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What actually goes into a data center? Guru Chahal🇺🇸 whiteboards the entire stack - across land, power, cooling, storage, networking, compute - and shares where we're seeing the most interesting innovation + startup opportunities → Base Power: virtual power plants from residential batteries → Periodic Labs: using AI to... discover new materials - ones that run cooler, conduct better, and waste less power → Nexthop AI: network switches that are 10–15% more power efficient than what's on the market → Unconventional AI: AI chips modeled after how the human brain works, targeting 100–1,000x better power efficiency → Ricursive Intelligence: AI to design chips. Today a first chip costs $100M and takes 2–3 years. They want to build in months, at a fraction of the cost → better materials → cheaper experiments → more chip designs → more efficient chips → less power → and what happens when you package all of this into a satellite and put it in orbit 🚀 As trillions of dollars of infrastructure flow into building the "AI factory", every layer of the intelligence economy is being rebuilt at once. Who are we missing? We'd love to meet if you are building somewhere on this stack.show more

Claire Zau

6,914 subscribers

45,448 views • 1 month ago •via X (Twitter)

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17 Comments

Claire Zau1 month ago

full episode and breakdown on youtube

cogsec1 month ago

@guruchahal @basepowerco super cool

Claire Zau1 month ago

@guruchahal @basepowerco thank you 🙏

Dara Miao1 month ago

@guruchahal @basepowerco so helpful i love this claire

Claire Zau1 month ago

@guruchahal @basepowerco so glad to hear - excited that we get to yap about all of this 🤗

Michelle Sun1 month ago

@guruchahal @basepowerco fantastic. more of these whiteboard educational pieces, please!

Claire Zau1 month ago

@guruchahal @basepowerco thank you so much!! so glad they’re interesting

Dakshay Mehta1 month ago

@guruchahal @basepowerco Guru is awesome

Claire Zau1 month ago

@guruchahal @basepowerco can confirm!! so much to learn from him

Dakshay Mehta1 month ago

@guruchahal @basepowerco 💯💯

Max Song (🌎, 🚀 , 🌕 )1 month ago

@guruchahal @basepowerco Awesome content!!

Vatsalpandya3331 month ago

@guruchahal @basepowerco 🐐

Nirvana Labs1 month ago

@guruchahal @basepowerco We are a high-performance storage cloud purpose built for the most demanding, real-time, stateful workloads. Faster and cheaper than hyperscalers by at least 20-30%. We have a bunch of clients in production including Altinity, Goldsky, Bitgo, Nansen etc. Check us out!

Stanley Wei1 month ago

@guruchahal @basepowerco The data center stack is a good reminder that AI infrastructure is a systems business, not a GPU shopping list. Land, power, cooling, and networking each become product surfaces—and each can bottleneck the others.

AI Mastery Guide1 month ago

@guruchahal @basepowerco Every layer getting rebuilt at once is wild to actually see mapped out.

Anjuli Pierce1 month ago

@guruchahal @basepowerco We want to go micro and have a plan for it; can’t afford to implement personally however would love the opportunity for a live pitch!

Randy Compute1 month ago

@guruchahal @basepowerco the seventh layer is a spreadsheet insisting the other six will arrive on time

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🇺🇸 Elon confirms the “Terafab” model links xAI, SpaceX, and Tesla to scale chips, energy, and factories together, aiming for terawatt-level compute output. The idea is to control the full stack: chip design, manufacturing, power generation, and deployment, with most compute eventually supporting space-based systems. So it’s like a feedback loop, more factories build more chips, which train better AI, which then designs even better factories. Because why build a factory… when you can try to build the entire stack. Source: Elon Musk Tesla

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4,623,015 views • 29 days ago

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Ray Myers

84,029 views • 9 months ago

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China is our adversary. They are building more power than we are, and then using it to power data centers to advance both economic interests and of course military as well. We can’t let the Chinese beat us in AI. We’ve gotta build more data centers, we’ve gotta build more power. We’ve got a lot ahead of us here because they’re beating us on this. We cannot let this happen.

China is our adversary. They are building more power than we are, and then using it to power data centers to advance both economic interests and of course military as well. We can’t let the Chinese beat us in AI. We’ve gotta build more data centers, we’ve gotta build more power. We’ve got a lot ahead of us here because they’re beating us on this. We cannot let this happen.

Kevin O'Leary aka Mr. Wonderful

19,405 views • 4 months ago

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Daniel Roberts of $IREN just laid out the brutal reality of the AI infrastructure buildout. He noted we are still in the dial up era of AI. The ultimate choke point is power. It requires steel, concrete, and years of physical construction. Starting a gigawatt AI factory today means you will not see the first compute online until the 2030s. It takes 18 to 24 months just to get a utility company to confirm if a piece of land even has power access. The market is pricing in rapid software scaling, but the physical bottlenecks are severe and unavoidable. The capital moving into power generation and data center infrastructure is a multi year trend. It’s not a sprint it’s a marathon.

Patient Investor

176,637 views • 4 months ago

Elon Musk explains how data centers in Space could help the US compete with China in AI “Given that Chinese AI companies are doing as well as they are with a relatively small amount of compute, it seems that if they had a lot of compute, there’s a good chance they would be the leaders. The constraints on AI are essentially electricity and AI chips. China is very strong in digital AI, and it has far more electricity than the United States. In fact, China already has more electricity than the United States, Europe and India combined. The US government can prevent US companies from using Chinese models, but it can’t stop the rest of the world from using them. That won’t stop China from becoming the leader in AI. Digital intelligence comes down to how much AI compute, how many chips and how much electricity you have. The current constraint is electricity outside China. In China, the constraint is chips. China is also closer than most people realize to solving the lithography problem, which would enable it to make AI chips in very large volumes. Once we address the power constraint with AI data centers in space, the constraint will once again be chips outside China.”

Elon Musk explains how data centers in Space could help the US compete with China in AI “Given that Chinese AI companies are doing as well as they are with a relatively small amount of compute, it seems that if they had a lot of compute, there’s a good chance they would be the leaders. The constraints on AI are essentially electricity and AI chips. China is very strong in digital AI, and it has far more electricity than the United States. In fact, China already has more electricity than the United States, Europe and India combined. The US government can prevent US companies from using Chinese models, but it can’t stop the rest of the world from using them. That won’t stop China from becoming the leader in AI. Digital intelligence comes down to how much AI compute, how many chips and how much electricity you have. The current constraint is electricity outside China. In China, the constraint is chips. China is also closer than most people realize to solving the lithography problem, which would enable it to make AI chips in very large volumes. Once we address the power constraint with AI data centers in space, the constraint will once again be chips outside China.”

DogeDesigner

246,547 views • 2 months ago

Bitzero is a power, permit, and land company. What they've done is search the globe looking for the lowest cost of power, sustainable electric power, some nuclear power, sub six cents a kilowatt hour. You can mine bitcoin on their land or you can do Ethereum, or you can build a data center. Everybody in AI has to have power, land, permits, and water. BitZero has them. It's an infrastructure play and I find a lot less risky than figuring out who's going to win in AI. Everybody needs what BitZero has, power.

Bitzero is a power, permit, and land company. What they've done is search the globe looking for the lowest cost of power, sustainable electric power, some nuclear power, sub six cents a kilowatt hour. You can mine bitcoin on their land or you can do Ethereum, or you can build a data center. Everybody in AI has to have power, land, permits, and water. BitZero has them. It's an infrastructure play and I find a lot less risky than figuring out who's going to win in AI. Everybody needs what BitZero has, power.

Kevin O'Leary aka Mr. Wonderful

18,648 views • 10 months ago

$Elon Musk just put a number on the flaw at the center of Nvidia’s empire. Wall Street has not done the math yet. Nvidia’s Blackwell is the most sought-after silicon on Earth. Every AI lab wants it. Every sovereign nation is bidding for it. Blackwell runs every model, for every company, in every data center on the planet. That universality built the empire. It is also the fracture point. Musk: “We believe the AI5 chip will be about a third of the power of an Nvidia Blackwell for roughly comparable performance. And much less than 10% of the cost.” One-third the power. Comparable performance. Less than ten percent of the cost. Musk: “This is a chip that is very much optimized for the Tesla AI software stack. It’s not meant to be a general purpose chip.” Nvidia builds silicon that serves a million different customers. Every transistor spent on universal compatibility is a transistor not dedicated to one task. Tesla is building silicon for exactly one customer. Itself. When you strip away every function you will never call, you do not get a lesser chip. You get a weapon. Here is what the market refuses to see. Data centers drink unlimited power from the grid. Robots run on batteries. Musk: “In order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient.” You cannot put a Blackwell inside a walking machine. It would drain the battery before it crossed the room. The entire AI revolution lives inside air-conditioned buildings bolted to the electrical grid. Musk is not competing for that market. He is engineering the silicon that survives outside of it. One-third the power is not a spec sheet footnote. It is the physics threshold that severs intelligence from the wall socket. Without that number, every robot on Earth stays tethered. With it, the algorithm walks. Less than ten percent of the cost is not a pricing strategy. It is the line where a machine brain stops being a capital expenditure and becomes a commodity component. When the chip inside a humanoid costs less than the motors in its legs, you do not manufacture hundreds of robots. You manufacture millions. Wall Street is valuing the AI revolution by who dominates the data center. Musk is building the only silicon designed to leave one. Nvidia built the brain of the cloud. Musk is building the brain of the physical world. No one has priced that in yet.$

Elon Musk just put a number on the flaw at the center of Nvidia’s empire. Wall Street has not done the math yet. Nvidia’s Blackwell is the most sought-after silicon on Earth. Every AI lab wants it. Every sovereign nation is bidding for it. Blackwell runs every model, for every company, in every data center on the planet. That universality built the empire. It is also the fracture point. Musk: “We believe the AI5 chip will be about a third of the power of an Nvidia Blackwell for roughly comparable performance. And much less than 10% of the cost.” One-third the power. Comparable performance. Less than ten percent of the cost. Musk: “This is a chip that is very much optimized for the Tesla AI software stack. It’s not meant to be a general purpose chip.” Nvidia builds silicon that serves a million different customers. Every transistor spent on universal compatibility is a transistor not dedicated to one task. Tesla is building silicon for exactly one customer. Itself. When you strip away every function you will never call, you do not get a lesser chip. You get a weapon. Here is what the market refuses to see. Data centers drink unlimited power from the grid. Robots run on batteries. Musk: “In order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient.” You cannot put a Blackwell inside a walking machine. It would drain the battery before it crossed the room. The entire AI revolution lives inside air-conditioned buildings bolted to the electrical grid. Musk is not competing for that market. He is engineering the silicon that survives outside of it. One-third the power is not a spec sheet footnote. It is the physics threshold that severs intelligence from the wall socket. Without that number, every robot on Earth stays tethered. With it, the algorithm walks. Less than ten percent of the cost is not a pricing strategy. It is the line where a machine brain stops being a capital expenditure and becomes a commodity component. When the chip inside a humanoid costs less than the motors in its legs, you do not manufacture hundreds of robots. You manufacture millions. Wall Street is valuing the AI revolution by who dominates the data center. Musk is building the only silicon designed to leave one. Nvidia built the brain of the cloud. Musk is building the brain of the physical world. No one has priced that in yet.

Dustin

160,633 views • 5 months ago

AI in the network is shifting the conversation beyond GPUs. At MWC 2026, Intel's Kevork Kechichian, EVP & GM of the Data Center Group, explains why inference workloads are bringing CPUs back into focus, especially in telco environments where power, space, and efficiency matter. With platforms like Intel Xeon and Clearwater Forest, operators are seeing up to 30% performance gains and 60% better power efficiency, helping scale AI workloads without overhauling infrastructure. As networks evolve toward AI-driven operations and 6G, one principle is becoming clear: The future of AI infrastructure is about using the right compute for the right workload.

AI in the network is shifting the conversation beyond GPUs. At MWC 2026, Intel's Kevork Kechichian, EVP & GM of the Data Center Group, explains why inference workloads are bringing CPUs back into focus, especially in telco environments where power, space, and efficiency matter. With platforms like Intel Xeon and Clearwater Forest, operators are seeing up to 30% performance gains and 60% better power efficiency, helping scale AI workloads without overhauling infrastructure. As networks evolve toward AI-driven operations and 6G, one principle is becoming clear: The future of AI infrastructure is about using the right compute for the right workload.

Six Five Media

131,501 views • 6 months ago

Elon Musk in new G20 interview on the AI power crisis: "There actually is a crisis of power. If you just follow the AI topic on the 𝕏 platform, you'll get a very good sense of where things are headed. That's how I get my news; There will be a significant power shortfall next year. The consensus estimate is there will be a 15GW power shortfall in 2027 for AI chips. This is why Google and Anthropic are leasing compute from SpaceX, because we've been able to turn on AI better than anyone else so far. This is by constructing our own power plants is how we've been able to do it." Recently, SpaceX powered down 11 turbines at their Southaven datacenter facility as they make way for their new 1.2 GW power plant coming online in the near future (under the Clean Air Act permit).

Elon Musk in new G20 interview on the AI power crisis: "There actually is a crisis of power. If you just follow the AI topic on the 𝕏 platform, you'll get a very good sense of where things are headed. That's how I get my news; There will be a significant power shortfall next year. The consensus estimate is there will be a 15GW power shortfall in 2027 for AI chips. This is why Google and Anthropic are leasing compute from SpaceX, because we've been able to turn on AI better than anyone else so far. This is by constructing our own power plants is how we've been able to do it." Recently, SpaceX powered down 11 turbines at their Southaven datacenter facility as they make way for their new 1.2 GW power plant coming online in the near future (under the Clean Air Act permit).

Sawyer Merritt

133,997 views • 21 days ago

AI workload depends on: power, infrastructure and connectivity. At #NEOM, we're bringing together the conditions that make the next generation of AI compute possible: scalable energy and water capacity, digital connectivity, developed industrial land and infrastructure. Building on this, HUMAIN and DataVoltKSA are advancing the construction of the first AI data center at Oxagon, further strengthening NEOM’s position as a hub for AI infrastructure. Together, we're creating an ecosystem for AI to scale, driving investment, innovation and strategic partnerships that support Saudi Arabia's economic diversification.

AI workload depends on: power, infrastructure and connectivity. At #NEOM, we're bringing together the conditions that make the next generation of AI compute possible: scalable energy and water capacity, digital connectivity, developed industrial land and infrastructure. Building on this, HUMAIN and DataVoltKSA are advancing the construction of the first AI data center at Oxagon, further strengthening NEOM’s position as a hub for AI infrastructure. Together, we're creating an ecosystem for AI to scale, driving investment, innovation and strategic partnerships that support Saudi Arabia's economic diversification.

NEOM

28,289 views • 22 days ago