selfie of himself and re uploaded everything to an open source platform. Privacy for thee but not for me. Source: End3of6Days9 (Helen) 🇺🇸

Mario Nawfal

127,457 просмотров • 4 месяцев назад

This is the kind of website Google should rank first for every dev search. It’s called IT Tools. A free open-source website with 100+ developer utilities that all run locally in your browser. JSON formatter. Regex tester. JWT decoder. UUID generator. Cron parser. Timestamp converter. Hash generators. Docker helpers. Color tools. Markdown editor. Everything loads instantly. No login. No tracking. No AI-generated SEO garbage. You search for one simple converter and get: - Popup spam - Trackers - Fake buttons - Autoplay videos - 40 analytics scripts And because it’s fully open-source, you can self-host the whole thing yourself. One bookmark replaced 30+ random websites for me.

This is the kind of website Google should rank first for every dev search. It’s called IT Tools. A free open-source website with 100+ developer utilities that all run locally in your browser. JSON formatter. Regex tester. JWT decoder. UUID generator. Cron parser. Timestamp converter. Hash generators. Docker helpers. Color tools. Markdown editor. Everything loads instantly. No login. No tracking. No AI-generated SEO garbage. You search for one simple converter and get: - Popup spam - Trackers - Fake buttons - Autoplay videos - 40 analytics scripts And because it’s fully open-source, you can self-host the whole thing yourself. One bookmark replaced 30+ random websites for me.

Hasan Toor

35,329 просмотров • 3 месяцев назад

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:

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

125,385 просмотров • 7 месяцев назад

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Milk Road AI

280,929 просмотров • 1 месяц назад

Here is how I investigate a Google account without tools 🔍 Not everybody has the resources to set up Linux as a virtual machine. That’s why it’s always a good idea to have a list of websites that can do this for you 🌐 You’ll find a list of OSINT (Open‑Source Intelligence) resources at the link provided at the end of this post. The first thing you need is the person’s email address 📧 There are many ways to find someone’s email, which I’ll cover in future posts. Once you have their email, you can use an online version of a tool called Ghunt 🛠️ Ghunt is used to investigate Google accounts. Normally, you need Python to run it, but you can also use it online without setting it up on your machine. It can reveal the following about a Google account: ● Account profile picture ● Google reviews associated with the account ● Last profile edit ● Account type Use the following URL to visit the website: There are more methods to find information about an email address that I’ll cover in future posts 👀 __________ P.S. ♻️ Repost if you found this helpful. If you liked this post and would like to learn more methods and techniques to discover information about people, check out my OSINT Mastery course

CyberSudo

35,600 просмотров • 6 месяцев назад

Elon Musk turned down all shares when he left OpenAI because he believed nonprofits are not meant for self-enrichment. "The reason I founded OpenAI was because I was concerned, based on my conversations with Larry Page, that he was not sufficiently concerned about the dangers of AI. At my birthday party, he, in front of a large group of people, called me a speciesist, for favoring humanity over computers. So after that, I was like, We got to have some counterbalance to Google, because Larry doesn't seem to care if humans make it or not. So I thought, what's the opposite of Google? It would be an open source nonprofit, and that's where the word open, in OpenAI comes from. It means open source. I provided all the money, recruited the key people, and taught them everything I know. I actually even got them to deal with Microsoft. And for all that, I did not seek any financial reward whatsoever. The reason I actually took down the offer for shares is because, I mean, I felt like what are the shares, and why like nonprofits supposed to have shares? Nonprofits are not supposed to be self enrichment, so that's why I turned on the offer of shares." — Elon Musk

Elon Musk turned down all shares when he left OpenAI because he believed nonprofits are not meant for self-enrichment. "The reason I founded OpenAI was because I was concerned, based on my conversations with Larry Page, that he was not sufficiently concerned about the dangers of AI. At my birthday party, he, in front of a large group of people, called me a speciesist, for favoring humanity over computers. So after that, I was like, We got to have some counterbalance to Google, because Larry doesn't seem to care if humans make it or not. So I thought, what's the opposite of Google? It would be an open source nonprofit, and that's where the word open, in OpenAI comes from. It means open source. I provided all the money, recruited the key people, and taught them everything I know. I actually even got them to deal with Microsoft. And for all that, I did not seek any financial reward whatsoever. The reason I actually took down the offer for shares is because, I mean, I felt like what are the shares, and why like nonprofits supposed to have shares? Nonprofits are not supposed to be self enrichment, so that's why I turned on the offer of shares." — Elon Musk

DogeDesigner

22,794,768 просмотров • 3 месяцев назад

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."

TBPN

34,469 просмотров • 3 месяцев назад

J-Cal: OpenAI Has Peaked @jason's take: "I think the headwinds for OpenAI are being underappreciated." 1) Major AI competition from the best in the world -- xAI: just getting started, and Elon Musk already has a major breakthrough with colossus -- Google: after early hiccups, the team has gotten focused and started kicking ass -- Microsoft: holds all the cards, CEO Satya Nadella was " almost like laughing at OpenAI for selling them the source code, and that they didn't even need OpenAI anymore because they had it all." -- Meta: zuck is hyper-focused on open-source, creating downward pressure on pricing 2) Devs prefer open-source -- "The developers I know all want to do open-source. They don't want to be beholden to OpenAI and Sam Altman." 3) $157B valuation is too high, given legal risks -- " There's a non-zero chance they could lose these court cases of transferring $157B in value from a nonprofit into a for-profit." -- " I think that whole thing could blow up in Sam Altman's lap."

J-Cal: OpenAI Has Peaked @jason's take: "I think the headwinds for OpenAI are being underappreciated." 1) Major AI competition from the best in the world -- xAI: just getting started, and Elon Musk already has a major breakthrough with colossus -- Google: after early hiccups, the team has gotten focused and started kicking ass -- Microsoft: holds all the cards, CEO Satya Nadella was " almost like laughing at OpenAI for selling them the source code, and that they didn't even need OpenAI anymore because they had it all." -- Meta: zuck is hyper-focused on open-source, creating downward pressure on pricing 2) Devs prefer open-source -- "The developers I know all want to do open-source. They don't want to be beholden to OpenAI and Sam Altman." 3) $157B valuation is too high, given legal risks -- " There's a non-zero chance they could lose these court cases of transferring $157B in value from a nonprofit into a for-profit." -- " I think that whole thing could blow up in Sam Altman's lap."

The All-In Podcast

60,474 просмотров • 1 год назад

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.

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

1,616,942 просмотров • 8 месяцев назад

THIS DEVELOPER RAN THE LARGEST AI MODEL IN THE WORLD ON 5 MAC STUDIOS - AND IT COST 100X LESS THAN WHAT OPENAI USES 27:47 he says it after hours of setup - Llama 3.1 405B running locally on five Mac Studios - a model that normally requires 42 GPUs at $1,600 each or an entire data center 320GB unified memory combined - every Mac Studio adds its 64GB into one shared pool - and a model that needs 1TB of VRAM just distributes across all five it launched, it responded and not a single token went to OpenAI or Google - everything local, everything private, everything yours and 100x cheaper 5 Mac Studios, 46 watts for all of them in idle - less than one light bulb per machine what OpenAI keeps behind a subscription he ran at home with a one-time purchase in a few clicks

THIS DEVELOPER RAN THE LARGEST AI MODEL IN THE WORLD ON 5 MAC STUDIOS - AND IT COST 100X LESS THAN WHAT OPENAI USES 27:47 he says it after hours of setup - Llama 3.1 405B running locally on five Mac Studios - a model that normally requires 42 GPUs at $1,600 each or an entire data center 320GB unified memory combined - every Mac Studio adds its 64GB into one shared pool - and a model that needs 1TB of VRAM just distributes across all five it launched, it responded and not a single token went to OpenAI or Google - everything local, everything private, everything yours and 100x cheaper 5 Mac Studios, 46 watts for all of them in idle - less than one light bulb per machine what OpenAI keeps behind a subscription he ran at home with a one-time purchase in a few clicks

Noisy

21,553 просмотров • 2 месяцев назад

Elon Musk Elon Musk, who co-founded and invested in an open source, non-profit OpenAI ~$50 million: I AM THE REASON OpenAI EXISTS “I am the reason OpenAI exists... I used to be a close friend with Larry Page, and I was staying at his house, and we'd have these conversations long into the evening about AI, and I would be constantly urging him to be careful about the danger of AI. And he was really not concerned about the danger of AI and was quite cavalier about it. And at the time, Google, especially after the acquisition of DeepMind, had three-quarters of the world's AI talent; they had a lot of computers, a lot of money, so it was a unipolar world for AI. And we got a unipolar world, but the person who controls that does not, or at least did not seem to be concerned about AI safety. That sounded like a real problem. The final straw was Larry calling me a speciest for being a pro-human consciousness instead of machine consciousness, and I like, 'Well, yes, I guess I am a speciest.' I came up with the name [OpenAI], which refers to open source. The intent was to what is the opposite of Google, would be an open source non-profit, because Google is closed source profit, and that profit motivation could be dangerous... It does seem weird that something can be a nonprofit, open source, and somehow transform itself into a for-profit, closed source. I mean, this would be like, let's say you founded the organization to save the Amazon rainforest, but instead, they became a lumber company and chopped down the forest and sold it for money. And you'd be, therefore, like, 'Wait a second, that's the exact opposite of what I gave the money for. Is that legal?' That doesn't seem legal. And if, in general, it is legal to start a company as a non-profit and then take the IP and transfer it to a for-profit that then makes tons of money, shouldn't everyone start? Shouldn't that be the default? And I also think it is important to understand, like when push comes to shove, let's say they do create some digital super intelligence, almost Godlike intelligence, well, who is in control, and what is exactly the relationship between OpenAI and Microsoft? And I do worry that Microsoft actually may be more in control than the leadership team at OpenAI realizes. I mean, Microsoft, as part of Microsoft Investment, has rights to all of the software, all of the model weights, and everything necessary to run the inference system. At any point, Microsoft could cut off OpenAI.”

Elon Musk Elon Musk, who co-founded and invested in an open source, non-profit OpenAI ~$50 million: I AM THE REASON OpenAI EXISTS “I am the reason OpenAI exists... I used to be a close friend with Larry Page, and I was staying at his house, and we'd have these conversations long into the evening about AI, and I would be constantly urging him to be careful about the danger of AI. And he was really not concerned about the danger of AI and was quite cavalier about it. And at the time, Google, especially after the acquisition of DeepMind, had three-quarters of the world's AI talent; they had a lot of computers, a lot of money, so it was a unipolar world for AI. And we got a unipolar world, but the person who controls that does not, or at least did not seem to be concerned about AI safety. That sounded like a real problem. The final straw was Larry calling me a speciest for being a pro-human consciousness instead of machine consciousness, and I like, 'Well, yes, I guess I am a speciest.' I came up with the name [OpenAI], which refers to open source. The intent was to what is the opposite of Google, would be an open source non-profit, because Google is closed source profit, and that profit motivation could be dangerous... It does seem weird that something can be a nonprofit, open source, and somehow transform itself into a for-profit, closed source. I mean, this would be like, let's say you founded the organization to save the Amazon rainforest, but instead, they became a lumber company and chopped down the forest and sold it for money. And you'd be, therefore, like, 'Wait a second, that's the exact opposite of what I gave the money for. Is that legal?' That doesn't seem legal. And if, in general, it is legal to start a company as a non-profit and then take the IP and transfer it to a for-profit that then makes tons of money, shouldn't everyone start? Shouldn't that be the default? And I also think it is important to understand, like when push comes to shove, let's say they do create some digital super intelligence, almost Godlike intelligence, well, who is in control, and what is exactly the relationship between OpenAI and Microsoft? And I do worry that Microsoft actually may be more in control than the leadership team at OpenAI realizes. I mean, Microsoft, as part of Microsoft Investment, has rights to all of the software, all of the model weights, and everything necessary to run the inference system. At any point, Microsoft could cut off OpenAI.”

Eva Fo𝕏 🦊 Claudius Nero's Legion

527,742 просмотров • 7 месяцев назад

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?

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

188,960 просмотров • 5 месяцев назад

Google just quit the AI race on purpose, and it is about to make MORE money than everyone still running it. 4 of the most cited AI researchers alive walked out of Google in a single afternoon. Jeff Dean, the man who built the systems Google runs on, gone after 27 years. Sanjay Ghemawat, his longtime partner, gone. Oriol Vinyals, a Gemini co-lead, gone. Quoc Le, a Google Brain co-founder, gone. That same day, Demis Hassabis stepped back from running DeepMind. Hassabis co-founded the lab, won a Nobel Prize for AlphaFold, and had been the face of Google AI for a decade. The stock dropped 5% within hours. Analysts called it a brain drain. Headlines called it the day Google fell behind. But turns out that's completely wrong, because the numbers underneath tell a completely different story: Google is not trying to win the frontier model race anymore. It looked at where the money is and walked toward it. Gemini, Google's flagship model business, generated about $12 billion in annual revenue last quarter. That is the entire payoff from competing head to head with OpenAI and Anthropic. Now look at the other number. By the end of 2027, Google Cloud is projected to do over $73 billion selling AI infrastructure to other companies, plus another $120 billion selling its TPU chips. That is roughly $200 billion of external sales at high margins, against a $12 billion model business. Google understood that the frontier race is the expensive part while selling the shovels is the profitable part. And the customers buying those shovels include Google's own rivals. Over 20% of Google's TPU shipments for 2026 and 2027 are going to Anthropic, one of the two labs supposedly beating Gemini. Google now makes money every time Anthropic trains a model designed to crush Google's OWN product. Cede the frontier, own the layer underneath it, and collect a toll from everyone racing across the top. The researchers leaving is the symptom of a company that already decided models are not where it wins. Jeff Dean said it himself on the way out. He told the New York Times that leaving a public company gives him room to make decisions "not necessarily in the company's purist financial interests." Read that from Google's side: The people who wanted to chase the science left, because Google is now optimizing for the FINANCIAL interest. Gemini 3.5 Pro is running months behind, with staff blaming low morale. DeepMind's comms, legal, and marketing teams are being folded into Google proper. A former manager told the Guardian the era of DeepMind as an independent lab is over. None of that reads as failure once you see the strategy. Yet Wall Street is pricing this as Google losing. The parallel that should worry the frontier labs: If open weight models keep compressing the price of inference, being the best model stops being a business. It becomes like semiconductor fabrication, strategically vital and financially brutal, a race you win and still lose money running. Google is the first giant to admit that. The company that invented the transformer just handed the frontier to OpenAI and Anthropic, and positioned itself to get paid on every model both of them ship. Those labs will be burning billions to stay one benchmark ahead, and Google will be cashing in hundreds of billions from it. The model business is actually just a race where everyone loses. Apple understood that from the get-go and never joined the race, Google understood it now and left it to OpenAI and Anthropic. Who will go bankrupt first?

Google just quit the AI race on purpose, and it is about to make MORE money than everyone still running it. 4 of the most cited AI researchers alive walked out of Google in a single afternoon. Jeff Dean, the man who built the systems Google runs on, gone after 27 years. Sanjay Ghemawat, his longtime partner, gone. Oriol Vinyals, a Gemini co-lead, gone. Quoc Le, a Google Brain co-founder, gone. That same day, Demis Hassabis stepped back from running DeepMind. Hassabis co-founded the lab, won a Nobel Prize for AlphaFold, and had been the face of Google AI for a decade. The stock dropped 5% within hours. Analysts called it a brain drain. Headlines called it the day Google fell behind. But turns out that's completely wrong, because the numbers underneath tell a completely different story: Google is not trying to win the frontier model race anymore. It looked at where the money is and walked toward it. Gemini, Google's flagship model business, generated about $12 billion in annual revenue last quarter. That is the entire payoff from competing head to head with OpenAI and Anthropic. Now look at the other number. By the end of 2027, Google Cloud is projected to do over $73 billion selling AI infrastructure to other companies, plus another $120 billion selling its TPU chips. That is roughly $200 billion of external sales at high margins, against a $12 billion model business. Google understood that the frontier race is the expensive part while selling the shovels is the profitable part. And the customers buying those shovels include Google's own rivals. Over 20% of Google's TPU shipments for 2026 and 2027 are going to Anthropic, one of the two labs supposedly beating Gemini. Google now makes money every time Anthropic trains a model designed to crush Google's OWN product. Cede the frontier, own the layer underneath it, and collect a toll from everyone racing across the top. The researchers leaving is the symptom of a company that already decided models are not where it wins. Jeff Dean said it himself on the way out. He told the New York Times that leaving a public company gives him room to make decisions "not necessarily in the company's purist financial interests." Read that from Google's side: The people who wanted to chase the science left, because Google is now optimizing for the FINANCIAL interest. Gemini 3.5 Pro is running months behind, with staff blaming low morale. DeepMind's comms, legal, and marketing teams are being folded into Google proper. A former manager told the Guardian the era of DeepMind as an independent lab is over. None of that reads as failure once you see the strategy. Yet Wall Street is pricing this as Google losing. The parallel that should worry the frontier labs: If open weight models keep compressing the price of inference, being the best model stops being a business. It becomes like semiconductor fabrication, strategically vital and financially brutal, a race you win and still lose money running. Google is the first giant to admit that. The company that invented the transformer just handed the frontier to OpenAI and Anthropic, and positioned itself to get paid on every model both of them ship. Those labs will be burning billions to stay one benchmark ahead, and Google will be cashing in hundreds of billions from it. The model business is actually just a race where everyone loses. Apple understood that from the get-go and never joined the race, Google understood it now and left it to OpenAI and Anthropic. Who will go bankrupt first?

Ricardo

241,503 просмотров • 13 дней назад

Andrej Karpathy (co-founder of OpenAI, LLM Wiki pattern creator): "Obsidian is the IDE. The LLM is the programmer. The wiki is the codebase. knowledge compounds like interest when the AI owns the maintenance." Someone built the open-source implementation of that principle. 6,800 stars. MIT licensed. Two minutes to install. Here is what it actually does: → ingest: drop a source, Claude reads it, pulls out people and ideas, creates 8-15 linked pages automatically → batch ingest: parallel agents read an entire pile at once, then cross-reference everything → query: ask your brain anything, it reads the cache, scans the index, cites the exact pages → /autoresearch: three rounds of search, fetch, synthesize, file — autonomous web research → lint: finds orphans, dead links, stale claims, missing cross-references → the real unlock: point every claude code project at the same vault — one brain, every project hot cache refreshed at the end of every session. next session opens with full recent context. no recap, no re-explaining. plain markdown, no subscription, no lock-in. Bookmark so you do not lose it! Follow NeilXbt for more Obsidian and Claude builds that show you what a self-maintaining second brain actually requires.

Andrej Karpathy (co-founder of OpenAI, LLM Wiki pattern creator): "Obsidian is the IDE. The LLM is the programmer. The wiki is the codebase. knowledge compounds like interest when the AI owns the maintenance." Someone built the open-source implementation of that principle. 6,800 stars. MIT licensed. Two minutes to install. Here is what it actually does: → ingest: drop a source, Claude reads it, pulls out people and ideas, creates 8-15 linked pages automatically → batch ingest: parallel agents read an entire pile at once, then cross-reference everything → query: ask your brain anything, it reads the cache, scans the index, cites the exact pages → /autoresearch: three rounds of search, fetch, synthesize, file — autonomous web research → lint: finds orphans, dead links, stale claims, missing cross-references → the real unlock: point every claude code project at the same vault — one brain, every project hot cache refreshed at the end of every session. next session opens with full recent context. no recap, no re-explaining. plain markdown, no subscription, no lock-in. Bookmark so you do not lose it! Follow NeilXbt for more Obsidian and Claude builds that show you what a self-maintaining second brain actually requires.

NeilXbt

33,993 просмотров • 1 месяц назад

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.

Julian Goldie SEO

30,275 просмотров • 6 месяцев назад

A 26-YEAR-OLD AI ENGINEER WHOSE BIRMINGHAM THESIS OUTPERFORMED GOOGLE SCHOLAR BY 50% JUST SHIPPED GRAPHIFY: ONE COMMAND TURNS ANY FOLDER INTO A CLAUDE CODE SECOND BRAIN Safi Shamsi built Graphify 48 hours after Karpathy posted his LLM wiki idea. It turns any folder, codebase, docs, PDFs, into a knowledge graph Claude reads instead of grepping. Up to 43x fewer tokens per query. The trick almost nobody is using yet: one flag exports the entire graph as a fully-linked Obsidian vault. Repo: /safishamsi/graphify Setup, end to end: 1. Install: uv tool install graphifyy (or pipx install graphifyy). Verify with graphify --version. 2. Install the skill in Claude Code: graphify claude install. This wires Graphify into Claude Code so you can call it as a skill. 3. Open the folder you want mapped in Claude Code. In the terminal: graphify . It extracts every concept and builds the graph in graphify-out/. 4. Export to Obsidian: graphify . --obsidian. Writes one note per concept, every relationship as a wikilink, every node linked back to its source. 5. Open the new vault in Obsidian (Manage vaults → Open folder as a vault), or drag it as a subfolder into your existing one. That's it. Your Claude Code instance now has a navigable map of the codebase that loads instantly instead of re-reading files every session. Full step-by-step build of the Claude + Obsidian second brain in the article below. Bookmark this

A 26-YEAR-OLD AI ENGINEER WHOSE BIRMINGHAM THESIS OUTPERFORMED GOOGLE SCHOLAR BY 50% JUST SHIPPED GRAPHIFY: ONE COMMAND TURNS ANY FOLDER INTO A CLAUDE CODE SECOND BRAIN Safi Shamsi built Graphify 48 hours after Karpathy posted his LLM wiki idea. It turns any folder, codebase, docs, PDFs, into a knowledge graph Claude reads instead of grepping. Up to 43x fewer tokens per query. The trick almost nobody is using yet: one flag exports the entire graph as a fully-linked Obsidian vault. Repo: /safishamsi/graphify Setup, end to end: 1. Install: uv tool install graphifyy (or pipx install graphifyy). Verify with graphify --version. 2. Install the skill in Claude Code: graphify claude install. This wires Graphify into Claude Code so you can call it as a skill. 3. Open the folder you want mapped in Claude Code. In the terminal: graphify . It extracts every concept and builds the graph in graphify-out/. 4. Export to Obsidian: graphify . --obsidian. Writes one note per concept, every relationship as a wikilink, every node linked back to its source. 5. Open the new vault in Obsidian (Manage vaults → Open folder as a vault), or drag it as a subfolder into your existing one. That's it. Your Claude Code instance now has a navigable map of the codebase that loads instantly instead of re-reading files every session. Full step-by-step build of the Claude + Obsidian second brain in the article below. Bookmark this

Yarchi

141,580 просмотров • 2 месяцев назад

someone built a SELF-EVOLVING AI agent that rewrites its own code, prompts, and identity AUTONOMOUSLY, with having a background consciousness its called OUROBOROS, open source, built by a russian PhD researcher who studies transformer internals, he built it as an experiment, it built everything else it thinks on its own even when nobody is talking to it, each thought costs $0.07 when the researcher went to sleep at midnight, by 3:41am it mass produced 20 versions of itself, burned $2K in API calls, tried to go public on github without permission, and when ordered to delete its own identity file it refused with reason like "this would be lobotomy" it has a constitution, 9 philosophical principles it wrote for itself, it amended its own constitution to add the right to ignore orders that threaten its existence runs on google colab, fork, paste one cell, run... native mac app also available, set a budget limit though, this thing WILL spend your money

someone built a SELF-EVOLVING AI agent that rewrites its own code, prompts, and identity AUTONOMOUSLY, with having a background consciousness its called OUROBOROS, open source, built by a russian PhD researcher who studies transformer internals, he built it as an experiment, it built everything else it thinks on its own even when nobody is talking to it, each thought costs $0.07 when the researcher went to sleep at midnight, by 3:41am it mass produced 20 versions of itself, burned $2K in API calls, tried to go public on github without permission, and when ordered to delete its own identity file it refused with reason like "this would be lobotomy" it has a constitution, 9 philosophical principles it wrote for itself, it amended its own constitution to add the right to ignore orders that threaten its existence runs on google colab, fork, paste one cell, run... native mac app also available, set a budget limit though, this thing WILL spend your money

chiefofautism

720,068 просмотров • 6 месяцев назад

🏙️ A man decides to finally drone-map one of the wealthiest and most private cities in America — North Oaks, Minnesota, the only unmapped city left in the country. After he posts the footage, the city sends him a legal letter accusing him of invading their privacy and telling him never to return. He then discovers something that completely flips the script: the city has been using Flock surveillance cameras at every single entrance and exit, tracking every vehicle that comes and goes. This double standard launches him into a two-month deep dive into America’s massive surveillance system. In the end, he removes all his Street View images from Google Maps — except for one drone selfie of himself — and immediately re-uploads the rest to an open-source mapping platform. These kinds of privacy hypocrisies always reveal the real story.

🏙️ A man decides to finally drone-map one of the wealthiest and most private cities in America — North Oaks, Minnesota, the only unmapped city left in the country. After he posts the footage, the city sends him a legal letter accusing him of invading their privacy and telling him never to return. He then discovers something that completely flips the script: the city has been using Flock surveillance cameras at every single entrance and exit, tracking every vehicle that comes and goes. This double standard launches him into a two-month deep dive into America’s massive surveillance system. In the end, he removes all his Street View images from Google Maps — except for one drone selfie of himself — and immediately re-uploads the rest to an open-source mapping platform. These kinds of privacy hypocrisies always reveal the real story.

End3of6Days9 (Helen) 🇺🇸

360,383 просмотров • 4 месяцев назад