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Exciting to see Chamath and J-Cal discussing the power of Targon distributed confidential compute on The All-In Podcast “I do think this idea of distributed inference has a real place in the American ecosystem.” We appreciate the mention, and are excited to watch the continued growth of the permissionless... show more

Targon

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ELON: AI WILL HARNESS THE POWER OF THE SUN AND GALAXY FOR COMPUTE "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute and then ultimately most of the power of the galaxy, you know, sort of cloud Kardashev two, Kardashev three scale compute. So I guess once you think of artificial intelligence not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of." Source: Jon Hernandez

ELON: AI WILL HARNESS THE POWER OF THE SUN AND GALAXY FOR COMPUTE "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute and then ultimately most of the power of the galaxy, you know, sort of cloud Kardashev two, Kardashev three scale compute. So I guess once you think of artificial intelligence not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of." Source: Jon Hernandez

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Elon Musk explains Tesla’s new Megapod concept for scaling distributed AI compute: “We’re building a Megapod design that pairs Tesla AI4 computers with x86 systems in a box...essentially digital Optimus in a box Similar to how Megapack packages batteries, a Megapod would combine a large number of AI4 and x86 systems inside one deployable unit These boxes could be placed anywhere across the country or outside the country allowing us to scale AI compute using distributed electricity production There is power available all around the world, including at our Supercharger sites. We have something like 7 gigawatts of power across the Supercharger network, and that continues to grow We could place Megapods at many of these locations and use that distributed power for AI compute I think that could be quite a big deal” Instead of relying entirely on enormous centralized data centers, Tesla could deploy modular AI-compute infrastructure wherever sufficient power is already available

X Freeze

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ELON MUSK: SpaceX could have closer to 10 GW of compute next year. “We are building and deploying compute, I think, faster; our rate of growth certainly is faster than anyone else and our efficiency of compute deployment, I think, is also the highest. So we expect to end this year with over two gigawatts of compute. And probably our cumulative compute online by the end of next year will be several times higher. So it may, let’s say, be closer to 10 gigawatts of compute than five gigawatts of compute. That’s the way to think about it.”

ELON MUSK: SpaceX could have closer to 10 GW of compute next year. “We are building and deploying compute, I think, faster; our rate of growth certainly is faster than anyone else and our efficiency of compute deployment, I think, is also the highest. So we expect to end this year with over two gigawatts of compute. And probably our cumulative compute online by the end of next year will be several times higher. So it may, let’s say, be closer to 10 gigawatts of compute than five gigawatts of compute. That’s the way to think about it.”

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Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire

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KanekoaTheGreat

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When we first met Tom, his obsession with energy markets came through immediately. Seemed random, but it's "actually" central to what he's building at Actual Computer. The thesis is that local inference is inevitable. Open source models are getting good enough, people don't want to feed their thoughts to AI labs, and demand for compute will continue to be insatiable. But the main forcing function is that chips aren't the bottleneck anymore - power is. Compute is derivative of energy, and the massive data center buildout has created an energy shortage where GPUs sit idle waiting for power to come online. Yet one place that already has power, and always will, is everywhere else. Homes. Businesses. Universities. Collectively, they have more compute than all the data centers combined. Tom Lynch goal is to build a distributed network of people plugging in their local compute (devices like Mac minis to consumer Nvidia cards) to serve inference demand. The substrate he's chosen is Bittensor, on Subnet 95. Actual Computer has an exceptional team behind it, and this is one of the projects that's gotten me most excited in a long time. Enjoy this conversation with the two of us!

When we first met Tom, his obsession with energy markets came through immediately. Seemed random, but it's "actually" central to what he's building at Actual Computer. The thesis is that local inference is inevitable. Open source models are getting good enough, people don't want to feed their thoughts to AI labs, and demand for compute will continue to be insatiable. But the main forcing function is that chips aren't the bottleneck anymore - power is. Compute is derivative of energy, and the massive data center buildout has created an energy shortage where GPUs sit idle waiting for power to come online. Yet one place that already has power, and always will, is everywhere else. Homes. Businesses. Universities. Collectively, they have more compute than all the data centers combined. Tom Lynch goal is to build a distributed network of people plugging in their local compute (devices like Mac minis to consumer Nvidia cards) to serve inference demand. The substrate he's chosen is Bittensor, on Subnet 95. Actual Computer has an exceptional team behind it, and this is one of the projects that's gotten me most excited in a long time. Enjoy this conversation with the two of us!

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AI Compute —ubiquitous, invisible, and instant. Russ , Exabits Chief of Sales, on the future of compute: “You plug in your lamp, you get power. You don’t think about where it comes from. That’s our vision for GPUs—distributed, on-demand, and everywhere AI needs it.” Emerging providers like Exabits are the backbone of this shift—scaling infrastructure to meet global AI demand.

AI Compute —ubiquitous, invisible, and instant. Russ , Exabits Chief of Sales, on the future of compute: “You plug in your lamp, you get power. You don’t think about where it comes from. That’s our vision for GPUs—distributed, on-demand, and everywhere AI needs it.” Emerging providers like Exabits are the backbone of this shift—scaling infrastructure to meet global AI demand.

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Elon Musk: Artificial intelligence will continue to scale until we've harnessed all the energy of our galaxy. “I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy, sort of Kardashev 2, Kardashev 3 scale compute. One should think about artificial intelligence, not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of. Human intelligence has also scaled as the population has increased and we've been able to store more and more information.” Interview at the All-In Summit, September 10, 2025

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AI infrastructure has been running in the dark. Controlled by a handful of players, the industry has been held back by hidden pricing, secretive deals, and locked doors. We built to change that. Distributed compute. Transparent pricing. Open access. For everyone. Everywhere. For over two years we have been working to bring light to the dark. Today with the launch of our new brand design, we are giving form to the idea. The lights are on.

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Building the world's largest AI compute DePIN means has tens of thousands of independent node operators around the world. Providing alternatives to centralized cloud providers is more than bringing transactions for compute on-chain, it is tapping into the distributed compute that already exists in the world and making it available to innovators and builders advancing AI and ML. video from our community member leeland アブス ✳️

io.net

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Centralized AI inference runs on one provider. NEAR AI's confidential inference draws from multiple compute partners distributed across regions instead of a single data center. No KYC required. No visibility into what you're running. Intelligence owned by the user.

Centralized AI inference runs on one provider. NEAR AI's confidential inference draws from multiple compute partners distributed across regions instead of a single data center. No KYC required. No visibility into what you're running. Intelligence owned by the user.

NEAR Protocol

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EIF Insights Part 1: Power is everything. It’s reshaping the grid. Capital is everything. It’s reshaping infrastructure. Flexibility is everything. It’s reshaping computing. And distributed computing is the future. We’re moving toward clusters of computing infrastructure—built where power is abundant, scalable, and increasingly renewable. Instead of moving electrons long distances to compute, we can move compute closer to the electrons. The convergence is accelerating. Power isn’t just power anymore. Compute isn’t just compute anymore. The two are rapidly becoming one interconnected infrastructure layer. That convergence will create new technologies, new business models, and entirely new investment opportunities at the intersection of power and computing. $SLNH Soluna

EIF Insights Part 1: Power is everything. It’s reshaping the grid. Capital is everything. It’s reshaping infrastructure. Flexibility is everything. It’s reshaping computing. And distributed computing is the future. We’re moving toward clusters of computing infrastructure—built where power is abundant, scalable, and increasingly renewable. Instead of moving electrons long distances to compute, we can move compute closer to the electrons. The convergence is accelerating. Power isn’t just power anymore. Compute isn’t just compute anymore. The two are rapidly becoming one interconnected infrastructure layer. That convergence will create new technologies, new business models, and entirely new investment opportunities at the intersection of power and computing. $SLNH Soluna

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ELON MUSK: “The way to expand compute is really in space. There’s a lot of room in space. And if you look at the size of Earth relative to the Sun or relative to the Solar System, you realize just how tiny it is. We’re very, very tiny. We only receive about half a billionth of the Sun’s energy. So you can really think of Earth as being like a tiny dust mote in a vast darkness. So the way to expand compute without, you know, using up all the land on Earth is to do so in space. And then you can do it without using space for power and water on Earth; you can just do it in space. So I think we’ll probably be launching our first AI satellites next year, and then we’ll be able to do that, I think, at large scale in about two years.”

ELON MUSK: “The way to expand compute is really in space. There’s a lot of room in space. And if you look at the size of Earth relative to the Sun or relative to the Solar System, you realize just how tiny it is. We’re very, very tiny. We only receive about half a billionth of the Sun’s energy. So you can really think of Earth as being like a tiny dust mote in a vast darkness. So the way to expand compute without, you know, using up all the land on Earth is to do so in space. And then you can do it without using space for power and water on Earth; you can just do it in space. So I think we’ll probably be launching our first AI satellites next year, and then we’ll be able to do that, I think, at large scale in about two years.”

DogeDesigner

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Jim Cramer says $CRWV could play a role in orbital data centers if AI compute eventually moves to space. He said CoreWeave has one of the best handles on building data centers quickly making it a name to watch if the space-compute thesis becomes real.

Jim Cramer says $CRWV could play a role in orbital data centers if AI compute eventually moves to space. He said CoreWeave has one of the best handles on building data centers quickly making it a name to watch if the space-compute thesis becomes real.

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"Compute is the currency of the future." "Compute is the new OIL." Great, so how do I invest? You can play with the NVIDIA stock, or spin up an AI-Ready Data Center. Challenges of Spinning up AI-Ready Compute: Cost: Even a small cluster of H100 machines is upward to $10M GPU Scarcity: Unallocated or “underutilized” H100, A100, and RTX4090 GPUs are almost non-existent. Very Specific Physical & Technical Requirements: A data center with the right infrastructure is also very rare. There are only 10 in North America that deploy thousands of GPUs, in the open market. Domain Expertise: Teams of experts with the years of experience required to operate, deploy, and manage AI compute at scale are as rare as the GPUs they deploy. Exabits checks all of these boxes and we are the premier Compute Tokenization Platform. We are backed by REAL COMPUTE used by REAL CUSTOMERS.

"Compute is the currency of the future." "Compute is the new OIL." Great, so how do I invest? You can play with the NVIDIA stock, or spin up an AI-Ready Data Center. Challenges of Spinning up AI-Ready Compute: Cost: Even a small cluster of H100 machines is upward to $10M GPU Scarcity: Unallocated or “underutilized” H100, A100, and RTX4090 GPUs are almost non-existent. Very Specific Physical & Technical Requirements: A data center with the right infrastructure is also very rare. There are only 10 in North America that deploy thousands of GPUs, in the open market. Domain Expertise: Teams of experts with the years of experience required to operate, deploy, and manage AI compute at scale are as rare as the GPUs they deploy. Exabits checks all of these boxes and we are the premier Compute Tokenization Platform. We are backed by REAL COMPUTE used by REAL CUSTOMERS.

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JUST IN: #Cardano $ADA Founder Charles Hoskinson says "confidential compute by 2029 will be a $50B a year industry, and 75% of all AI workloads will run on confidential compute clusters. How do those servers talk and share workloads? We do the coordination between them." $NIGHT

JUST IN: #Cardano $ADA Founder Charles Hoskinson says "confidential compute by 2029 will be a $50B a year industry, and 75% of all AI workloads will run on confidential compute clusters. How do those servers talk and share workloads? We do the coordination between them." $NIGHT

Angry Crypto Show

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🚨OpenAI CFO speaks on AI boom and data centers “I think we are sooo in the early innings. I think a lot of prognosticators wanna call it “we’re on the sugar rush”… WE ARE NOT! more like the railroads or the build out of electricity. The internet turns out in hindsight a relatively capex light build out. I think we are just getting started! Now.. we have to do a lot to make data centers more efficient.. we need to think about new ways to power them. BUT in terms of AI, it is voracious right now for GPUs and COMPUTE. the biggest thing we face is WE ARE CONSTANTLY UNDER COMPUTE That’s why we launched Stargate. That’s why we are doing the BIGGER builds with ..Microsoft*, with ORACLE, CoreWeave and so on.. And we are just getting started!”

🚨OpenAI CFO speaks on AI boom and data centers “I think we are sooo in the early innings. I think a lot of prognosticators wanna call it “we’re on the sugar rush”… WE ARE NOT! more like the railroads or the build out of electricity. The internet turns out in hindsight a relatively capex light build out. I think we are just getting started! Now.. we have to do a lot to make data centers more efficient.. we need to think about new ways to power them. BUT in terms of AI, it is voracious right now for GPUs and COMPUTE. the biggest thing we face is WE ARE CONSTANTLY UNDER COMPUTE That’s why we launched Stargate. That’s why we are doing the BIGGER builds with ..Microsoft*, with ORACLE, CoreWeave and so on.. And we are just getting started!”

NIK

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😍 Watch Chef Rush’s new video to see what’s fueling his inspiration this week. Then, join the community on TON Real Talk for a deep dive into COCOON AI and the benefits of Confidential Compute Networks. The future is on TON 🚀

😍 Watch Chef Rush’s new video to see what’s fueling his inspiration this week. Then, join the community on TON Real Talk for a deep dive into COCOON AI and the benefits of Confidential Compute Networks. The future is on TON 🚀

TON 💎

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Elon Musk super bullish on compute: 10x more will 2x intelligence, it continues to scale all the way up to where most of the power of the sun is harnessed for compute & then ultimately most of the power of the galaxy, a Kardashev Type II, Kardashev Type III scale compute. $nvda

Elon Musk super bullish on compute: 10x more will 2x intelligence, it continues to scale all the way up to where most of the power of the sun is harnessed for compute & then ultimately most of the power of the galaxy, a Kardashev Type II, Kardashev Type III scale compute. $nvda

The AI Investor

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Atreides' Gavin Baker says that once Starship is reusable, the economics of orbital compute crush the economics of terrestrial compute. He lays out the math: "Once $SPCX can reuse Starship, the math for orbital compute becomes pretty compelling." "It's $60B to bring on a GW terrestrially. $25B is power and cooling — you don't need that in space. And so the right comp for that $35B in IT equipment — GPU, CPU, switches, memory, storage — is that $25B [in power and cooling] vs. the cost of launch." "And once Starship is reusable, I think the cost to launch is $5B. So that means you can put a GW into space for [$40B]. The GW on earth is $60B."

Atreides' Gavin Baker says that once Starship is reusable, the economics of orbital compute crush the economics of terrestrial compute. He lays out the math: "Once $SPCX can reuse Starship, the math for orbital compute becomes pretty compelling." "It's $60B to bring on a GW terrestrially. $25B is power and cooling — you don't need that in space. And so the right comp for that $35B in IT equipment — GPU, CPU, switches, memory, storage — is that $25B [in power and cooling] vs. the cost of launch." "And once Starship is reusable, I think the cost to launch is $5B. So that means you can put a GW into space for [$40B]. The GW on earth is $60B."

TBPN

102,778 Aufrufe • vor 2 Monaten