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NVIDIA Blackwell changed the data center infrastructure permanently. 120kW per rack. Mandatory liquid cooling. $500K to $2M per MW in CapEx. Here is what that means for AI compute access and why decentralized networks are the answer.

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Aethir

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11,764 次观看 • 3 个月前 •via X (Twitter)

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Water usage has been a hot topic in the AI data center world, but the numbers may surprise you. According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling. By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero. Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets. Learn more below ⬇️
0:10

Water usage has been a hot topic in the AI data center world, but the numbers may surprise you. According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling. By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero. Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets. Learn more below ⬇️

NVIDIA

33,844,545 次观看 • 2 个月前

📢 AITECH Data Center is Now Live! Solidus Ai Tech’s HPC Data Center is now live — the first ever built by a Web3 company, setting a new benchmark for decentralized AI infrastructure. 8000 sqft | 20MW capacity | 624 TFLOPS compute | RADOX cooling | <1ms latency | ISO 27001 compliant Next up is the launch of the Compute Marketplace, unlocking access to our available compute — all powered by the $AITECH token. A massive leap forward. 🔗 Learn more:
0:17

📢 AITECH Data Center is Now Live! Solidus Ai Tech’s HPC Data Center is now live — the first ever built by a Web3 company, setting a new benchmark for decentralized AI infrastructure. 8000 sqft | 20MW capacity | 624 TFLOPS compute | RADOX cooling | <1ms latency | ISO 27001 compliant Next up is the launch of the Compute Marketplace, unlocking access to our available compute — all powered by the $AITECH token. A massive leap forward. 🔗 Learn more:

AITECH CLOUD NETWORK

170,573 次观看 • 1 年前

Strategic positioning inside the most rapidly expanding markets As Bitcoin mining, AI, and data centers scale, energy efficiency and cooling become the limiting factors. PinLink and Crypto Miners are together building proprietary custom hydro-cooling infrastructure. The first prototypes are almost shipped. By operating this layer, PinLink captures value where demand is structurally guaranteed. These systems will also be tokenized through PinLink, enabling on-chain access to real infrastructure through expanded distribution channels. Tokenized and physical access. The link between decentralized physical infra networks. Energy, cooling, and compute converge here. $PIN —> LINK
0:18

Strategic positioning inside the most rapidly expanding markets As Bitcoin mining, AI, and data centers scale, energy efficiency and cooling become the limiting factors. PinLink and Crypto Miners are together building proprietary custom hydro-cooling infrastructure. The first prototypes are almost shipped. By operating this layer, PinLink captures value where demand is structurally guaranteed. These systems will also be tokenized through PinLink, enabling on-chain access to real infrastructure through expanded distribution channels. Tokenized and physical access. The link between decentralized physical infra networks. Energy, cooling, and compute converge here. $PIN —> LINK

PinLink

18,963 次观看 • 8 个月前

BREAKING 🚨 xAI reportedly to spend $18B to acquire 300K more NVIDIA chips for COLOSSUS 2, world's 1st Gigawatt AI Supercluster - xAI set to be valued at $200 billion soon - 200MW implemented in six months what took 15 months for Oracle, Crusoe and OpenAI. Let that sink in. - 500K chips now, and will eventually have 1M chips as per Elon The data center looks amazing. I am even more excited for Grok 5.
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BREAKING 🚨 xAI reportedly to spend $18B to acquire 300K more NVIDIA chips for COLOSSUS 2, world's 1st Gigawatt AI Supercluster - xAI set to be valued at $200 billion soon - 200MW implemented in six months what took 15 months for Oracle, Crusoe and OpenAI. Let that sink in. - 500K chips now, and will eventually have 1M chips as per Elon The data center looks amazing. I am even more excited for Grok 5.

Prashant

913,379 次观看 • 11 个月前

Satya Nadella: Microsoft’s latest Wisconsin AI data center keeps yearly water consumption no higher than that of 1 local restaurant. "The cooling loop is filled once and the data centre can operate effectively with zero water consumption. Daily water usage across a year is roughly equivalent to what a single restaurant would use" The mechanism is mainly about replacing evaporative cooling with closed-loop direct-to-chip liquid cooling, so water moves like coolant inside a sealed machine rather than being boiled off into the air. Hot GB200-class AI racks produce too much heat for normal air cooling, so cold liquid is pushed through pipes into the servers and across metal cold plates touching the hottest chips. The liquid enters the rack cool, absorbs heat from the chips through cold plates, then exits the rack at a higher temperature and carries that heat through pipes to a huge cooling system outside the compute floor. Microsoft says Fairwater sends that hot water to cooling “fins” beside the datacenter, where 172 20-foot fans blow air across the fins and dump the heat into the outside air. The important detail is that the air cools the water through metal surfaces, so the water does not need to evaporate the way many older datacenters use cooling towers. The cooled liquid then returns to the servers, repeats the loop, and keeps absorbing heat from the chips. In older data centers, heat is often removed partly through cooling towers. Hot water meets moving air, some water evaporates, and that phase change carries heat away. Effective, but it consumes fresh water continuously. But Firwater is a closed loop because the same coolant keeps circulating through sealed pipes: it absorbs heat from the chips, releases that heat through radiator-like fins, then flows back to the chips again. For Wisconsin Fairwater, Microsoft says more than 90% of the facility uses closed-loop liquid cooling, while the remaining portion uses outside air and switches to water only on the hottest days. ---- From "Microsoft" YouTube channel, (link in comment)
0:19

Satya Nadella: Microsoft’s latest Wisconsin AI data center keeps yearly water consumption no higher than that of 1 local restaurant. "The cooling loop is filled once and the data centre can operate effectively with zero water consumption. Daily water usage across a year is roughly equivalent to what a single restaurant would use" The mechanism is mainly about replacing evaporative cooling with closed-loop direct-to-chip liquid cooling, so water moves like coolant inside a sealed machine rather than being boiled off into the air. Hot GB200-class AI racks produce too much heat for normal air cooling, so cold liquid is pushed through pipes into the servers and across metal cold plates touching the hottest chips. The liquid enters the rack cool, absorbs heat from the chips through cold plates, then exits the rack at a higher temperature and carries that heat through pipes to a huge cooling system outside the compute floor. Microsoft says Fairwater sends that hot water to cooling “fins” beside the datacenter, where 172 20-foot fans blow air across the fins and dump the heat into the outside air. The important detail is that the air cools the water through metal surfaces, so the water does not need to evaporate the way many older datacenters use cooling towers. The cooled liquid then returns to the servers, repeats the loop, and keeps absorbing heat from the chips. In older data centers, heat is often removed partly through cooling towers. Hot water meets moving air, some water evaporates, and that phase change carries heat away. Effective, but it consumes fresh water continuously. But Firwater is a closed loop because the same coolant keeps circulating through sealed pipes: it absorbs heat from the chips, releases that heat through radiator-like fins, then flows back to the chips again. For Wisconsin Fairwater, Microsoft says more than 90% of the facility uses closed-loop liquid cooling, while the remaining portion uses outside air and switches to water only on the hottest days. ---- From "Microsoft" YouTube channel, (link in comment)

Rohan Paul

83,644 次观看 • 8 天前

China just took AI infrastructure underwater. The country has reportedly launched a wind-powered underwater data center near Shanghai, designed to cool AI servers using seawater instead of traditional cooling systems 🌊🤖 Around 2,000 servers are said to be sealed inside submarine-grade modules, helping reduce land use, water consumption, and cooling energy. The project is powered by offshore wind and built for AI workloads, big data, and large-scale computing. Why it matters? AI is creating massive demand for electricity, cooling, and infrastructure. If underwater data centers prove reliable, they could become a new way to scale AI while using less energy. But the challenge is huge: corrosion, maintenance, sea conditions, and long-term reliability still need to be proven.
0:15

China just took AI infrastructure underwater. The country has reportedly launched a wind-powered underwater data center near Shanghai, designed to cool AI servers using seawater instead of traditional cooling systems 🌊🤖 Around 2,000 servers are said to be sealed inside submarine-grade modules, helping reduce land use, water consumption, and cooling energy. The project is powered by offshore wind and built for AI workloads, big data, and large-scale computing. Why it matters? AI is creating massive demand for electricity, cooling, and infrastructure. If underwater data centers prove reliable, they could become a new way to scale AI while using less energy. But the challenge is huge: corrosion, maintenance, sea conditions, and long-term reliability still need to be proven.

Neha Singhal Trader

173,813 次观看 • 2 个月前

📢 NEW AI ADOPTION ALERT 📢 We’re excited to welcome @RingfenceAI to the Vanar ecosystem! 🚀 Ringfence is a fully agentic protocol redefining how data powers the AI economy. Leveraging Data Agents, Ringfence creates a decentralized infrastructure that ensures fairer data ownership, monetization and accessibility for the next generation of AI systems. Welcome to the future of decentralized data ownership! 🌌
0:18

📢 NEW AI ADOPTION ALERT 📢 We’re excited to welcome @RingfenceAI to the Vanar ecosystem! 🚀 Ringfence is a fully agentic protocol redefining how data powers the AI economy. Leveraging Data Agents, Ringfence creates a decentralized infrastructure that ensures fairer data ownership, monetization and accessibility for the next generation of AI systems. Welcome to the future of decentralized data ownership! 🌌

Vanar

33,151 次观看 • 1 年前

📈 Q2 is wrapping up — and Solidus Ai Tech is just getting started! We're entering a critical stretch with major rollouts on the horizon that will shape the next phase of our AI + Web3 vision. Here's what we have in store for the upcoming weeks: 🔹 Bridge to Solana 🔹 Data Center Phase 1 🔹 NVIDIA Servers Live 🔹 Exchange Listing 🔹 Compute Marketplace Live Infrastructure. Adoption. Momentum. If you're watching closely, now’s the time!
0:11

📈 Q2 is wrapping up — and Solidus Ai Tech is just getting started! We're entering a critical stretch with major rollouts on the horizon that will shape the next phase of our AI + Web3 vision. Here's what we have in store for the upcoming weeks: 🔹 Bridge to Solana 🔹 Data Center Phase 1 🔹 NVIDIA Servers Live 🔹 Exchange Listing 🔹 Compute Marketplace Live Infrastructure. Adoption. Momentum. If you're watching closely, now’s the time!

AITECH CLOUD NETWORK

52,923 次观看 • 1 年前

Behind every OptimAI Node is a mission far greater than rewards: 🔸To build a decentralized Reinforcement Data Network 🔸To unlock Agentic AI for everyone—not just a privileged few 👉OptimAI Edge Node: Our architecture is now in motion: 🔸OptimAI DePIN to power decentralized infrastructure 🔸OptimAI DeHIN to amplify collective intelligence 🔸Reinforcement Data Layer to train agents smarter, fairer 🔸Compute Layer to enable real-time AI at the edge 🔸OptimAI Chain to govern everything, transparently and efficiently OptimAI Agent Studio, Agent OS, Data Engine, Compute Engine: all part of what we’re building next. This is a network built by people, for people. And you’re not just early, you’re essential. Let’s keep mining, contributing, earning rewards in return, and rewriting the future of Decentralized AI. The future is Agentic. The fuel is your data. The power is decentralized. One Node. One Data. One Agent at a Time. #BUIDL with us!
0:12

Behind every OptimAI Node is a mission far greater than rewards: 🔸To build a decentralized Reinforcement Data Network 🔸To unlock Agentic AI for everyone—not just a privileged few 👉OptimAI Edge Node: Our architecture is now in motion: 🔸OptimAI DePIN to power decentralized infrastructure 🔸OptimAI DeHIN to amplify collective intelligence 🔸Reinforcement Data Layer to train agents smarter, fairer 🔸Compute Layer to enable real-time AI at the edge 🔸OptimAI Chain to govern everything, transparently and efficiently OptimAI Agent Studio, Agent OS, Data Engine, Compute Engine: all part of what we’re building next. This is a network built by people, for people. And you’re not just early, you’re essential. Let’s keep mining, contributing, earning rewards in return, and rewriting the future of Decentralized AI. The future is Agentic. The fuel is your data. The power is decentralized. One Node. One Data. One Agent at a Time. #BUIDL with us!

OptimAI Network

60,353 次观看 • 1 年前

Atoma Network x Linera: Advancing Decentralized AI 🚀 Super proud to announce that Atoma and Linera ⛓️ are partnering to bring scalable, private, and verifiable AI compute to Linera’s microchain ecosystem. Now, decentralized applications can access decentralized AI compute with full privacy—no reliance on centralized AI providers. You can join Jorge António and Mathieu Baudet next week to hear them discuss the partnership - Now, let's dive into this thread to see what this partnership is all about 👇
0:10

Atoma Network x Linera: Advancing Decentralized AI 🚀 Super proud to announce that Atoma and Linera ⛓️ are partnering to bring scalable, private, and verifiable AI compute to Linera’s microchain ecosystem. Now, decentralized applications can access decentralized AI compute with full privacy—no reliance on centralized AI providers. You can join Jorge António and Mathieu Baudet next week to hear them discuss the partnership - Now, let's dive into this thread to see what this partnership is all about 👇

Atoma

268,929 次观看 • 1 年前

Today, Nesa is excited to announce it is partnering with io.net to bring their decentralized fleet of GPUs to Nesa. Nesa and are natural complements to one another. Nesa’s private, distributed AI inference executed on ocean of decentralized compute means greater accessibility for the network. Together, we are one step closer to decentralizing AI for all.
0:16

Today, Nesa is excited to announce it is partnering with io.net to bring their decentralized fleet of GPUs to Nesa. Nesa and are natural complements to one another. Nesa’s private, distributed AI inference executed on ocean of decentralized compute means greater accessibility for the network. Together, we are one step closer to decentralizing AI for all.

Nesa

257,904 次观看 • 2 年前

🖥️🇦🇲Armenia to Launch High-Tech AI Data Center in Gagarin Village Investor: Eleveight AI ($60 million in private investment). Hardware: Equipped with 512 of the latest #NVIDIA B300 Blackwell GPUs. #Armenia is among the first countries globally to deploy this technology. Power: 1.2 MW capacity (scalable to 2.0 MW) powered by renewable energy sources. Timeline: Full operational launch expected by March 2026. Key Impact: Armenia is transitioning from an "exporter of talent" to a regional #AI infrastructure hub. This facility allows local startups, businesses, and scientific groups to train complex AI models domestically using world-class resources, eliminating the need for foreign relocation or reliance on external cloud providers. #Gagarin #SouthCaucasus #MiddleEast #Technology #IT
0:16

🖥️🇦🇲Armenia to Launch High-Tech AI Data Center in Gagarin Village Investor: Eleveight AI ($60 million in private investment). Hardware: Equipped with 512 of the latest #NVIDIA B300 Blackwell GPUs. #Armenia is among the first countries globally to deploy this technology. Power: 1.2 MW capacity (scalable to 2.0 MW) powered by renewable energy sources. Timeline: Full operational launch expected by March 2026. Key Impact: Armenia is transitioning from an "exporter of talent" to a regional #AI infrastructure hub. This facility allows local startups, businesses, and scientific groups to train complex AI models domestically using world-class resources, eliminating the need for foreign relocation or reliance on external cloud providers. #Gagarin #SouthCaucasus #MiddleEast #Technology #IT

Arthur Maghakian

59,896 次观看 • 7 个月前

🔐 𝗣𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗡𝗲𝘅𝘁 𝗪𝗮𝘃𝗲 𝗼𝗳 𝗔𝗜 We're proud to partner with Stempoint to secure the future of decentralized AI compute. StemPoint is building one of the most advanced distributed AI infrastructures on the planet, sharded GPU compute, open model libraries, and secure data flows across a global mesh. Now with Naoris Protocol’s Sub-Zero Layer and dPoSec consensus, every node, model, and data packet gains: • Post-quantum cryptographic protection • Real-time validation of compute and algorithms • A decentralized trust layer for sovereign AI 🚫 No more trusting black boxes. ✅ Verifiable AI infrastructure at scale.
0:14

🔐 𝗣𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗡𝗲𝘅𝘁 𝗪𝗮𝘃𝗲 𝗼𝗳 𝗔𝗜 We're proud to partner with Stempoint to secure the future of decentralized AI compute. StemPoint is building one of the most advanced distributed AI infrastructures on the planet, sharded GPU compute, open model libraries, and secure data flows across a global mesh. Now with Naoris Protocol’s Sub-Zero Layer and dPoSec consensus, every node, model, and data packet gains: • Post-quantum cryptographic protection • Real-time validation of compute and algorithms • A decentralized trust layer for sovereign AI 🚫 No more trusting black boxes. ✅ Verifiable AI infrastructure at scale.

NaoX Protocol

23,336 次观看 • 1 年前

LayerAI Compute: Decentralized GPU Power for AI 🧬 LayerAI is stepping into the physical AI infrastructure game with our latest: DePin for AI Computing. This move tackles a key AI/ML market gap: instant, on-demand compute power, available worldwide with just a few clicks. We're not just decentralizing data with AI2Earn; we're now also decentralizing the compute, making the AI ecosystem stronger and more resilient. The first iteration of this product will go live in the 2nd week of February.
0:18

LayerAI Compute: Decentralized GPU Power for AI 🧬 LayerAI is stepping into the physical AI infrastructure game with our latest: DePin for AI Computing. This move tackles a key AI/ML market gap: instant, on-demand compute power, available worldwide with just a few clicks. We're not just decentralizing data with AI2Earn; we're now also decentralizing the compute, making the AI ecosystem stronger and more resilient. The first iteration of this product will go live in the 2nd week of February.

LayerAI | AI2Earn

23,656 次观看 • 1 年前

Loading DeFAI infrastructure ▓▓▓▓▓▓▓▓▓░ io.net, a decentralized GPU compute network has expanded to power the future of DeFAI for Injective builders. The integration aims to support the growing trend of developers building AI Agents, DeFAI, and gaming initiatives in web3. io.net provides Web3 builders with tools to train, fine-tune, and deploy ML models using decentralized resources. The collaboration combines Injective's iAgent framework with io.net’s extensive GPU network, setting the stage for more accessible and innovative development across use cases that require compute resources. Key features include: ✅ Access to over 10,000 cluster-ready GPUs and CPUs, ✅ AI-driven blockchain activities using Injective's iAgent SDK, and ✅ Potential for new on-chain financial products leveraging GPU pricing and data feeds. 👀 io.net’s DePIN network deploys on-demand, decentralized GPU resources globally, designed for low latency and high-throughput processing. Benefits include reduced barriers for AI/ML projects, enhanced integration of AI with on-chain activities, and democratized access to high-performance computing resources. Together, this marks a significant milestone in decentralized AI infrastructure, addressing key challenges and paving the way for unprecedented innovation in AI development and on-chain finance.
0:11

Loading DeFAI infrastructure ▓▓▓▓▓▓▓▓▓░ io.net, a decentralized GPU compute network has expanded to power the future of DeFAI for Injective builders. The integration aims to support the growing trend of developers building AI Agents, DeFAI, and gaming initiatives in web3. io.net provides Web3 builders with tools to train, fine-tune, and deploy ML models using decentralized resources. The collaboration combines Injective's iAgent framework with io.net’s extensive GPU network, setting the stage for more accessible and innovative development across use cases that require compute resources. Key features include: ✅ Access to over 10,000 cluster-ready GPUs and CPUs, ✅ AI-driven blockchain activities using Injective's iAgent SDK, and ✅ Potential for new on-chain financial products leveraging GPU pricing and data feeds. 👀 io.net’s DePIN network deploys on-demand, decentralized GPU resources globally, designed for low latency and high-throughput processing. Benefits include reduced barriers for AI/ML projects, enhanced integration of AI with on-chain activities, and democratized access to high-performance computing resources. Together, this marks a significant milestone in decentralized AI infrastructure, addressing key challenges and paving the way for unprecedented innovation in AI development and on-chain finance.

Injective 🥷

131,743 次观看 • 1 年前

THIS GUY BUILT A MINI AI FARM OUT OF 4 NVIDIA BOXES. IT DOESN'T LOOK LIKE A DATA CENTER. IT LOOKS LIKE A STACK OF SMALL MACHINES SITTING NEXT TO A LAPTOP. BUT EACH BOX IS A DGX SPARK WITH GRACE BLACKWELL INSIDE. 4 BOXES. 512GB OF UNIFIED MEMORY. NEARLY $12,000 OF LOCAL AI COMPUTE SITTING ON ONE DESK. NO CLOUD GPU RENTAL FEES. NO HOURLY METER. NO RENTED COMPUTE EATING YOUR MARGINS. MOST PEOPLE STILL THINK LOCAL AI MEANS A SLOW LAPTOP RUNNING A TOY MODEL. MEANWHILE, PEOPLE ARE STACKING SERIOUS AI COMPUTE AT HOME. LOCAL AI IS STARTING TO LOOK LIKE THE NEW MINING FARM.
0:11

THIS GUY BUILT A MINI AI FARM OUT OF 4 NVIDIA BOXES. IT DOESN'T LOOK LIKE A DATA CENTER. IT LOOKS LIKE A STACK OF SMALL MACHINES SITTING NEXT TO A LAPTOP. BUT EACH BOX IS A DGX SPARK WITH GRACE BLACKWELL INSIDE. 4 BOXES. 512GB OF UNIFIED MEMORY. NEARLY $12,000 OF LOCAL AI COMPUTE SITTING ON ONE DESK. NO CLOUD GPU RENTAL FEES. NO HOURLY METER. NO RENTED COMPUTE EATING YOUR MARGINS. MOST PEOPLE STILL THINK LOCAL AI MEANS A SLOW LAPTOP RUNNING A TOY MODEL. MEANWHILE, PEOPLE ARE STACKING SERIOUS AI COMPUTE AT HOME. LOCAL AI IS STARTING TO LOOK LIKE THE NEW MINING FARM.

Vivek Sen

31,812 次观看 • 28 天前

Why is the market selling off today? (Save this). The semi selloff right now is being driven by a mix of macro fear, profit taking and investors questioning how quickly all of this AI spending will actually pay off, not because demand for AI infrastructure suddenly disappeared. The market is basically trading this chain reaction, the ongoing US Iran escalation pushes oil higher, higher oil keeps inflation elevated, sticky inflation keeps Treasury yields high and that increases the risk of the Fed staying hawkish or even hiking again. That is a terrible setup for semis because many of these companies are valued on the massive earnings investors expect them to generate years from now. When yields rise, those future earnings become worth less today which is why the highest multiple AI and semiconductor names usually get hit first. (I don't think there will be a hike this year). This is also why everything is moving together right now. Nvidia, Micron, Nebius, SanDisk, Broadcom and Applied Optoelectronics are all completely different businesses, but institutions are not separating memory, networking, optics, compute and cloud infrastructure at the moment. They are reducing exposure to the entire AI trade, taking profits in the names that have already run the most and moving into a more defensive position potentially ahead of the Fed. There is also growing pressure around hyperscaler capex. Microsoft, Meta, Amazon and Google are still spending enormous amounts on GPUs, data centers, networking and power but the market is starting to ask when all of that spending will actually turn into revenue and free cash flow. Investors are no longer satisfied with hearing that AI capex is growing. They want proof that the returns are arriving fast enough to justify the valuations already priced into the entire AI ecosystem. That creates a weird situation where hyperscaler capex can continue rising while semiconductor stocks still fall. The market is not asking whether AI spending is growing anymore but rather asking whether it is growing fast enough to beat the expectations already baked into these stocks. Crowded positioning is another major factor. Semis and AI infrastructure stocks have been some of the biggest winners in the market so institutions are sitting on huge profits and many funds own the exact same names. When macro risk increases, investors usually sell the most liquid winners first. That does not mean demand for memory, optics or custom chips suddenly collapsed but rather means investors are locking in gains and reducing risk. Tariffs add another layer because even when they are not directly placed on chips, they can still raise the cost of servers, electrical equipment, cooling systems, construction materials and the overall data center buildout. That makes AI infrastructure more expensive while also adding another source of inflation. Then you have Jensen Huang’s letter to the White House this morning about open weight AI models, which I think is one of the most important long term developments here. Nvidia, Meta, Microsoft, Palantir and several other companies are pushing Washington not to place broad restrictions on open weight AI. OpenAI and Anthropic were notably absent because open models are much more of a threat to their business models. OpenAI and Anthropic benefit from a world where a few closed frontier labs control the best models and companies have to pay them through subscriptions and APIs. Open weight models weaken that advantage because businesses can download a model, customize it for their own use and run it on their own infrastructure or through a neocloud. That is bad for OpenAI and Anthropic because it puts pressure on pricing, margins and the idea that they will control the intelligence layer of the economy but it is very good for the AI ecosystem as a whole over the long run. But the question is what does this mean for all the OpenAI and Anthropic commitments? so that's adding to the fear as well. But with that being said open models make AI cheaper and more accessible. Instead of AI being controlled by a few giant labs, thousands of startups, universities, governments and regular businesses can deploy models themselves. That spreads AI adoption across the entire economy and creates a much larger infrastructure opportunity and that is exactly why Jensen cares. Nvidia does not need OpenAI or Anthropic to win. Nvidia just needs more people using AI. Whether the model comes from OpenAI, Anthropic, Meta, Mistral, Kimi or some startup nobody has heard of yet, it still needs GPUs, memory, networking, data centers and electricity. So open weight AI could actually weaken the model companies while making the infrastructure layer much bigger. More open models mean more companies running inference. More inference means more GPUs. More GPUs mean more HBM, optical transceivers, switches, data centers and power. That is bullish for Nvidia Nebius, Micron, Broadcom , Marvell and Applied Optoelectronics over the long run. So my take is that the current semi selloff is being driven mostly by macro uncertainty, higher oil, rising yields, Fed fears, tariffs, crowded positioning and questions around the return on hyperscaler capex. The underlying AI infrastructure thesis has not suddenly broken. We are not broadly seeing hyperscalers cancel GPU orders, slash capex, abandon data center projects or report that AI demand has collapsed. What has changed is the valuation investors are willing to pay while the macro environment remains unstable. The market is lowering the price it is willing to pay for semiconductor growth but is not necessarily saying that growth is gone. And while Jensen’s open weight push may be bad for OpenAI and Anthropic, it could be one of the best things possible for the AI ecosystem over the long run because it creates more models, more developers, more competition and ultimately much more demand for the infrastructure underneath all of it. Nothing about the AI thesis has changed for me, so I will be going shopping and taking advantage of this sale while the market is selling everything together. I am an analyst at Milk Road Pro, and if you want to see exactly what I am buying, you can join for just $1 using the link below.
0:11

Why is the market selling off today? (Save this). The semi selloff right now is being driven by a mix of macro fear, profit taking and investors questioning how quickly all of this AI spending will actually pay off, not because demand for AI infrastructure suddenly disappeared. The market is basically trading this chain reaction, the ongoing US Iran escalation pushes oil higher, higher oil keeps inflation elevated, sticky inflation keeps Treasury yields high and that increases the risk of the Fed staying hawkish or even hiking again. That is a terrible setup for semis because many of these companies are valued on the massive earnings investors expect them to generate years from now. When yields rise, those future earnings become worth less today which is why the highest multiple AI and semiconductor names usually get hit first. (I don't think there will be a hike this year). This is also why everything is moving together right now. Nvidia, Micron, Nebius, SanDisk, Broadcom and Applied Optoelectronics are all completely different businesses, but institutions are not separating memory, networking, optics, compute and cloud infrastructure at the moment. They are reducing exposure to the entire AI trade, taking profits in the names that have already run the most and moving into a more defensive position potentially ahead of the Fed. There is also growing pressure around hyperscaler capex. Microsoft, Meta, Amazon and Google are still spending enormous amounts on GPUs, data centers, networking and power but the market is starting to ask when all of that spending will actually turn into revenue and free cash flow. Investors are no longer satisfied with hearing that AI capex is growing. They want proof that the returns are arriving fast enough to justify the valuations already priced into the entire AI ecosystem. That creates a weird situation where hyperscaler capex can continue rising while semiconductor stocks still fall. The market is not asking whether AI spending is growing anymore but rather asking whether it is growing fast enough to beat the expectations already baked into these stocks. Crowded positioning is another major factor. Semis and AI infrastructure stocks have been some of the biggest winners in the market so institutions are sitting on huge profits and many funds own the exact same names. When macro risk increases, investors usually sell the most liquid winners first. That does not mean demand for memory, optics or custom chips suddenly collapsed but rather means investors are locking in gains and reducing risk. Tariffs add another layer because even when they are not directly placed on chips, they can still raise the cost of servers, electrical equipment, cooling systems, construction materials and the overall data center buildout. That makes AI infrastructure more expensive while also adding another source of inflation. Then you have Jensen Huang’s letter to the White House this morning about open weight AI models, which I think is one of the most important long term developments here. Nvidia, Meta, Microsoft, Palantir and several other companies are pushing Washington not to place broad restrictions on open weight AI. OpenAI and Anthropic were notably absent because open models are much more of a threat to their business models. OpenAI and Anthropic benefit from a world where a few closed frontier labs control the best models and companies have to pay them through subscriptions and APIs. Open weight models weaken that advantage because businesses can download a model, customize it for their own use and run it on their own infrastructure or through a neocloud. That is bad for OpenAI and Anthropic because it puts pressure on pricing, margins and the idea that they will control the intelligence layer of the economy but it is very good for the AI ecosystem as a whole over the long run. But the question is what does this mean for all the OpenAI and Anthropic commitments? so that's adding to the fear as well. But with that being said open models make AI cheaper and more accessible. Instead of AI being controlled by a few giant labs, thousands of startups, universities, governments and regular businesses can deploy models themselves. That spreads AI adoption across the entire economy and creates a much larger infrastructure opportunity and that is exactly why Jensen cares. Nvidia does not need OpenAI or Anthropic to win. Nvidia just needs more people using AI. Whether the model comes from OpenAI, Anthropic, Meta, Mistral, Kimi or some startup nobody has heard of yet, it still needs GPUs, memory, networking, data centers and electricity. So open weight AI could actually weaken the model companies while making the infrastructure layer much bigger. More open models mean more companies running inference. More inference means more GPUs. More GPUs mean more HBM, optical transceivers, switches, data centers and power. That is bullish for Nvidia Nebius, Micron, Broadcom , Marvell and Applied Optoelectronics over the long run. So my take is that the current semi selloff is being driven mostly by macro uncertainty, higher oil, rising yields, Fed fears, tariffs, crowded positioning and questions around the return on hyperscaler capex. The underlying AI infrastructure thesis has not suddenly broken. We are not broadly seeing hyperscalers cancel GPU orders, slash capex, abandon data center projects or report that AI demand has collapsed. What has changed is the valuation investors are willing to pay while the macro environment remains unstable. The market is lowering the price it is willing to pay for semiconductor growth but is not necessarily saying that growth is gone. And while Jensen’s open weight push may be bad for OpenAI and Anthropic, it could be one of the best things possible for the AI ecosystem over the long run because it creates more models, more developers, more competition and ultimately much more demand for the infrastructure underneath all of it. Nothing about the AI thesis has changed for me, so I will be going shopping and taking advantage of this sale while the market is selling everything together. I am an analyst at Milk Road Pro, and if you want to see exactly what I am buying, you can join for just $1 using the link below.

Melvin

180,578 次观看 • 1 个月前

SpaceX is building an AI data center for orbit, then reusing the same brain box on Earth. Starmind AI1 packs NVIDIA Rubin GPUs and Vera CPUs, solar power and Starlink laser links into one orbital system. On the ground, Elon says they can remove the solar wings and radiators while keeping the core compute design. Same brain. Different address. But a major improvement in data center efficiency. SpaceX Starlink NVIDIA / Writer: Annette, Grok Imagine Designer: Janné
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SpaceX is building an AI data center for orbit, then reusing the same brain box on Earth. Starmind AI1 packs NVIDIA Rubin GPUs and Vera CPUs, solar power and Starlink laser links into one orbital system. On the ground, Elon says they can remove the solar wings and radiators while keeping the core compute design. Same brain. Different address. But a major improvement in data center efficiency. SpaceX Starlink NVIDIA / Writer: Annette, Grok Imagine Designer: Janné

Mario Nawfal

64,730 次观看 • 1 个月前