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Germany is so back. Munich drone startup Quantum Systems just raised $1.2 billion at an $8 billion valuation. 14 months ago the company was worth $1 billion. it tripled in November, then more than doubled again this week. the origin story is my favorite part: founder Florian Seibel is... a former Bundeswehr helicopter pilot who spent years selling electric survey drones to farmers and construction companies. boring, profitable, invisible. then Russia invaded Ukraine. suddenly his tech that mapped cornfields was exactly what a modern battlefield needed. their flagship drone is called the Vector: it takes off vertically like a helicopter. at altitude, the rotors physically swivel forward and it becomes a fixed-wing plane. which means one soldier can launch it from a forest clearing or a muddy ditch in under 2 minutes. no runway, no catapult, no launch crew. the software is the actual moat though: > it flies without GPS. Russian jamming kills ordinary drones in seconds. Vector navigates by sight instead, the way a pilot reads the ground > it hears artillery. acoustic sensors catch enemy guns firing and the AI locates the position > one operator runs a whole swarm. the mission-AI keeps coordinating even when individual drones get shot down mid-mission all of it is battle-proven: 19,000+ missions flown in Ukraine last year. they even opened a factory inside Ukraine. the reason why governments are lining up to purchase: most defense companies sell closed systems. locked software, locked data, dependency forever. Quantum Systems keeps everything open. the buyer owns the data and controls the software. and after 2 decades of depending on American defense tech, that's exactly what European capitals want to hear. the business underneath is legit too: ~€115M revenue in 2024 ~€300M projected for 2025, profitable. long Quantum Systems.show more

Ole Lehmann

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50,212 次观看 • 10 天前 •via X (Twitter)

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Ukraine has established a kill zone along the front, which makes it extremely difficult for the Russians to advance. Russians call it a drone zone, which extends 10 to 15 kilometers along the frontline. Essentially, within this drone zone, it is nearly impossible for the Russians to move except on foot and at night. And even then, they become targets. Ukraine has made drones its key defensive asset. ‼️This is not a "war fought by the poor," as some disparagingly say about Ukraine. This is a modern war. And Ukraine, over the last few years and right now, is changing the way modern wars are fought. Ukraine is demonstrating an incredible level of technical and technological innovation and adaptation of weapons and defense systems. Ukraine is emerging as a powerful military superpower in the midst of a major war, under the pressure of shelling, and in the face of losses. Ukraine has not just stood its ground; it has adapted and is now taking the war onto the enemy's territory. 📹: The Sun

Ukraine has established a kill zone along the front, which makes it extremely difficult for the Russians to advance. Russians call it a drone zone, which extends 10 to 15 kilometers along the frontline. Essentially, within this drone zone, it is nearly impossible for the Russians to move except on foot and at night. And even then, they become targets. Ukraine has made drones its key defensive asset. ‼️This is not a "war fought by the poor," as some disparagingly say about Ukraine. This is a modern war. And Ukraine, over the last few years and right now, is changing the way modern wars are fought. Ukraine is demonstrating an incredible level of technical and technological innovation and adaptation of weapons and defense systems. Ukraine is emerging as a powerful military superpower in the midst of a major war, under the pressure of shelling, and in the face of losses. Ukraine has not just stood its ground; it has adapted and is now taking the war onto the enemy's territory. 📹: The Sun

Anton Gerashchenko

202,728 次观看 • 3 个月前

NEW LONG FORM VIDEO: The rise and fall of OnlyFans The owner of OnlyFans made $700 million last year with just 46 employees and no debt. By almost any measure, it’s one of the most profitable businesses on the internet. About a year ago, the owner tried to sell the company and has been struggling ever since to get the price he wants. So why is one of the most profitable businesses in internet history so hard to sell? The answer goes back to how the business was built. It all started with a $10,000 loan from a father to his son to launch the company. Today, more than $7.2 billion in revenue flows through OnlyFans each year. If a business generating $700 million in annual cash flow were publicly traded, it would likely be valued in the tens of billions of dollars. But here we are, and OnlyFans is still stuck on the market. And look, this is a complicated story. OnlyFans is an adult content platform, which makes it one of the more challenging businesses to analyze and talk about openly. Still, there are some fascinating business lessons behind how it grew, why it became so profitable, and why selling it has proven so difficult.

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NEW LONG FORM VIDEO: The rise and fall of OnlyFans The owner of OnlyFans made $700 million last year with just 46 employees and no debt. By almost any measure, it’s one of the most profitable businesses on the internet. About a year ago, the owner tried to sell the company and has been struggling ever since to get the price he wants. So why is one of the most profitable businesses in internet history so hard to sell? The answer goes back to how the business was built. It all started with a $10,000 loan from a father to his son to launch the company. Today, more than $7.2 billion in revenue flows through OnlyFans each year. If a business generating $700 million in annual cash flow were publicly traded, it would likely be valued in the tens of billions of dollars. But here we are, and OnlyFans is still stuck on the market. And look, this is a complicated story. OnlyFans is an adult content platform, which makes it one of the more challenging businesses to analyze and talk about openly. Still, there are some fascinating business lessons behind how it grew, why it became so profitable, and why selling it has proven so difficult.

Michael Girdley

95,409 次观看 • 3 个月前

🚨🇺🇦 UKRAINE IS TURNING AI INTO THE UPPER HAND: DRONES, SNIPER TECH, AND ALGORITHMIC WARFARE In the rolling fields of eastern Ukraine, a soldier peers through the scope of a rifle pointed at a target 2 and a half miles away. At that distance, even the Earth’s curve starts to matter. In older wars, this kind of shot would have been impossible - mythical even. But when the trigger is pulled, the impossible happens: a bullet arcs through the air and finds its mark. A new world record. The secret wasn’t just the shooter’s steady hand. It was an alliance of man, machine, and math - AI-powered optics calculating wind, humidity, and drop, while a drone overhead fed real-time telemetry into the rifle’s brain. That single shot is the metaphor for Ukraine’s entire war. Russia has the size - tanks, jets, bodies to burn. Ukraine has the brains - algorithms, drones, precision. Ukraine’s Unmanned Systems Forces isn’t a sideshow. It’s a whole new branch of the military, running swarms of drones that hit tens of thousands of Russian targets every month. Some drones distract, others jam, and the killers dive last. AI makes this possible. Drones fly beyond line-of-sight, reroute around jammers, and finish missions even when cut off from human pilots. That’s how Ukrainian drones just lit up Russia’s Saratov oil refinery, slicing into Moscow’s fuel supply lines. Earlier this month, AI-guided strikes crippled Ryazan and Novokuibyshevsk refineries - knocking them offline for weeks and cutting Russia’s war machine at the knees. Behind the frontline is Brave1, Ukraine’s innovation engine. It takes battlefield requests - “make a drone that can dodge jammers” - and spits out prototypes in months, not years. Think Silicon Valley, but instead of apps, the product is software-guided kamikaze drones that can fly 600 km deep into Russia. Even NATO defense startups are plugging into this ecosystem, testing autonomous drones in Ukraine’s skies like it’s the world’s deadliest beta test. Every mission trains the algorithms, making the next strike smarter and sharper. Russia wanted a war of numbers. Ukraine made it a war of code. And in that fight, Moscow’s massive army looks like a dinosaur charging headfirst into a digital age. Sources: Reuters, BBC, Kyiv Independent, Politico

🚨🇺🇦 UKRAINE IS TURNING AI INTO THE UPPER HAND: DRONES, SNIPER TECH, AND ALGORITHMIC WARFARE In the rolling fields of eastern Ukraine, a soldier peers through the scope of a rifle pointed at a target 2 and a half miles away. At that distance, even the Earth’s curve starts to matter. In older wars, this kind of shot would have been impossible - mythical even. But when the trigger is pulled, the impossible happens: a bullet arcs through the air and finds its mark. A new world record. The secret wasn’t just the shooter’s steady hand. It was an alliance of man, machine, and math - AI-powered optics calculating wind, humidity, and drop, while a drone overhead fed real-time telemetry into the rifle’s brain. That single shot is the metaphor for Ukraine’s entire war. Russia has the size - tanks, jets, bodies to burn. Ukraine has the brains - algorithms, drones, precision. Ukraine’s Unmanned Systems Forces isn’t a sideshow. It’s a whole new branch of the military, running swarms of drones that hit tens of thousands of Russian targets every month. Some drones distract, others jam, and the killers dive last. AI makes this possible. Drones fly beyond line-of-sight, reroute around jammers, and finish missions even when cut off from human pilots. That’s how Ukrainian drones just lit up Russia’s Saratov oil refinery, slicing into Moscow’s fuel supply lines. Earlier this month, AI-guided strikes crippled Ryazan and Novokuibyshevsk refineries - knocking them offline for weeks and cutting Russia’s war machine at the knees. Behind the frontline is Brave1, Ukraine’s innovation engine. It takes battlefield requests - “make a drone that can dodge jammers” - and spits out prototypes in months, not years. Think Silicon Valley, but instead of apps, the product is software-guided kamikaze drones that can fly 600 km deep into Russia. Even NATO defense startups are plugging into this ecosystem, testing autonomous drones in Ukraine’s skies like it’s the world’s deadliest beta test. Every mission trains the algorithms, making the next strike smarter and sharper. Russia wanted a war of numbers. Ukraine made it a war of code. And in that fight, Moscow’s massive army looks like a dinosaur charging headfirst into a digital age. Sources: Reuters, BBC, Kyiv Independent, Politico

Mario Nawfal

167,140 次观看 • 11 个月前

🇺🇸 MEET X-BAT: AMERICA’S NEW AI-POWERED FIGHTER JET WITH NO PILOT Shield AI just unveiled the X-Bat, a next-gen fighter jet that flies itself, takes off like a helicopter, and doesn’t need a runway. It’s powered by Hivemind, their custom AI pilot, and can fly 2,000 miles, reach 50,000 feet, and pack missiles. It’s built for combat, can launch from a ship in the middle of nowhere, and costs just $27 million, compared to the $100M+ F-35. The X-Bat reflects a fast-growing trend in warfare: AI-driven drones taking the lead. In Ukraine, drones have become central to modern combat, shifting the way battles are fought. Drone expert and senior aviation lecturer at UNSW Canberra, Oleksandra Molloy: “What we see from the war in Ukraine and the Middle East, they are tactically, operationally and strategically absolutely important weapons. We have seen a lack of those systems from the U.S., and particularly, we have not really seen the presence of many American companies in the real battlefield.” The U.S. government is now racing to catch up. In June, Trump signed an executive order called Unleashing American Drone Dominance, designed to fast-track drone commercialization and fold AI-powered aircraft into U.S. airspace - with billions from the Big Beautiful Bill fueling unmanned and AI defense tech. Shield AI is aiming to disrupt the defense giants and already landed a $200M Coast Guard deal. Backed by $5.3B in funding and a nudge from Trump’s Drone Dominance order, Shield AI says it’s building the future of war. Source: CNBC

🇺🇸 MEET X-BAT: AMERICA’S NEW AI-POWERED FIGHTER JET WITH NO PILOT Shield AI just unveiled the X-Bat, a next-gen fighter jet that flies itself, takes off like a helicopter, and doesn’t need a runway. It’s powered by Hivemind, their custom AI pilot, and can fly 2,000 miles, reach 50,000 feet, and pack missiles. It’s built for combat, can launch from a ship in the middle of nowhere, and costs just $27 million, compared to the $100M+ F-35. The X-Bat reflects a fast-growing trend in warfare: AI-driven drones taking the lead. In Ukraine, drones have become central to modern combat, shifting the way battles are fought. Drone expert and senior aviation lecturer at UNSW Canberra, Oleksandra Molloy: “What we see from the war in Ukraine and the Middle East, they are tactically, operationally and strategically absolutely important weapons. We have seen a lack of those systems from the U.S., and particularly, we have not really seen the presence of many American companies in the real battlefield.” The U.S. government is now racing to catch up. In June, Trump signed an executive order called Unleashing American Drone Dominance, designed to fast-track drone commercialization and fold AI-powered aircraft into U.S. airspace - with billions from the Big Beautiful Bill fueling unmanned and AI defense tech. Shield AI is aiming to disrupt the defense giants and already landed a $200M Coast Guard deal. Backed by $5.3B in funding and a nudge from Trump’s Drone Dominance order, Shield AI says it’s building the future of war. Source: CNBC

Mario Nawfal

900,172 次观看 • 8 个月前

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Ricardo

159,113 次观看 • 2 个月前

🚨🇷🇺 WEST'S WORST NIGHTMARE: Russia Building the War Machine of Tomorrow After four years of fighting in Ukraine, Russia has created a smart, practical way to build new weapons and systems. They focus on what actually works on the battlefield, not fancy stuff. 🔸 Russia plans to train 1 million specialists in drones and unmanned systems by 2030. 🔸 They’re boosting AI experts by more than 400% every year. 🔸 Russian V2U drones can now fly, find targets, and attack completely on their own — even when signals are jammed. 🔸 Russia made over 30 major upgrades to Iranian Shahed drones in under 3 years, developing an entire line of Geran drones. 🔸 New Glaz/Groza software lets them spot a target and hit it with artillery in just minutes instead of hours. 🔸Russia is empowering students, volunteers, and even “garage” inventors. Their own Defense Minister proudly supports this decentralized energy. The scary part? These same Russian-backed drone tactics are already hitting American bases in the Middle East, not just in Ukraine. Do you think the West is capable of keeping up with Russia's pace of innovation?

🚨🇷🇺 WEST'S WORST NIGHTMARE: Russia Building the War Machine of Tomorrow After four years of fighting in Ukraine, Russia has created a smart, practical way to build new weapons and systems. They focus on what actually works on the battlefield, not fancy stuff. 🔸 Russia plans to train 1 million specialists in drones and unmanned systems by 2030. 🔸 They’re boosting AI experts by more than 400% every year. 🔸 Russian V2U drones can now fly, find targets, and attack completely on their own — even when signals are jammed. 🔸 Russia made over 30 major upgrades to Iranian Shahed drones in under 3 years, developing an entire line of Geran drones. 🔸 New Glaz/Groza software lets them spot a target and hit it with artillery in just minutes instead of hours. 🔸Russia is empowering students, volunteers, and even “garage” inventors. Their own Defense Minister proudly supports this decentralized energy. The scary part? These same Russian-backed drone tactics are already hitting American bases in the Middle East, not just in Ukraine. Do you think the West is capable of keeping up with Russia's pace of innovation?

NewRulesGeopolitics

72,039 次观看 • 2 个月前

$Big Tech's $1 trillion AI moat just got DESTROYED by a free Chinese download. Microsoft, Amazon, Google, and Meta are pouring fortunes into chips and data centers because they have been told that whoever builds the biggest model wins, and that lead becomes a fortress no one can cross. Last week a lab called Zhipu - it trades in Hong Kong as Knowledge Atlas Technology - released a model called GLM-5.2 and destroyed that idea in a single afternoon. It's open weights under an MIT license, which means anyone on earth can download it and build on it for free. On the coding and design benchmarks that actually matter, it went toe to toe with the best models America has - matching even Anthropic's Mythos-class work and beating OpenAI's flagship outright on the coding test everyone watches. And it does the work at roughly one-sixth the price. ONE-SIXTH And barely a year and a half ago a model called DeepSeek did the same thing and wiped the better part of $600 billion off Nvidia in a single session. This was only the first chapter. You cannot dig a moat around something your competitor is happy to give away. If 95% of frontier capability is free, open, and runs at a fraction of the cost, then the hundreds of billions being spent to defend the last 5% is NOT a moat. And now for the irony: The company that just proved the moat is worthless is itself the single most absurd valuation I have seen in a long career of watching absurd valuations. Zhipu did about $105 million in revenue last year and lost more than 4x what it took in. This week the market handed it a value of roughly $128 billion - at the peak, north of a 1,000x sales - on a float so thin that barely 4% of the stock actually trades. THINK about this... A company drowning in losses, doing 9 figures of revenue, priced like it does hundreds of billions, with almost nothing available to sell. So we now have a bubble in China detonating the entire justification for a bubble in America. Two manias pointed straight at each other. This is the lesson I've spent 45 years trying to beat into people. You can ignore valuation for a long time but you cannot ignore it forever. A moat story sold a trillion dollars of spending, a free download just exposed it, and the company that exposed it is priced for a fantasy of its own. When the picks-and-shovels crowd loses its monopoly on the picks, you want to be very careful what you are paying for the shovels. Numbers don't lie. Shoutout to Limitless - they were onto this story before almost anyone on Wall Street. One of the sharpest AI shows out there.$

Big Tech's $1 trillion AI moat just got DESTROYED by a free Chinese download. Microsoft, Amazon, Google, and Meta are pouring fortunes into chips and data centers because they have been told that whoever builds the biggest model wins, and that lead becomes a fortress no one can cross. Last week a lab called Zhipu - it trades in Hong Kong as Knowledge Atlas Technology - released a model called GLM-5.2 and destroyed that idea in a single afternoon. It's open weights under an MIT license, which means anyone on earth can download it and build on it for free. On the coding and design benchmarks that actually matter, it went toe to toe with the best models America has - matching even Anthropic's Mythos-class work and beating OpenAI's flagship outright on the coding test everyone watches. And it does the work at roughly one-sixth the price. ONE-SIXTH And barely a year and a half ago a model called DeepSeek did the same thing and wiped the better part of $600 billion off Nvidia in a single session. This was only the first chapter. You cannot dig a moat around something your competitor is happy to give away. If 95% of frontier capability is free, open, and runs at a fraction of the cost, then the hundreds of billions being spent to defend the last 5% is NOT a moat. And now for the irony: The company that just proved the moat is worthless is itself the single most absurd valuation I have seen in a long career of watching absurd valuations. Zhipu did about $105 million in revenue last year and lost more than 4x what it took in. This week the market handed it a value of roughly $128 billion - at the peak, north of a 1,000x sales - on a float so thin that barely 4% of the stock actually trades. THINK about this... A company drowning in losses, doing 9 figures of revenue, priced like it does hundreds of billions, with almost nothing available to sell. So we now have a bubble in China detonating the entire justification for a bubble in America. Two manias pointed straight at each other. This is the lesson I've spent 45 years trying to beat into people. You can ignore valuation for a long time but you cannot ignore it forever. A moat story sold a trillion dollars of spending, a free download just exposed it, and the company that exposed it is priced for a fantasy of its own. When the picks-and-shovels crowd loses its monopoly on the picks, you want to be very careful what you are paying for the shovels. Numbers don't lie. Shoutout to Limitless - they were onto this story before almost anyone on Wall Street. One of the sharpest AI shows out there.

George Noble

69,599 次观看 • 19 天前

What's happening in Ukraine right now is rewriting modern warfare. We need to be paying more attention and learn from our friends in Kyiv. - Over 12,000 drones were operating over a city the size of Hereford in a single day. Yes… one day. - 90% of casualties are caused by drones. Not artillery or rifles. Just drones. - Russia is close to building a million drones a month. Ukraine is trying to match them. - Russia's uncrewed systems force is 80,000 strong. That is bigger than our entire Army. Britain has to catch up and we don't have the luxury of time to do it. We MUST: - Treat drones as ammunition. - Build up always-on drone production here in the UK. - Centralise the data. Use AI to make them smarter. - Stand up an uncrewed systems force now. Not after a review at some point in future… but now. - Cut the rules choking off trial and testing. - Joint ventures between British and Ukrainian industry. They've learnt more in a few years than most countries learn in thirty… - Work with Ukrainian veterans to test how we exercise and operate. Remember: A £4000 drone can take out a £4million tank.

What's happening in Ukraine right now is rewriting modern warfare. We need to be paying more attention and learn from our friends in Kyiv. - Over 12,000 drones were operating over a city the size of Hereford in a single day. Yes… one day. - 90% of casualties are caused by drones. Not artillery or rifles. Just drones. - Russia is close to building a million drones a month. Ukraine is trying to match them. - Russia's uncrewed systems force is 80,000 strong. That is bigger than our entire Army. Britain has to catch up and we don't have the luxury of time to do it. We MUST: - Treat drones as ammunition. - Build up always-on drone production here in the UK. - Centralise the data. Use AI to make them smarter. - Stand up an uncrewed systems force now. Not after a review at some point in future… but now. - Cut the rules choking off trial and testing. - Joint ventures between British and Ukrainian industry. They've learnt more in a few years than most countries learn in thirty… - Work with Ukrainian veterans to test how we exercise and operate. Remember: A £4000 drone can take out a £4million tank.

Al Carns

107,333 次观看 • 16 天前

Elon Musk's biggest competitor is secretly paying him $1.25 BILLION per month. SpaceX just revealed its financials for the first time in 23 years of existence. And buried deep in the S-1 is a detail that changes how you should think about the entire AI race. Anthropic, the company building Claude, the company that positions itself as OpenAI's biggest threat, the company valued at over $100 billion, is paying SpaceX $1.25 billion EVERY SINGLE MONTH for compute capacity through May 2029. That is $15 billion a year flowing directly from Elon's top AI competitor into Elon's bank account. Think about what that means: Every time Anthropic trains a new model, improves Claude, or lands an enterprise customer, a massive chunk of that revenue goes straight to the guy who owns the competing AI product. Anthropic is literally funding the war against itself. And that's just the beginning of what this filing reveals... The entire SpaceX IPO is structured around a bet most people haven't figured out yet. In 2025, SpaceX spent $20 billion in capex. 60% of that, roughly $12 billion, went to AI infrastructure. Rockets and satellites got the leftovers. In Q1 2026 alone, $7.7 billion out of $10 billion in total capex went to AI. The "rocket company" is spending like an AI company. Meanwhile, xAI, the division that houses Grok, generated $3.2 billion in revenue for the full year of 2025. But its R&D costs TRIPLED to $5 billion. It's burning cash at a pace that would have destroyed it as a standalone company. Which is exactly why Elon merged it into SpaceX two months before filing the IPO. And Starlink is the engine that makes the whole thing work: $11.4 billion in revenue, $4.4 billion in operating profit, and 10.3 million subscribers across 164 countries. It's one of the most profitable subscription businesses on the planet right now. But the average revenue per user DROPPED from $99 per month in 2023 to $66 per month in March 2026. Subscribers quadrupled but each one is paying a third less. Starlink is growing by getting cheaper. SpaceX has lost $37 BILLION since it was founded. Net loss in 2025 was $4.9 billion. This is a company that has never turned an annual profit in 23 years of operation, and it is about to IPO at a $1.75 trillion valuation. And the total addressable market SpaceX claims in the filing is $28.5 trillion. That is a QUARTER of global GDP. So here is what investors are actually buying when this IPO prices: They are buying the most profitable satellite internet business in history, stapled to an AI lab that is burning cash, wrapped inside a Mars colonization pitch that requires building a permanent city on another planet, funded by monthly billion-dollar payments from a direct competitor who has no other option for compute at that scale. This is the kind of thing only Elon could pull off.

Elon Musk's biggest competitor is secretly paying him $1.25 BILLION per month. SpaceX just revealed its financials for the first time in 23 years of existence. And buried deep in the S-1 is a detail that changes how you should think about the entire AI race. Anthropic, the company building Claude, the company that positions itself as OpenAI's biggest threat, the company valued at over $100 billion, is paying SpaceX $1.25 billion EVERY SINGLE MONTH for compute capacity through May 2029. That is $15 billion a year flowing directly from Elon's top AI competitor into Elon's bank account. Think about what that means: Every time Anthropic trains a new model, improves Claude, or lands an enterprise customer, a massive chunk of that revenue goes straight to the guy who owns the competing AI product. Anthropic is literally funding the war against itself. And that's just the beginning of what this filing reveals... The entire SpaceX IPO is structured around a bet most people haven't figured out yet. In 2025, SpaceX spent $20 billion in capex. 60% of that, roughly $12 billion, went to AI infrastructure. Rockets and satellites got the leftovers. In Q1 2026 alone, $7.7 billion out of $10 billion in total capex went to AI. The "rocket company" is spending like an AI company. Meanwhile, xAI, the division that houses Grok, generated $3.2 billion in revenue for the full year of 2025. But its R&D costs TRIPLED to $5 billion. It's burning cash at a pace that would have destroyed it as a standalone company. Which is exactly why Elon merged it into SpaceX two months before filing the IPO. And Starlink is the engine that makes the whole thing work: $11.4 billion in revenue, $4.4 billion in operating profit, and 10.3 million subscribers across 164 countries. It's one of the most profitable subscription businesses on the planet right now. But the average revenue per user DROPPED from $99 per month in 2023 to $66 per month in March 2026. Subscribers quadrupled but each one is paying a third less. Starlink is growing by getting cheaper. SpaceX has lost $37 BILLION since it was founded. Net loss in 2025 was $4.9 billion. This is a company that has never turned an annual profit in 23 years of operation, and it is about to IPO at a $1.75 trillion valuation. And the total addressable market SpaceX claims in the filing is $28.5 trillion. That is a QUARTER of global GDP. So here is what investors are actually buying when this IPO prices: They are buying the most profitable satellite internet business in history, stapled to an AI lab that is burning cash, wrapped inside a Mars colonization pitch that requires building a permanent city on another planet, funded by monthly billion-dollar payments from a direct competitor who has no other option for compute at that scale. This is the kind of thing only Elon could pull off.

Ricardo

208,495 次观看 • 1 个月前

🚨WATCH THIS CAREFULLY… Bookmark for later. You want to see this. An AH-64 Apache just erased another Iranian attack drone from the sky. You can hear the crew calling it out… “Target destroyed.” Seconds later… another one. Destroyed. These aren’t large aircraft. They’re single-prop attack drones… the kind Iran and its proxies have been flooding the region with. Small. Cheap. Hard to detect. But incredibly dangerous. Many of these drones have operational ranges pushing 2,000 kilometers. Think about that for a second. Two thousand kilometers. That means a drone launched from deep inside hostile territory can travel across borders… across seas… and still reach major cities. Which raises a few very serious questions… Where exactly are these drones being launched from? Who is supplying them? Who is coordinating the targeting data? Because a drone doesn’t just magically know where a refinery… port… airport… or city skyline is located. Someone is feeding coordinates. Someone is providing guidance. Someone is directing these strikes. And now American-made AH-64 Apache helicopters are in the air hunting them down one by one. The Apache isn’t just a helicopter… It’s a flying battlefield computer. Longbow radar. Infrared targeting. Night dominance. Hellfire missiles. 30mm cannon. Designed for one purpose… Find the threat. Lock it. Erase it. In this footage you can literally hear the moment the drone disappears from the sky. “Target destroyed.” But the real question remains… Who keeps sending them? Because every drone shot down tells us something important… There is an entire launch network somewhere behind it. Launch sites. Operators. Command signals. Targeting data. And until that network is exposed… The drones will keep coming. Watch the clip closely. This is modern warfare in real time. Cheap drones… versus the most advanced attack helicopter on earth. And right now… the Apache is winning. #ApacheHelicopter #DroneWarfare #SilentMajoritySpeaks #AStoneGroove

🚨WATCH THIS CAREFULLY… Bookmark for later. You want to see this. An AH-64 Apache just erased another Iranian attack drone from the sky. You can hear the crew calling it out… “Target destroyed.” Seconds later… another one. Destroyed. These aren’t large aircraft. They’re single-prop attack drones… the kind Iran and its proxies have been flooding the region with. Small. Cheap. Hard to detect. But incredibly dangerous. Many of these drones have operational ranges pushing 2,000 kilometers. Think about that for a second. Two thousand kilometers. That means a drone launched from deep inside hostile territory can travel across borders… across seas… and still reach major cities. Which raises a few very serious questions… Where exactly are these drones being launched from? Who is supplying them? Who is coordinating the targeting data? Because a drone doesn’t just magically know where a refinery… port… airport… or city skyline is located. Someone is feeding coordinates. Someone is providing guidance. Someone is directing these strikes. And now American-made AH-64 Apache helicopters are in the air hunting them down one by one. The Apache isn’t just a helicopter… It’s a flying battlefield computer. Longbow radar. Infrared targeting. Night dominance. Hellfire missiles. 30mm cannon. Designed for one purpose… Find the threat. Lock it. Erase it. In this footage you can literally hear the moment the drone disappears from the sky. “Target destroyed.” But the real question remains… Who keeps sending them? Because every drone shot down tells us something important… There is an entire launch network somewhere behind it. Launch sites. Operators. Command signals. Targeting data. And until that network is exposed… The drones will keep coming. Watch the clip closely. This is modern warfare in real time. Cheap drones… versus the most advanced attack helicopter on earth. And right now… the Apache is winning. #ApacheHelicopter #DroneWarfare #SilentMajoritySpeaks #AStoneGroove

A Gene Robinson

64,174 次观看 • 4 个月前

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dustin

318,457 次观看 • 4 个月前

The current position of Europe is clear: Ukraine will receive support, but only within limits that do not provoke a Russian attack against the countries providing that assistance. Ukrainians understood long ago that NATO would not close our skies. But look: Ukraine had no weapons at the beginning of the full-scale war in 2022, and now, in 2026, Ukrainian drones are striking targets deep in Russia’s Ural, while Putin is afraid to hold a military parade on Red Square in Moscow without extraordinary security measures. Ukraine is now helping strengthen air defense systems in the Middle East through our battlefield experience and technological expertise, and is a strategic partner for countries in that region. Ukraine tries to shoot down every possible Russian drone, including those flying toward neighboring countries such as Romania, Moldova, and Poland. Ukraine is building a modern air defense architecture that will help protect not only Ukraine, but also our neighbors from Russian drones and missiles. It is important to help Ukraine strengthen our air defense and produce interceptor missiles. This will also strengthen Europe’s defense against Russia.

The current position of Europe is clear: Ukraine will receive support, but only within limits that do not provoke a Russian attack against the countries providing that assistance. Ukrainians understood long ago that NATO would not close our skies. But look: Ukraine had no weapons at the beginning of the full-scale war in 2022, and now, in 2026, Ukrainian drones are striking targets deep in Russia’s Ural, while Putin is afraid to hold a military parade on Red Square in Moscow without extraordinary security measures. Ukraine is now helping strengthen air defense systems in the Middle East through our battlefield experience and technological expertise, and is a strategic partner for countries in that region. Ukraine tries to shoot down every possible Russian drone, including those flying toward neighboring countries such as Romania, Moldova, and Poland. Ukraine is building a modern air defense architecture that will help protect not only Ukraine, but also our neighbors from Russian drones and missiles. It is important to help Ukraine strengthen our air defense and produce interceptor missiles. This will also strengthen Europe’s defense against Russia.

Anton Gerashchenko

34,622 次观看 • 1 个月前

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 次观看 • 1 个月前

$This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.$

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.

Ricardo

1,813,369 次观看 • 5 个月前

Hezbollah’s fiber-optic FPV drones, which cost under $500, are disabling Israeli Merkava tanks worth $5 to 7 million. The IOF does not have a single weapon in their arsenal that can detect these new drones, which are completely immune to traditional electronic jamming devices. VPol journalist Calla Walsh (Calla) explains. ￭ Rather than a radio link, the fiber-optic drones are physically tethered to their operator by an ultra-thin fiber-optic cable that stretches for up to 60km, transmitting video and data back to the pilot. ￭ The Israeli occupation has been shocked by the introduction of these drones into the battlefield, and there is no indication the IOF had any foresight or intel on Hezbollah’s supply chain. ￭ These drones were first deployed by Russia and Ukraine, but there’s no sign of direct Russian involvement, nor is there any need for it. Rather, Hezbollah is closely studying other warzones to innovate and adapt for their own battle against Israeli occupation, and information on fiber-optic FPVs is open-source. ￭ Israeli media describes it as “a technological arms race, and although Israel is at the forefront of interception technology, there is currently no complete solution to the threat… the battlefield in Lebanon proves that sometimes a single thin thread can threaten even the most heavily armored technological systems… Israel possesses Arrow missiles and F-35 Lightning II aircraft, but it has failed to deal with cheap explosive drones in southern Lebanon.”

Hezbollah’s fiber-optic FPV drones, which cost under $500, are disabling Israeli Merkava tanks worth $5 to 7 million. The IOF does not have a single weapon in their arsenal that can detect these new drones, which are completely immune to traditional electronic jamming devices. VPol journalist Calla Walsh (Calla) explains. ￭ Rather than a radio link, the fiber-optic drones are physically tethered to their operator by an ultra-thin fiber-optic cable that stretches for up to 60km, transmitting video and data back to the pilot. ￭ The Israeli occupation has been shocked by the introduction of these drones into the battlefield, and there is no indication the IOF had any foresight or intel on Hezbollah’s supply chain. ￭ These drones were first deployed by Russia and Ukraine, but there’s no sign of direct Russian involvement, nor is there any need for it. Rather, Hezbollah is closely studying other warzones to innovate and adapt for their own battle against Israeli occupation, and information on fiber-optic FPVs is open-source. ￭ Israeli media describes it as “a technological arms race, and although Israel is at the forefront of interception technology, there is currently no complete solution to the threat… the battlefield in Lebanon proves that sometimes a single thin thread can threaten even the most heavily armored technological systems… Israel possesses Arrow missiles and F-35 Lightning II aircraft, but it has failed to deal with cheap explosive drones in southern Lebanon.”

VPol

52,653 次观看 • 2 个月前

The man who INVENTED modern AI just made a billion dollar bet that ChatGPT, Claude, and every AI company on earth is building the wrong technology. Yann LeCun won the Turing Award in 2018 for creating the neural networks that made AI possible. He spent a decade running AI research at Meta. Oversaw the creation of Llama and PyTorch, the tools that half the AI industry runs on. Then he quit. And raised $1.03 billion in a seed round. The LARGEST seed round in European history. $3.5 billion valuation before generating a single dollar of revenue. Bezos wrote the check. So did Nvidia. Samsung. Toyota. Temasek. Eric Schmidt. Mark Cuban. Tim Berners-Lee (the guy who invented the internet). His new company is called AMI Labs. And it's built on one thesis: Every AI company spending billions on large language models is wasting their money. ChatGPT, Claude, Gemini, Grok. They all work the same way. They predict the next word in a sequence. See "the cat sat on the" and predict "mat." Scale that to trillions of words and you get something that sounds intelligent. But LeCun says it doesn't UNDERSTAND anything. It can't reason. It can't plan. It can't predict what happens when you push a glass off a table. A two year old can do that. GPT-5 cannot. That's why AI hallucinates. It doesn't have a model of how the world actually works. It just predicts words. His solution? Something called JEPA. Instead of predicting words, it learns how the PHYSICAL WORLD works. Abstract representations of reality. Not language but physics. Think about what that means. Current AI can write your emails. LeCun's AI could design a car, run a factory, operate a robot, or diagnose a patient without hallucinating and killing someone. The CEO of AMI said it perfectly: "Factories, hospitals, and robots need AI that grasps reality. Predicting tokens doesn't cut it." And here's what's really crazy to me... LeCun isn't some outsider throwing rocks. He literally built the foundations that ChatGPT runs on. He knows exactly how these systems work because he helped create them. And after watching the entire industry sprint in one direction for three years, he raised a billion dollars to run the OPPOSITE way. No product. No revenue. No timeline. Just pure research. He told investors it could take YEARS to produce anything commercial. But they funded it anyway in just four months. Meanwhile OpenAI just raised $120 billion and still can't stop their models from making things up. Anthropic is building AI so dangerous they're afraid to release it. Google is burning billions trying to catch up. And the guy who started it all says they're all solving the wrong problem. Two Turing Award winners raised $2 billion in three weeks betting AGAINST the entire LLM approach. LeCun at AMI. Fei-Fei Li at World Labs. The smartest people in AI are quietly building the exit from the technology everyone else is betting their future on. Either they're wrong and the trillion dollar LLM industry keeps printing. Or they're right and every AI company on earth just built on a foundation that's about to crack.

The man who INVENTED modern AI just made a billion dollar bet that ChatGPT, Claude, and every AI company on earth is building the wrong technology. Yann LeCun won the Turing Award in 2018 for creating the neural networks that made AI possible. He spent a decade running AI research at Meta. Oversaw the creation of Llama and PyTorch, the tools that half the AI industry runs on. Then he quit. And raised $1.03 billion in a seed round. The LARGEST seed round in European history. $3.5 billion valuation before generating a single dollar of revenue. Bezos wrote the check. So did Nvidia. Samsung. Toyota. Temasek. Eric Schmidt. Mark Cuban. Tim Berners-Lee (the guy who invented the internet). His new company is called AMI Labs. And it's built on one thesis: Every AI company spending billions on large language models is wasting their money. ChatGPT, Claude, Gemini, Grok. They all work the same way. They predict the next word in a sequence. See "the cat sat on the" and predict "mat." Scale that to trillions of words and you get something that sounds intelligent. But LeCun says it doesn't UNDERSTAND anything. It can't reason. It can't plan. It can't predict what happens when you push a glass off a table. A two year old can do that. GPT-5 cannot. That's why AI hallucinates. It doesn't have a model of how the world actually works. It just predicts words. His solution? Something called JEPA. Instead of predicting words, it learns how the PHYSICAL WORLD works. Abstract representations of reality. Not language but physics. Think about what that means. Current AI can write your emails. LeCun's AI could design a car, run a factory, operate a robot, or diagnose a patient without hallucinating and killing someone. The CEO of AMI said it perfectly: "Factories, hospitals, and robots need AI that grasps reality. Predicting tokens doesn't cut it." And here's what's really crazy to me... LeCun isn't some outsider throwing rocks. He literally built the foundations that ChatGPT runs on. He knows exactly how these systems work because he helped create them. And after watching the entire industry sprint in one direction for three years, he raised a billion dollars to run the OPPOSITE way. No product. No revenue. No timeline. Just pure research. He told investors it could take YEARS to produce anything commercial. But they funded it anyway in just four months. Meanwhile OpenAI just raised $120 billion and still can't stop their models from making things up. Anthropic is building AI so dangerous they're afraid to release it. Google is burning billions trying to catch up. And the guy who started it all says they're all solving the wrong problem. Two Turing Award winners raised $2 billion in three weeks betting AGAINST the entire LLM approach. LeCun at AMI. Fei-Fei Li at World Labs. The smartest people in AI are quietly building the exit from the technology everyone else is betting their future on. Either they're wrong and the trillion dollar LLM industry keeps printing. Or they're right and every AI company on earth just built on a foundation that's about to crack.

Ricardo

605,742 次观看 • 3 个月前

Big Tech just ran out of money building AI and what they're doing to cover it up should be illegal. Google, Amazon, Microsoft, and Meta are spending a combined $700 BILLION this year on AI infrastructure. This eats up 94% of their total operating cash flow. The richest companies in human history are almost broke. And instead of slowing down, they're covering it up with the biggest financial engineering operation since 2008: Google just sold $80 billion in stock to fund AI infrastructure. That was their first equity raise in 20 YEARS. The last time Google needed to sell stock, YouTube didn't even exist. Sundar Pichai admitted the thing keeping him up at night is "compute capacity." The company that prints $100 billion a year in ad revenue just told Wall Street it isn't enough anymore. Amazon's free cash flow is projected to go NEGATIVE this year for the first time ever. Morgan Stanley estimates a $17 billion deficit and Bank of America says $28 billion. The most profitable logistics machine on Earth is about to burn more cash than it generates, and they quietly filed with the SEC saying they may need to raise even more debt and equity to keep building. All four hyperscalers are now borrowing hundreds of billions in bonds to keep the AI buildout alive. These were the most cash-rich companies in human history, and they're leveraging themselves to the teeth to build infrastructure that nobody has proven will generate enough revenue to pay for itself. And the cracks are already starting to show: Broadcom makes the custom AI chips that power Google, Meta, OpenAI, and Anthropic. This week their AI revenue TRIPLED year over year, sales grew 48%, and profits smashed every Wall Street estimate. The reward for all of that was $320 billion in value erased in a single trading session. Their CEO Hock Tan went on the earnings call and exposed three things about the AI industry: Google is already shopping for cheaper AI chip alternatives, broadcom abandoned its strategy of selling complete AI systems and is now retreating to selling bare chips at lower margins. And despite supposedly "unprecedented demand," Tan refused to raise his full-year forecast, which tells you everything about what he's actually seeing behind the curtain. Wall Street heard all three and hit the sell button so hard it dragged AMD, Intel, and the entire chip sector down with it. When a company triples its AI revenue and gets punished because tripling isn't fast enough, the expectations have left the atmosphere entirely. And here's the really scary part... These companies ARE your retirement account. Apple, Microsoft, Amazon, Google, Meta, and Nvidia make up roughly 30% of the S&P 500. If you have a 401k or an index fund, you are already exposed to this bet whether you chose to be or not. Every single one of these companies is telling you AI will generate trillions in revenue. But right now the math says they're spending trillions FIRST and hoping the revenue shows up later. If the revenue catches up, this becomes the greatest infrastructure buildout in human history. Bigger than railroads and bigger than the internet. If it doesn't, the companies that make up a third of the American stock market just leveraged their balance sheets into the largest write-down cycle since 2000. And unlike the dot-com crash, this time the bubble companies aren't random startups with no revenue. They're the backbone of the entire global economy.

Big Tech just ran out of money building AI and what they're doing to cover it up should be illegal. Google, Amazon, Microsoft, and Meta are spending a combined $700 BILLION this year on AI infrastructure. This eats up 94% of their total operating cash flow. The richest companies in human history are almost broke. And instead of slowing down, they're covering it up with the biggest financial engineering operation since 2008: Google just sold $80 billion in stock to fund AI infrastructure. That was their first equity raise in 20 YEARS. The last time Google needed to sell stock, YouTube didn't even exist. Sundar Pichai admitted the thing keeping him up at night is "compute capacity." The company that prints $100 billion a year in ad revenue just told Wall Street it isn't enough anymore. Amazon's free cash flow is projected to go NEGATIVE this year for the first time ever. Morgan Stanley estimates a $17 billion deficit and Bank of America says $28 billion. The most profitable logistics machine on Earth is about to burn more cash than it generates, and they quietly filed with the SEC saying they may need to raise even more debt and equity to keep building. All four hyperscalers are now borrowing hundreds of billions in bonds to keep the AI buildout alive. These were the most cash-rich companies in human history, and they're leveraging themselves to the teeth to build infrastructure that nobody has proven will generate enough revenue to pay for itself. And the cracks are already starting to show: Broadcom makes the custom AI chips that power Google, Meta, OpenAI, and Anthropic. This week their AI revenue TRIPLED year over year, sales grew 48%, and profits smashed every Wall Street estimate. The reward for all of that was $320 billion in value erased in a single trading session. Their CEO Hock Tan went on the earnings call and exposed three things about the AI industry: Google is already shopping for cheaper AI chip alternatives, broadcom abandoned its strategy of selling complete AI systems and is now retreating to selling bare chips at lower margins. And despite supposedly "unprecedented demand," Tan refused to raise his full-year forecast, which tells you everything about what he's actually seeing behind the curtain. Wall Street heard all three and hit the sell button so hard it dragged AMD, Intel, and the entire chip sector down with it. When a company triples its AI revenue and gets punished because tripling isn't fast enough, the expectations have left the atmosphere entirely. And here's the really scary part... These companies ARE your retirement account. Apple, Microsoft, Amazon, Google, Meta, and Nvidia make up roughly 30% of the S&P 500. If you have a 401k or an index fund, you are already exposed to this bet whether you chose to be or not. Every single one of these companies is telling you AI will generate trillions in revenue. But right now the math says they're spending trillions FIRST and hoping the revenue shows up later. If the revenue catches up, this becomes the greatest infrastructure buildout in human history. Bigger than railroads and bigger than the internet. If it doesn't, the companies that make up a third of the American stock market just leveraged their balance sheets into the largest write-down cycle since 2000. And unlike the dot-com crash, this time the bubble companies aren't random startups with no revenue. They're the backbone of the entire global economy.

Ricardo

227,397 次观看 • 1 个月前

Nebius will be a trillion dollar company (Save this). The neocloud market, purpose-built AI cloud infrastructure, separate from legacy hyperscalers generated roughly $25 billion in revenue in 2025, up 223% year over year. Synergy Research projects it will approach $400 billion by 2031, compounding at 58% annually one of the fastest sustained growth rates ever recorded for an infrastructure category of this scale. The CEO's explanation for why they win is worth understanding in detail. GPU compute is scarce and that part everyone knows but Nebius is not simply renting GPUs by the hour and marking them up, which is what most neocloud imitators do. They have built their own physical capacity for inference, optimized the full technology stack from the software layer all the way down to the rack hardware and recently acquired a company called Agen specifically to push inference latency even lower and throughput even higher. The CEO frames the core problem directly that in 2026, every product you build is powered by tokens, AI intelligence and while you can get those tokens from OpenAI or Anthropic via a simple API call, the moment you want to run open source models, specialized vertical models, or anything other than the two dominant frontier labs, you run into a wall. You can download the weights from Hugging Face and assemble the pieces. But getting those workloads to run at scale, at the economics you need, with the reliability your product requires, is an extraordinarily complex engineering challenge that most companies cannot staff or afford to solve in-house. That is the problem Nebius is solving, and that is why their inference product called Token Factory exists. The financial results are among the most dramatic growth numbers reported by any public company this year. In Q1 2026, Nebius posted $399 million in revenue, a 684% increase from the same quarter a year earlier. In the span of twelve months, the company swung from a $104 million net loss to $621 million in net income. Cash from operations went from negative $184 million to positive $2.26 billion in the same period meaning this is not growth funded by burning investor capital, it is growth that is now generating its own fuel. For the full year 2026, Nebius is guiding for an annualized revenue run rate of $7 billion to $9 billion, with pipeline creation tracking to surpass $4 billion. The contracted backlog sits at $49 billion, anchored by a $27 billion agreement with Meta, a deal worth up to $19.4 billion with Microsoft, and a public endorsement from Jensen Huang at NVIDIA's GTC conference in 2026. The current market cap is approximately $56 billion. A company with $7 to $9 billion in annualized revenue, growing at 684%, turning cash-flow positive, sitting on $49 billion in contracted backlog, operating in a market compounding at 58% annually toward $400 billion, that company has a credible path to 20x from its current valuation if execution holds. That is the trillion dollar case, and it does not require any heroic assumptions and it requires Nebius to keep doing what it is already demonstrably doing. Milk Road Pro called this one early. Our analysts added Nebius to the portfolio when it was still flying under the radar, and we are sitting on a massive gain on that position right now. If you want to see what else we are building conviction on before the rest of the market catches up, come join us at Milk Road Pro using the link below!

Nebius will be a trillion dollar company (Save this). The neocloud market, purpose-built AI cloud infrastructure, separate from legacy hyperscalers generated roughly $25 billion in revenue in 2025, up 223% year over year. Synergy Research projects it will approach $400 billion by 2031, compounding at 58% annually one of the fastest sustained growth rates ever recorded for an infrastructure category of this scale. The CEO's explanation for why they win is worth understanding in detail. GPU compute is scarce and that part everyone knows but Nebius is not simply renting GPUs by the hour and marking them up, which is what most neocloud imitators do. They have built their own physical capacity for inference, optimized the full technology stack from the software layer all the way down to the rack hardware and recently acquired a company called Agen specifically to push inference latency even lower and throughput even higher. The CEO frames the core problem directly that in 2026, every product you build is powered by tokens, AI intelligence and while you can get those tokens from OpenAI or Anthropic via a simple API call, the moment you want to run open source models, specialized vertical models, or anything other than the two dominant frontier labs, you run into a wall. You can download the weights from Hugging Face and assemble the pieces. But getting those workloads to run at scale, at the economics you need, with the reliability your product requires, is an extraordinarily complex engineering challenge that most companies cannot staff or afford to solve in-house. That is the problem Nebius is solving, and that is why their inference product called Token Factory exists. The financial results are among the most dramatic growth numbers reported by any public company this year. In Q1 2026, Nebius posted $399 million in revenue, a 684% increase from the same quarter a year earlier. In the span of twelve months, the company swung from a $104 million net loss to $621 million in net income. Cash from operations went from negative $184 million to positive $2.26 billion in the same period meaning this is not growth funded by burning investor capital, it is growth that is now generating its own fuel. For the full year 2026, Nebius is guiding for an annualized revenue run rate of $7 billion to $9 billion, with pipeline creation tracking to surpass $4 billion. The contracted backlog sits at $49 billion, anchored by a $27 billion agreement with Meta, a deal worth up to $19.4 billion with Microsoft, and a public endorsement from Jensen Huang at NVIDIA's GTC conference in 2026. The current market cap is approximately $56 billion. A company with $7 to $9 billion in annualized revenue, growing at 684%, turning cash-flow positive, sitting on $49 billion in contracted backlog, operating in a market compounding at 58% annually toward $400 billion, that company has a credible path to 20x from its current valuation if execution holds. That is the trillion dollar case, and it does not require any heroic assumptions and it requires Nebius to keep doing what it is already demonstrably doing. Milk Road Pro called this one early. Our analysts added Nebius to the portfolio when it was still flying under the radar, and we are sitting on a massive gain on that position right now. If you want to see what else we are building conviction on before the rest of the market catches up, come join us at Milk Road Pro using the link below!

Milk Road AI

28,622 次观看 • 1 个月前

Two data points dropped in the last few months that should terrify every software company that thinks its codebase is a moat. First, one engineer at Cloudflare, working with Claude via AI agents, rebuilt 94% of Next.js, one of the most widely used frontend frameworks on the internet, built over 10 years by a large engineering team in a single week. Total cost was $1,100 in API tokens. The result, called Vinext, is a drop-in replacement that builds production apps up to 4x faster and produces client bundles 57% smaller and customers are already running it in production. Second is Cursor CEO Michael Truell deployed a swarm of hundreds of GPT-5.2 agents that ran uninterrupted for an entire week and built a fully functional web browser from scratch called FastRender. 3 million lines of code, thousands of files and a custom Rust rendering engine with HTML parsing, CSS layout, text shaping, and a custom JavaScript VM. Total cost was roughly $30,000. For context, Google has spent billions of dollars and decades of engineering building Chrome. And the benchmarks say by next year, you will be able to one-shot prompt anything. The moat that software companies spent decades building, the complexity of their codebase, the years it would take a competitor to replicate it, the switching costs that moat assumed humans were the unit of production. AI does not care how long it took you to build it, it only cares how long it takes to rebuild it. And right now, the answer is one week.

Two data points dropped in the last few months that should terrify every software company that thinks its codebase is a moat. First, one engineer at Cloudflare, working with Claude via AI agents, rebuilt 94% of Next.js, one of the most widely used frontend frameworks on the internet, built over 10 years by a large engineering team in a single week. Total cost was $1,100 in API tokens. The result, called Vinext, is a drop-in replacement that builds production apps up to 4x faster and produces client bundles 57% smaller and customers are already running it in production. Second is Cursor CEO Michael Truell deployed a swarm of hundreds of GPT-5.2 agents that ran uninterrupted for an entire week and built a fully functional web browser from scratch called FastRender. 3 million lines of code, thousands of files and a custom Rust rendering engine with HTML parsing, CSS layout, text shaping, and a custom JavaScript VM. Total cost was roughly $30,000. For context, Google has spent billions of dollars and decades of engineering building Chrome. And the benchmarks say by next year, you will be able to one-shot prompt anything. The moat that software companies spent decades building, the complexity of their codebase, the years it would take a competitor to replicate it, the switching costs that moat assumed humans were the unit of production. AI does not care how long it took you to build it, it only cares how long it takes to rebuild it. And right now, the answer is one week.

Milk Road AI

16,781 次观看 • 2 个月前