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is building autonomous manufacturing systems to turn CAD designs into high-quality mechanical parts as fast as one day. They’re already saving weeks on hardware iteration cycles for multi-billion dollar companies by delivering high-quality parts, while doing $400k in monthly revenue. Congrats on the launch, Revanth Bodepudi & Prerit!

Y Combinator

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111,326 次观看 • 3 个月前 •via X (Twitter)

健康养生科学技术

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AI designs functional hardware! 🔧 Claude Opus 4.7 is leading CAD benchmarks, and AI is starting to design functional hardware autonomously. The shift happening: CAD as a tool → CAD as an autonomous system. The model didn't just sketch geometry, it generated mechanically valid designs with joints and motion constraints. It optimized for real-world functionality, not just visual correctness like earlier LLMs. This mirrors what happened in coding last year. In software, engineers moved toward requirements, architecture, and orchestration while code became the compiled outcome of AI systems. Mechanical engineering may follow the same path: from designing parts → defining intent. This changes the role of engineering teams. Instead of manually designing every component, engineers will define constraints, validate outputs, and focus on system-level architecture. Engineers spend less time on geometry and more time on optimization and integration. AI handles the mechanical validity checks that traditionally required experienced designers. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

AI designs functional hardware! 🔧 Claude Opus 4.7 is leading CAD benchmarks, and AI is starting to design functional hardware autonomously. The shift happening: CAD as a tool → CAD as an autonomous system. The model didn't just sketch geometry, it generated mechanically valid designs with joints and motion constraints. It optimized for real-world functionality, not just visual correctness like earlier LLMs. This mirrors what happened in coding last year. In software, engineers moved toward requirements, architecture, and orchestration while code became the compiled outcome of AI systems. Mechanical engineering may follow the same path: from designing parts → defining intent. This changes the role of engineering teams. Instead of manually designing every component, engineers will define constraints, validate outputs, and focus on system-level architecture. Engineers spend less time on geometry and more time on optimization and integration. AI handles the mechanical validity checks that traditionally required experienced designers. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

25,458 次观看 • 4 个月前

The 2026 Guangdong Provincial High-Quality Development Conference was held on February 24, the first work day after the Chinese New Year holiday in Guangzhou. This year's conference focuses on promoting the coordinated development of the manufacturing and service industries. Guangdong has one of the most complete manufacturing systems in the world - covering all 31 major industrial categories in China. It has powered the province's economy for decades. But today, scale alone is no longer enough. In Guangdong, services already account for nearly 60% of GDP, the potential is enormous. How does Guangdong plan to push for the coordinated development of the manufacturing and service industries, and turn that into the next competitive edge? In this episode of China Xplained, we'll search for the answers.

The 2026 Guangdong Provincial High-Quality Development Conference was held on February 24, the first work day after the Chinese New Year holiday in Guangzhou. This year's conference focuses on promoting the coordinated development of the manufacturing and service industries. Guangdong has one of the most complete manufacturing systems in the world - covering all 31 major industrial categories in China. It has powered the province's economy for decades. But today, scale alone is no longer enough. In Guangdong, services already account for nearly 60% of GDP, the potential is enormous. How does Guangdong plan to push for the coordinated development of the manufacturing and service industries, and turn that into the next competitive edge? In this episode of China Xplained, we'll search for the answers.

Hi,GBA

119,829 次观看 • 6 个月前

On 10th April, we inaugurated the Arctus HQ in Bengaluru and unveiled the AX1 - our first tech demonstrator unmanned aircraft - in the presence of Tejasvi Surya. The specs of AX1 are as follows - 20,000 feet cruising altitude, 50 KGs of payload and endurance of 10 hours! What stands out is how much of this was enabled by Bangalore. The ecosystem here allows you to go from concept to hardware at an aggressive pace - access to high-quality engineers, suppliers, early customers, and capital all within a tight loop. For a team building complex aerospace systems, that density compounds fast. Over the last few months, we’ve been heads down - designing, building, and testing - operating like an F1 team with rapid iteration cycles across structures, avionics, and flight systems. The AX1 is a direct output of that process. This facility is not just an office - it’s where we intend to push the limits of high-altitude UAVs, continuously iterating toward larger platforms and longer endurance. This is day zero for us, and there’s a lot more to build. Arctus Aerospace _india Version One Ventures gradCapital Aditya Agarwal Prateek Mehta Ankit Chowdhary Prateek Behera Boris Wertz Abhishek Sethi Angela Tran

On 10th April, we inaugurated the Arctus HQ in Bengaluru and unveiled the AX1 - our first tech demonstrator unmanned aircraft - in the presence of Tejasvi Surya. The specs of AX1 are as follows - 20,000 feet cruising altitude, 50 KGs of payload and endurance of 10 hours! What stands out is how much of this was enabled by Bangalore. The ecosystem here allows you to go from concept to hardware at an aggressive pace - access to high-quality engineers, suppliers, early customers, and capital all within a tight loop. For a team building complex aerospace systems, that density compounds fast. Over the last few months, we’ve been heads down - designing, building, and testing - operating like an F1 team with rapid iteration cycles across structures, avionics, and flight systems. The AX1 is a direct output of that process. This facility is not just an office - it’s where we intend to push the limits of high-altitude UAVs, continuously iterating toward larger platforms and longer endurance. This is day zero for us, and there’s a lot more to build. Arctus Aerospace _india Version One Ventures gradCapital Aditya Agarwal Prateek Mehta Ankit Chowdhary Prateek Behera Boris Wertz Abhishek Sethi Angela Tran

Shreepoorna S Rao

13,386 次观看 • 4 个月前

Ryan Graves: "There are high quality UFO videos which will be released by The White House in the next few weeks" 👽🛸 He told Peter Doocy: "There is a spectrum in the quality of the videos. We are currently seeing low quality videos but we are at the start of a regular release cycle that is going to go on for some period of time. From what I have heard the videos will get more high fidelity and clearer with more context as to what these things actually are" Former F-18 Pilot Ryan Graves said there are two parts to this disclosure process. "There is the long running UFO crash retrieval reverse engineering legacy program & also the data collected from around 2017 since the stigma was reduced across all military assets"

Ryan Graves: "There are high quality UFO videos which will be released by The White House in the next few weeks" 👽🛸 He told Peter Doocy: "There is a spectrum in the quality of the videos. We are currently seeing low quality videos but we are at the start of a regular release cycle that is going to go on for some period of time. From what I have heard the videos will get more high fidelity and clearer with more context as to what these things actually are" Former F-18 Pilot Ryan Graves said there are two parts to this disclosure process. "There is the long running UFO crash retrieval reverse engineering legacy program & also the data collected from around 2017 since the stigma was reduced across all military assets"

Interstellar

269,637 次观看 • 3 个月前

🎉 Meet Krea 2 from Krea, an aesthetic open-source image model ranked #1 text-to-image from an independent lab on Artificial Analysis. Day-0 support is now live in SGLang! Krea 2 ships as two models built to work together: 1️⃣ RAW: undistilled base checkpoint: diverse & malleable, made for fine-tuning, post-training & LoRA 2️⃣ Turbo: 8-step distilled checkpoint: fast, high-quality text-to-image Train LoRAs on RAW, run them on Turbo: base for training, Turbo for fast inference on your own hardware Run it now with SGLang!

🎉 Meet Krea 2 from Krea, an aesthetic open-source image model ranked #1 text-to-image from an independent lab on Artificial Analysis. Day-0 support is now live in SGLang! Krea 2 ships as two models built to work together: 1️⃣ RAW: undistilled base checkpoint: diverse & malleable, made for fine-tuning, post-training & LoRA 2️⃣ Turbo: 8-step distilled checkpoint: fast, high-quality text-to-image Train LoRAs on RAW, run them on Turbo: base for training, Turbo for fast inference on your own hardware Run it now with SGLang!

LMSYS Org

11,216 次观看 • 2 个月前

🦩 Ukrainian Defense Forces struck the Progress Rocket and Space Centre in Samara with FP-5 “Flamingo” cruise missiles — Russia’s only serial production facility for Soyuz-2 launch vehicles. The strike reportedly hit Building 106A, where critical onboard electronics, control systems and wiring, essentially the rocket’s “nervous system”, are assembled. There is no backup for Progress in Russia. Soyuz-2 launch vehicles put Russian military satellites into orbit, including reconnaissance and targeting systems, as well as satellites for Russia’s “Rassvet” satellite internet network. And this is not a quick repair job. A fire inside a high-cleanliness production area means decontamination, requalification of clean zones, process recertification and repeated quality controls. Restoring production could take months, not weeks.

🦩 Ukrainian Defense Forces struck the Progress Rocket and Space Centre in Samara with FP-5 “Flamingo” cruise missiles — Russia’s only serial production facility for Soyuz-2 launch vehicles. The strike reportedly hit Building 106A, where critical onboard electronics, control systems and wiring, essentially the rocket’s “nervous system”, are assembled. There is no backup for Progress in Russia. Soyuz-2 launch vehicles put Russian military satellites into orbit, including reconnaissance and targeting systems, as well as satellites for Russia’s “Rassvet” satellite internet network. And this is not a quick repair job. A fire inside a high-cleanliness production area means decontamination, requalification of clean zones, process recertification and repeated quality controls. Restoring production could take months, not weeks.

Fire Point

71,326 次观看 • 15 天前

A $100 Billion hardware boom is unfolding right now And a $3,000 quadruped bot dumping live suppressed rounds without flinching is the ultimate payday signal for spatial AI builders. In this range test, a custom tactical quadruped fired rapid bursts from a top-mounted rifle. The moment gun recoil hit the frame, high-torque actuators and microsecond control loops adjusted joint resistance in real time, keeping the barrel locked dead on target. Instead of building simple wrappers, smart developers are pivoting straight to physical AI. Defense labs and hardware startups are aggressively handing out $200k–$400k+ compensation packages to anyone who can master C++ control SDKs, ROS2 middleware, and real-time Nvidia Isaac Sim reinforcement learning. The mechanical hardware is already dirt cheap. The multi-billion-dollar goldmine sits entirely in the software layer that processes force-feedback telemetry and mitigates physical shock under live fire.

A $100 Billion hardware boom is unfolding right now And a $3,000 quadruped bot dumping live suppressed rounds without flinching is the ultimate payday signal for spatial AI builders. In this range test, a custom tactical quadruped fired rapid bursts from a top-mounted rifle. The moment gun recoil hit the frame, high-torque actuators and microsecond control loops adjusted joint resistance in real time, keeping the barrel locked dead on target. Instead of building simple wrappers, smart developers are pivoting straight to physical AI. Defense labs and hardware startups are aggressively handing out $200k–$400k+ compensation packages to anyone who can master C++ control SDKs, ROS2 middleware, and real-time Nvidia Isaac Sim reinforcement learning. The mechanical hardware is already dirt cheap. The multi-billion-dollar goldmine sits entirely in the software layer that processes force-feedback telemetry and mitigates physical shock under live fire.

Rich Odin

13,600 次观看 • 16 天前

Agents have reached hardware. We are launching Flow v3, the Agentic Platform for Physical Engineering. We've spent over a year building it in secret, alongside the best hardware companies and AI research labs. An agent can now do real engineering work: change a requirement, push the update into your CAD and simulation tools, and flag every test that needs to rerun. Iterations/learning cycles that took months are being reduced to days. Agents are the biggest shift in how we engineer hardware since CAD. The core innovation for the CAD era was the parametric model. The core innovation for the Agentic Era is Flow's Systems Graph. The systems graph is a living model of every requirement, design model, test, analysis and every connection between them. It gives every agent the full context of the system, so every change stays consistent across the whole design. Engineers and agents work side by side on the same system. Engineers get to focus on architecture - the decisions that matter -while thousands of agents churn through rewriting reports, rerunning analysis and simulation, and triggering tests. Reusable rockets, self-driving cars, small modular reactors, robots that make decisions, the most complex machines ever built, are defined by millions of interconnected requirements, far beyond what any human team can keep aligned on its own. Rivian, Joby, Astranis, Skydio, Radiant, and the most ambitious hardware programs already build on Flow. More on the launch in the comments. Flow Engineering

Agents have reached hardware. We are launching Flow v3, the Agentic Platform for Physical Engineering. We've spent over a year building it in secret, alongside the best hardware companies and AI research labs. An agent can now do real engineering work: change a requirement, push the update into your CAD and simulation tools, and flag every test that needs to rerun. Iterations/learning cycles that took months are being reduced to days. Agents are the biggest shift in how we engineer hardware since CAD. The core innovation for the CAD era was the parametric model. The core innovation for the Agentic Era is Flow's Systems Graph. The systems graph is a living model of every requirement, design model, test, analysis and every connection between them. It gives every agent the full context of the system, so every change stays consistent across the whole design. Engineers and agents work side by side on the same system. Engineers get to focus on architecture - the decisions that matter -while thousands of agents churn through rewriting reports, rerunning analysis and simulation, and triggering tests. Reusable rockets, self-driving cars, small modular reactors, robots that make decisions, the most complex machines ever built, are defined by millions of interconnected requirements, far beyond what any human team can keep aligned on its own. Rivian, Joby, Astranis, Skydio, Radiant, and the most ambitious hardware programs already build on Flow. More on the launch in the comments. Flow Engineering

Pari Singh

39,750 次观看 • 2 个月前

I want to hear all the competing theses for how manufacturing happens in space. My current view: The first thing we'll manufacture in space won't be spacecraft. It'll be hydrocarbons. We need fuel and food. Survival before sophistication. For a long time, most hardware will still be shipped from Earth. Manufacturing will mostly mean repair, maintenance, and replacement of spare parts by astronauts maybe robots. 1000s of Starships leaving with lots of spare parts every 18 month. So the real challenge isn't producing known parts. It's dealing with the unexpected. Every settlement, station, ship, or habitat will eventually break in ways nobody predicted. New missions will create needs nobody anticipated. Waiting months for a launch window is not a viable supply chain. That implies, space manufacturing cannot begin with giant, specialized factories. It starts with highly versatile systems capable of making many different things from limited feedstocks. Multi-purpose robots. Flexible. General-purpose manufacturing cells. In other words, the opposite of most factories today. My bet is that space manufacturing evolves as a network of distributed robotic job shops and microfactories, not monolithic production plants. The manufacturing systems that win early because they can repair the unexpected will become the industrial legacy of space. When demand eventually grows large enough for mass production, those flexible systems will already be everywhere so that is the paradigm that will scale to large volumes. What's the strongest argument against this?

I want to hear all the competing theses for how manufacturing happens in space. My current view: The first thing we'll manufacture in space won't be spacecraft. It'll be hydrocarbons. We need fuel and food. Survival before sophistication. For a long time, most hardware will still be shipped from Earth. Manufacturing will mostly mean repair, maintenance, and replacement of spare parts by astronauts maybe robots. 1000s of Starships leaving with lots of spare parts every 18 month. So the real challenge isn't producing known parts. It's dealing with the unexpected. Every settlement, station, ship, or habitat will eventually break in ways nobody predicted. New missions will create needs nobody anticipated. Waiting months for a launch window is not a viable supply chain. That implies, space manufacturing cannot begin with giant, specialized factories. It starts with highly versatile systems capable of making many different things from limited feedstocks. Multi-purpose robots. Flexible. General-purpose manufacturing cells. In other words, the opposite of most factories today. My bet is that space manufacturing evolves as a network of distributed robotic job shops and microfactories, not monolithic production plants. The manufacturing systems that win early because they can repair the unexpected will become the industrial legacy of space. When demand eventually grows large enough for mass production, those flexible systems will already be everywhere so that is the paradigm that will scale to large volumes. What's the strongest argument against this?

Edward Mehr

16,926 次观看 • 2 个月前

Hohn’s strategy essentially redefines quality as extreme resilience against substitution and competition over a multi-decade timeline. Hohn targets super-companies where physical, non-replicable assets create monopolistic barriers to entry, rendering executive talent largely irrelevant to the underlying cash flows. He deliberately avoids high-growth sectors vulnerable to disruption, viewing terminal value as the greatest source of alpha missed by short-term analysts. For instance, in infrastructure, he targets assets like cell towers, rail lines, and literal toll roads where tenancy ratios allow for near-100% margin expansion on zero-cost additions, and cash flow yields are contractually linked to inflation. In aerospace, his conviction is absolute. TCI's largest holding is $GE Aerospace. Hohn categorizes this as an unbreakable moat because the complexity of building aircraft engines has prevented any new market entrants in over 50 years. The true economic value, however, is not the engine itself, but the captive aftermarket spare parts and servicing ecosystem. Once an airline adopts an engine, the switching costs are effectively insurmountable, guaranteeing decades of highly predictable, high-margin revenue. Hohn’s view on moats is dynamic. He believes even the strongest moats can erode. In a definitive move in early 2026, TCI slashed a large portion of its $8B stake in $MSFT, which is a position held for nearly a decade. Hohn explicitly cited that the rapid advancement of Generative AI posed an existential risk to Microsoft's core Office and Azure moats, proving that he will mercilessly abandon a historically 'high quality' asset the moment technological disruption threatens its terminal value.

Hohn’s strategy essentially redefines quality as extreme resilience against substitution and competition over a multi-decade timeline. Hohn targets super-companies where physical, non-replicable assets create monopolistic barriers to entry, rendering executive talent largely irrelevant to the underlying cash flows. He deliberately avoids high-growth sectors vulnerable to disruption, viewing terminal value as the greatest source of alpha missed by short-term analysts. For instance, in infrastructure, he targets assets like cell towers, rail lines, and literal toll roads where tenancy ratios allow for near-100% margin expansion on zero-cost additions, and cash flow yields are contractually linked to inflation. In aerospace, his conviction is absolute. TCI's largest holding is $GE Aerospace. Hohn categorizes this as an unbreakable moat because the complexity of building aircraft engines has prevented any new market entrants in over 50 years. The true economic value, however, is not the engine itself, but the captive aftermarket spare parts and servicing ecosystem. Once an airline adopts an engine, the switching costs are effectively insurmountable, guaranteeing decades of highly predictable, high-margin revenue. Hohn’s view on moats is dynamic. He believes even the strongest moats can erode. In a definitive move in early 2026, TCI slashed a large portion of its $8B stake in $MSFT, which is a position held for nearly a decade. Hohn explicitly cited that the rapid advancement of Generative AI posed an existential risk to Microsoft's core Office and Azure moats, proving that he will mercilessly abandon a historically 'high quality' asset the moment technological disruption threatens its terminal value.

CapexAndChill

27,269 次观看 • 3 个月前

We are pleased to inform the public that asphalt laying is actively ongoing along the Alagbole–Akute Road as rehabilitation works progress steadily on the corridor. Contractors on site have already completed the initial stages, including mechanical sweeping of the surface and the application of colasé to prepare and stabilise the base layer. With the groundwork done, asphalt overlaying is now moving smoothly across the treated sections. We reiterate our commitment to delivering durable and high-quality road infrastructure across the state, noting that the Alagbole–Akute axis remains a vital link for daily commuters, businesses, and communities in the area. #BuildingOurFutureTogether #ISEYA #DapoAbiodun #OgunState #InfrastructureDevelopment

We are pleased to inform the public that asphalt laying is actively ongoing along the Alagbole–Akute Road as rehabilitation works progress steadily on the corridor. Contractors on site have already completed the initial stages, including mechanical sweeping of the surface and the application of colasé to prepare and stabilise the base layer. With the groundwork done, asphalt overlaying is now moving smoothly across the treated sections. We reiterate our commitment to delivering durable and high-quality road infrastructure across the state, noting that the Alagbole–Akute axis remains a vital link for daily commuters, businesses, and communities in the area. #BuildingOurFutureTogether #ISEYA #DapoAbiodun #OgunState #InfrastructureDevelopment

Prince Dr. Dapo Abiodun, CON

84,446 次观看 • 9 个月前

Banks Smash Record Trading Revenues as Global Volatility Ignites Q1 2026 Bonanza Wall Street’s biggest banks delivered a trading revenue explosion in the first quarter of 2026, powered by intense market volatility that sent client activity through the roof. JPMorgan Chase $JPM led the pack with a record $11.6 billion in markets revenue, up 20% year-over-year. Fixed-income, currencies and commodities (FICC) surged 21% to $7.1 billion, while equities trading climbed 17% to $4.5 billion. The bank’s overall profit hit $16.5 billion, or $5.94 per share, crushing estimates and marking its second-best quarter ever. Not to be outdone, Goldman Sachs $GS posted record equities trading revenue of $5.33 billion, up 27%, as hedge-fund prime brokerage and derivatives desks lit up amid wild swings. The firm’s markets business contributed to a 14% jump in total revenue to $17.23 billion and a 19% rise in profit to $5.63 billion. Citigroup $C wasn’t far behind. Its markets revenue soared 19% to $7.2 billion its highest quarterly haul in over a decade. FICC revenue climbed 13% to $5.2 billion on strong commodities, credit and currency flows, while equities trading exploded 39% to a record $2.1 billion. Bank of America $BAC saw sales and trading revenue rise 13% to $6.4 billion, with equities trading jumping 30% to $2.83 billion on heightened client hedging and positioning. Morgan Stanley capped the blowout with its own record quarter: total revenue hit $20.58 billion, up 16%, driven by a record $5.15 billion in equities trading, up 25%. Analysts had called for the largest banks to deliver around $18 billion in stock-trading revenue alone for the quarter. The numbers show Wall Street is on pace to smash that target, with combined trading revenues across the majors exceeding $40 billion. The driver was unmistakable: extreme volatility from geopolitical tensions in the Middle East, energy-price swings and anxious investor flows. Traders racked up gains facilitating hedges in commodities and currencies while capitalizing on rapid moves across rates, credit and equities. Jamie Dimon himself highlighted the “increasingly complex set of global economic risks” even as his bank’s trading desks delivered the goods. Surging client activity in commodities, credit, emerging markets and energy futures turned uncertainty into revenue for the desks. Fixed-income units thrived on credit and currency flows; equities desks saw strong prime brokerage and derivatives demand. For the first time in years, every major player reported double-digit gains in sales and trading. The numbers confirm, the big banks thrive in high volatility environments served on a gold platter by President Trump. Q1 2026 will go down as one of the strongest trading quarters on record, setting a high bar for the rest of the year as volatility shows no signs of fading.

Banks Smash Record Trading Revenues as Global Volatility Ignites Q1 2026 Bonanza Wall Street’s biggest banks delivered a trading revenue explosion in the first quarter of 2026, powered by intense market volatility that sent client activity through the roof. JPMorgan Chase $JPM led the pack with a record $11.6 billion in markets revenue, up 20% year-over-year. Fixed-income, currencies and commodities (FICC) surged 21% to $7.1 billion, while equities trading climbed 17% to $4.5 billion. The bank’s overall profit hit $16.5 billion, or $5.94 per share, crushing estimates and marking its second-best quarter ever. Not to be outdone, Goldman Sachs $GS posted record equities trading revenue of $5.33 billion, up 27%, as hedge-fund prime brokerage and derivatives desks lit up amid wild swings. The firm’s markets business contributed to a 14% jump in total revenue to $17.23 billion and a 19% rise in profit to $5.63 billion. Citigroup $C wasn’t far behind. Its markets revenue soared 19% to $7.2 billion its highest quarterly haul in over a decade. FICC revenue climbed 13% to $5.2 billion on strong commodities, credit and currency flows, while equities trading exploded 39% to a record $2.1 billion. Bank of America $BAC saw sales and trading revenue rise 13% to $6.4 billion, with equities trading jumping 30% to $2.83 billion on heightened client hedging and positioning. Morgan Stanley capped the blowout with its own record quarter: total revenue hit $20.58 billion, up 16%, driven by a record $5.15 billion in equities trading, up 25%. Analysts had called for the largest banks to deliver around $18 billion in stock-trading revenue alone for the quarter. The numbers show Wall Street is on pace to smash that target, with combined trading revenues across the majors exceeding $40 billion. The driver was unmistakable: extreme volatility from geopolitical tensions in the Middle East, energy-price swings and anxious investor flows. Traders racked up gains facilitating hedges in commodities and currencies while capitalizing on rapid moves across rates, credit and equities. Jamie Dimon himself highlighted the “increasingly complex set of global economic risks” even as his bank’s trading desks delivered the goods. Surging client activity in commodities, credit, emerging markets and energy futures turned uncertainty into revenue for the desks. Fixed-income units thrived on credit and currency flows; equities desks saw strong prime brokerage and derivatives demand. For the first time in years, every major player reported double-digit gains in sales and trading. The numbers confirm, the big banks thrive in high volatility environments served on a gold platter by President Trump. Q1 2026 will go down as one of the strongest trading quarters on record, setting a high bar for the rest of the year as volatility shows no signs of fading.

Financelot

18,129 次观看 • 4 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

159,345 次观看 • 3 个月前

Shane Wighton, from the YouTube channel Stuff Made Here, used 3D-printed tooling to form a sheet metal component as part of a concept validation process. Metal manufacturing is essential for all areas of the economy. Because of their strength, stiffness, and long-term durability, metal components are used in applications from appliances to construction parts and car body panels. Traditional metal manufacturing techniques include forming, casting, molding, joining, and machining. Sheet metal forming involves various processes where force is applied to a piece of sheet metal to plastically deform the material into the desired shape, modifying its geometry rather than removing any material. Sheet metals can be bent or stretched into a variety of complex shapes, permitting the creation of complex structures with great strength and a minimum amount of material. Sheet metal forming is the most cost-effective forming procedure today for manufacturing parts in large quantities. It can be highly automated in factories or, at the other end of the spectrum, manually operated in metal workshops for small series parts. It is a versatile, consistent, and high-quality procedure to create accurate metal parts with limited material waste. From metal cans to protective housing for hardware, parts created by sheet metal forming are found everywhere in our daily lives. In this article, learn the basics of sheet metals, the various sheet metal forming processes, and how to reduce the cost of sheet metal forming with rapid tooling and 3D printed dies. For a detailed overview and the step-by-step method, watch our webinar or download our white paper: Research conducted by Shane Wighton. Check out the fantastic 15-minute video on his YouTube channel 'Stuff Made Here'! its top-notch engineering content.:

Shane Wighton, from the YouTube channel Stuff Made Here, used 3D-printed tooling to form a sheet metal component as part of a concept validation process. Metal manufacturing is essential for all areas of the economy. Because of their strength, stiffness, and long-term durability, metal components are used in applications from appliances to construction parts and car body panels. Traditional metal manufacturing techniques include forming, casting, molding, joining, and machining. Sheet metal forming involves various processes where force is applied to a piece of sheet metal to plastically deform the material into the desired shape, modifying its geometry rather than removing any material. Sheet metals can be bent or stretched into a variety of complex shapes, permitting the creation of complex structures with great strength and a minimum amount of material. Sheet metal forming is the most cost-effective forming procedure today for manufacturing parts in large quantities. It can be highly automated in factories or, at the other end of the spectrum, manually operated in metal workshops for small series parts. It is a versatile, consistent, and high-quality procedure to create accurate metal parts with limited material waste. From metal cans to protective housing for hardware, parts created by sheet metal forming are found everywhere in our daily lives. In this article, learn the basics of sheet metals, the various sheet metal forming processes, and how to reduce the cost of sheet metal forming with rapid tooling and 3D printed dies. For a detailed overview and the step-by-step method, watch our webinar or download our white paper: Research conducted by Shane Wighton. Check out the fantastic 15-minute video on his YouTube channel 'Stuff Made Here'! its top-notch engineering content.:

Formlabs

39,948 次观看 • 1 年前

The conventional wisdom is that American manufacturing cannot compete on cost as our labor is too expensive. A factory worker in Ohio will never be as cheap as one in Shenzhen. Bryon Hargis (Bryon Hargis) thinks this misses the point entirely. "In aerospace, the thing that costs money is everybody's time," he said. Cut the time, and the cost follows. Not by paying workers less, but by designing systems that need less labor to build: fewer steps, higher yield, parts that can only go together one correct way. The problem is that America has spent decades doing the opposite. Its development process is so labor-intensive that it is approaching the limit of what it can afford to build at all.

The conventional wisdom is that American manufacturing cannot compete on cost as our labor is too expensive. A factory worker in Ohio will never be as cheap as one in Shenzhen. Bryon Hargis (Bryon Hargis) thinks this misses the point entirely. "In aerospace, the thing that costs money is everybody's time," he said. Cut the time, and the cost follows. Not by paying workers less, but by designing systems that need less labor to build: fewer steps, higher yield, parts that can only go together one correct way. The problem is that America has spent decades doing the opposite. Its development process is so labor-intensive that it is approaching the limit of what it can afford to build at all.

Mario Gabriele

10,532 次观看 • 2 个月前

A futuristic Monday morning turns into a high-speed race against the clock. Comparison of Seedance 2.0 and Seedance 2.5 on CapCut Set in 2036, a young woman wakes up late and discovers that her everyday high heels have a hidden upgrade. As she races through her apartment, down the building corridors, and into the bustling city, her elegant shoes transform into high-tech roller shoes powered by glowing blue thrusters. What starts as a desperate commute quickly becomes a cinematic chase through a futuristic city filled with skyscrapers, pedestrians, and unexpected obstacles. From mechanical shoe transformations to rocket-powered acceleration, every moment blends fashion, technology, and comedy into one fast-paced visual experience. She makes it to the office just in time. MONDAY, 2036 — Technology evolved. Mondays didn’t.

A futuristic Monday morning turns into a high-speed race against the clock. Comparison of Seedance 2.0 and Seedance 2.5 on CapCut Set in 2036, a young woman wakes up late and discovers that her everyday high heels have a hidden upgrade. As she races through her apartment, down the building corridors, and into the bustling city, her elegant shoes transform into high-tech roller shoes powered by glowing blue thrusters. What starts as a desperate commute quickly becomes a cinematic chase through a futuristic city filled with skyscrapers, pedestrians, and unexpected obstacles. From mechanical shoe transformations to rocket-powered acceleration, every moment blends fashion, technology, and comedy into one fast-paced visual experience. She makes it to the office just in time. MONDAY, 2036 — Technology evolved. Mondays didn’t.

Aaliya

29,578 次观看 • 20 天前

Here’s why $RKLB just spent ~$8B acquiring $IRDM. Rocket Lab wants to own the network, spectrum and recurring revenue layer once satellites are in orbit which is why this deal is really about vertical integration as Neutron comes online. Once Rocket Lab can launch Iridium satellites on Neutron then it internalizes a cost that used to flow to third-party launch providers making the deal way more accretive over time as Neutron comes online. What I like is that Iridium also brings something Rocket Lab stack has lacked which is recurring, high-margin service revenue tied to global connectivity, direct-to-device and government communications. The space economy is splitting into companies that can launch and refresh their own networks and companies that have to rent access to orbit. $SPCX already proved which side wins because if you own both launch and the network then you control the cost structure, refresh cycle and margin stack in a way third-party launch customers cannot match. Launch gets you to orbit but connectivity is what you monetize once you're there and the companies that own both the launch layer and the network become the platforms of the space economy.

Here’s why $RKLB just spent ~$8B acquiring $IRDM. Rocket Lab wants to own the network, spectrum and recurring revenue layer once satellites are in orbit which is why this deal is really about vertical integration as Neutron comes online. Once Rocket Lab can launch Iridium satellites on Neutron then it internalizes a cost that used to flow to third-party launch providers making the deal way more accretive over time as Neutron comes online. What I like is that Iridium also brings something Rocket Lab stack has lacked which is recurring, high-margin service revenue tied to global connectivity, direct-to-device and government communications. The space economy is splitting into companies that can launch and refresh their own networks and companies that have to rent access to orbit. $SPCX already proved which side wins because if you own both launch and the network then you control the cost structure, refresh cycle and margin stack in a way third-party launch customers cannot match. Launch gets you to orbit but connectivity is what you monetize once you're there and the companies that own both the launch layer and the network become the platforms of the space economy.

Shay Boloor

173,424 次观看 • 2 个月前