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ROBA Compute is officially LIVE. This isn't a feature drop. This is ROBA expanding into the AI infrastructure market - hundreds of billions in scale, and we're staking our claim. Rent GPUs on-demand. Enterprise-grade allocation. Transparent USDC pricing. Zero hidden fees and all on-chain. We're already in talks with...

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Roba Labs

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44,287 görüntüleme • 1 ay önce •via X (Twitter)

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Over 2,000 NVIDIA B300 GPUs are going live in a mega-cluster on Aethir's decentralized cloud very soon. ☁️ This is next-level infrastructure that unlocks access for the most ambitious AI workloads and use cases. 💻 Enterprise-grade GPU compute, ready to scale with your ambitions. ⚡️ Listen to Mark Rydon, our Co-Founder, explain the importance of Aethir’s B300 deployment.
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Over 2,000 NVIDIA B300 GPUs are going live in a mega-cluster on Aethir's decentralized cloud very soon. ☁️ This is next-level infrastructure that unlocks access for the most ambitious AI workloads and use cases. 💻 Enterprise-grade GPU compute, ready to scale with your ambitions. ⚡️ Listen to Mark Rydon, our Co-Founder, explain the importance of Aethir’s B300 deployment.

Aethir

12,867 görüntüleme • 6 ay önce

"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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"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.

Exabits

13,896 görüntüleme • 2 yıl önce

Introducing PulseAI, where your data is your knowledge. PulseAI Platform is an agent-to-silicon AI infrastructure platform built to keep your data secure and sovereign, enabling the next AI enterprise. Offered in form factors for every stage of enterprise AI, PulseAI enables enterprise from initial pilot to hyperscale. Combining Gruve's AI-native services with NVIDIA-powered GPU architectures, it scales from 16 RTX 6000 PRO to 2,048 B300 GPUs, with security, storage, and compute integrated. The next enterprise is built on its own data and intelligence. We are here to enable it. Book your consultation: Read more on PulseAI from our Chief AI & Technology Officer Matt Robinson:
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Introducing PulseAI, where your data is your knowledge. PulseAI Platform is an agent-to-silicon AI infrastructure platform built to keep your data secure and sovereign, enabling the next AI enterprise. Offered in form factors for every stage of enterprise AI, PulseAI enables enterprise from initial pilot to hyperscale. Combining Gruve's AI-native services with NVIDIA-powered GPU architectures, it scales from 16 RTX 6000 PRO to 2,048 B300 GPUs, with security, storage, and compute integrated. The next enterprise is built on its own data and intelligence. We are here to enable it. Book your consultation: Read more on PulseAI from our Chief AI & Technology Officer Matt Robinson:

Gruve

66,390 görüntüleme • 3 ay önce

If intelligence is the log of compute… it starts with a lot of compute! And that’s why we’re scaling our GPU fleet faster than anyone else. Just last year, we added over 2 gigawatts of new capacity – roughly the output of 2 nuclear power plants. And today we’re going further, announcing the world's most powerful AI datacenter, located in southeastern Wisconsin. Fairwater is a seamless cluster of hundreds of thousands of NVIDIA GB200s, connected by enough fiber to circle the Earth 4.5 times. It will deliver 10x the performance of the world’s fastest supercomputer today, enabling AI training and inference workloads at a level never before seen. For AI training workloads, you need compute at exponential scale. That’s why we designed the datacenter, GPU fleet, and network together as one integrated system. This ensures a single job can run from day 1 at exponential scale across thousands of GPUs. Fairwater uses a liquid-cooled closed-loop system for cooling GPUs that requires zero water for operations after construction. And we’re matching all of the energy that is consumed with renewable sources. And of course, it is just one of several similar sites we’re lighting up across our 70+ regions. We have multiple identical Fairwater datacenters under construction in other locations across the US, in addition to our AI infrastructure already deployed in over 100 datacenters around the world, powering model training, test-time compute, RL tuning, and real-time inference at global scale. Too often during times like this, people go with the current and only later wonder, how did we get here? With Fairwater, we're charting a new path: doing the hard engineering work, bringing compute, network, and storage into one highly scaled cluster, and designing closed-loop energy systems to meet real-world computing needs. And partnering with local communities to ensure it's thoughtfully done in a way that is sustainable, creates new jobs, and expands opportunity. We are thrilled to see this take hold in Wisconsin, and we are just getting started.
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If intelligence is the log of compute… it starts with a lot of compute! And that’s why we’re scaling our GPU fleet faster than anyone else. Just last year, we added over 2 gigawatts of new capacity – roughly the output of 2 nuclear power plants. And today we’re going further, announcing the world's most powerful AI datacenter, located in southeastern Wisconsin. Fairwater is a seamless cluster of hundreds of thousands of NVIDIA GB200s, connected by enough fiber to circle the Earth 4.5 times. It will deliver 10x the performance of the world’s fastest supercomputer today, enabling AI training and inference workloads at a level never before seen. For AI training workloads, you need compute at exponential scale. That’s why we designed the datacenter, GPU fleet, and network together as one integrated system. This ensures a single job can run from day 1 at exponential scale across thousands of GPUs. Fairwater uses a liquid-cooled closed-loop system for cooling GPUs that requires zero water for operations after construction. And we’re matching all of the energy that is consumed with renewable sources. And of course, it is just one of several similar sites we’re lighting up across our 70+ regions. We have multiple identical Fairwater datacenters under construction in other locations across the US, in addition to our AI infrastructure already deployed in over 100 datacenters around the world, powering model training, test-time compute, RL tuning, and real-time inference at global scale. Too often during times like this, people go with the current and only later wonder, how did we get here? With Fairwater, we're charting a new path: doing the hard engineering work, bringing compute, network, and storage into one highly scaled cluster, and designing closed-loop energy systems to meet real-world computing needs. And partnering with local communities to ensure it's thoughtfully done in a way that is sustainable, creates new jobs, and expands opportunity. We are thrilled to see this take hold in Wisconsin, and we are just getting started.

Satya Nadella

2,025,048 görüntüleme • 1 yıl önce

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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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

KanekoaTheGreat

39,709 görüntüleme • 3 ay önce

🚨ELON: AI COMPUTE WILL BE CHEAPEST IN SPACE “Once we get solar domestically at scale and launch Starship at scale, the cheapest way to do AI compute will be in space. With full reusability, propellant cost per flight is close to a million dollars... That’s about a million dollars to transport 10 megawatts of AI compute.” Source: Philip Johnston
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🚨ELON: AI COMPUTE WILL BE CHEAPEST IN SPACE “Once we get solar domestically at scale and launch Starship at scale, the cheapest way to do AI compute will be in space. With full reusability, propellant cost per flight is close to a million dollars... That’s about a million dollars to transport 10 megawatts of AI compute.” Source: Philip Johnston

Mario Nawfal

35,283 görüntüleme • 8 ay önce

Sam Altman on why he likes hard problems (like making his own chip) “Philosophically I'm very inclined to try to find the high-leverage, difficult problem that will continue the exponential. And for us this is models and compute. Those are problems that naturally suit me.” “To scale compute in the way that we're doing requires a complex supply chain. There's a lot of interesting partnerships to figure out, which I like doing. There's interesting financial challenges of how you're going to finance what is rapidly becoming the most expensive infrastructure project in history.” “The technology questions that go into building out compute at this scale from designing your own chip, to the supply chain of fabs and people that make racks, to the power systems for these things. There are a lot of problems that are interesting across technology, business, policy, supply chain, logistics— all come together around building compute at this kind of scale.”
1:05

Sam Altman on why he likes hard problems (like making his own chip) “Philosophically I'm very inclined to try to find the high-leverage, difficult problem that will continue the exponential. And for us this is models and compute. Those are problems that naturally suit me.” “To scale compute in the way that we're doing requires a complex supply chain. There's a lot of interesting partnerships to figure out, which I like doing. There's interesting financial challenges of how you're going to finance what is rapidly becoming the most expensive infrastructure project in history.” “The technology questions that go into building out compute at this scale from designing your own chip, to the supply chain of fabs and people that make racks, to the power systems for these things. There are a lot of problems that are interesting across technology, business, policy, supply chain, logistics— all come together around building compute at this kind of scale.”

David Senra

27,700 görüntüleme • 18 gün önce

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.
1:19

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

26,820 görüntüleme • 12 gün önce

In a matter of few months, Phoenix’s AI Utility Staking has grown rapidly and surpassed the milestone of 500,000 PHB, with Ink Finance being latest AI Ecosystem partner to stake (more details of this to come). Current applications, use cases, and synergies for our utility staking partners include but are not limited to AI trading, decentralized compute infrastructure, AI agents, AI-powered DeSci, and vertical use-case LLMs. Phoenix is at the forefront of driving real world application-specific adoption of decentralized AI infrastructure – and this is just the beginning. #Phoenix $PHB
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In a matter of few months, Phoenix’s AI Utility Staking has grown rapidly and surpassed the milestone of 500,000 PHB, with Ink Finance being latest AI Ecosystem partner to stake (more details of this to come). Current applications, use cases, and synergies for our utility staking partners include but are not limited to AI trading, decentralized compute infrastructure, AI agents, AI-powered DeSci, and vertical use-case LLMs. Phoenix is at the forefront of driving real world application-specific adoption of decentralized AI infrastructure – and this is just the beginning. #Phoenix $PHB

Phoenix AI Labs

50,724 görüntüleme • 1 yıl önce

Announcing ComputeConnect, the financial industry’s first exchange-for-physical (EFP) network for compute, coming soon from Architect and Compute Desk. ComputeConnect links US exchange-traded compute futures to compute capacity delivery. Exchange-listed cash-settled compute futures are entering US markets to correct course on the current AI economy, reorienting debt to long-term growth: • Creating price discovery and transparency independent of any single capacity provider. • Establishing a forward curve for measuring deprecation and forecasting supply and demand. • Providing financial hedges for compute consumers and producers. • Enabling hedge funds, ETF companies, and traders to gain long and short financial exposure to compute. US cash-settled compute futures lack a physical delivery mechanism, and ComputeConnect fills this gap. Existing physically settled futures such as energy and agriculturals require their clearing house (DCO) to set a uniform standard for the grade and delivery method for the underlying commodity. Compute, by contrast, is highly fragmented, heterogeneous, and rapidly evolving, making it infeasible for any single DCO to define and enforce comparable standards. ComputeConnect establishes a network of compute capacity providers and links the network with Architect’s US futures products using exchange-for-physicals (EFPs), OTC contracts in which futures positions are exchanged for the assets the futures track. EFPs allow counterparties to negotiate the grade, timing, location, and other characteristics of the commodity along with a basis tied to the futures settlement price. ComputeConnect will • Build a network of capacity providers and capacity marketplaces. • Establish an open protocol for members of the network to receive delivery requests and advertise available GPUs. • Publish standard basis tables for different SKUs, memory configurations, and locations for GPUs. • Book the futures legs of the transactions to Architect’s DCM, the American Innovation Exchange. • Facilitate and guarantee delivery of capacity using Compute Desk’s ComputeClear platform. The advancement of US AI is constrained at every link in the supply chain: materials, power, chips, capital… The American Innovation Exchange, ComputeConnect, and our industry partners aim to secure compute’s dominance as an American asset class.
0:21

Announcing ComputeConnect, the financial industry’s first exchange-for-physical (EFP) network for compute, coming soon from Architect and Compute Desk. ComputeConnect links US exchange-traded compute futures to compute capacity delivery. Exchange-listed cash-settled compute futures are entering US markets to correct course on the current AI economy, reorienting debt to long-term growth: • Creating price discovery and transparency independent of any single capacity provider. • Establishing a forward curve for measuring deprecation and forecasting supply and demand. • Providing financial hedges for compute consumers and producers. • Enabling hedge funds, ETF companies, and traders to gain long and short financial exposure to compute. US cash-settled compute futures lack a physical delivery mechanism, and ComputeConnect fills this gap. Existing physically settled futures such as energy and agriculturals require their clearing house (DCO) to set a uniform standard for the grade and delivery method for the underlying commodity. Compute, by contrast, is highly fragmented, heterogeneous, and rapidly evolving, making it infeasible for any single DCO to define and enforce comparable standards. ComputeConnect establishes a network of compute capacity providers and links the network with Architect’s US futures products using exchange-for-physicals (EFPs), OTC contracts in which futures positions are exchanged for the assets the futures track. EFPs allow counterparties to negotiate the grade, timing, location, and other characteristics of the commodity along with a basis tied to the futures settlement price. ComputeConnect will • Build a network of capacity providers and capacity marketplaces. • Establish an open protocol for members of the network to receive delivery requests and advertise available GPUs. • Publish standard basis tables for different SKUs, memory configurations, and locations for GPUs. • Book the futures legs of the transactions to Architect’s DCM, the American Innovation Exchange. • Facilitate and guarantee delivery of capacity using Compute Desk’s ComputeClear platform. The advancement of US AI is constrained at every link in the supply chain: materials, power, chips, capital… The American Innovation Exchange, ComputeConnect, and our industry partners aim to secure compute’s dominance as an American asset class.

Brett Harrison

28,436 görüntüleme • 2 ay önce

In the 20th century, power depended on OIL and STEEL. In the 21st century, power depends on AI, CHIPS and COMPUTE CAPABILITY. At AI Summit 2026 India, I spoke about why the GPU challenge is not just a ‘supply chain issue’ but a ‘sovereignty issue’. In the AI century, power will rest with those who control chips, compute capacity and data centres. Today, design monopolies, manufacturing concentration and export controls determine who gets access. India controls none of these critical levers. We have the talent. We have the ambition. We have the intent. We have the capital. But talent without compute is aspiration. And compute without sovereignty is dependence. The role of policymakers is not to slow AI down; it is to remove bottlenecks, diversify access, set clear national targets, and build sovereign AI infrastructure in India. This is not partisan. It is strategic. #IndiaAIImpactSummit2026 #AI #ResponsibleAI #ArtificialIntelligence #BharatMandapam
3:41

In the 20th century, power depended on OIL and STEEL. In the 21st century, power depends on AI, CHIPS and COMPUTE CAPABILITY. At AI Summit 2026 India, I spoke about why the GPU challenge is not just a ‘supply chain issue’ but a ‘sovereignty issue’. In the AI century, power will rest with those who control chips, compute capacity and data centres. Today, design monopolies, manufacturing concentration and export controls determine who gets access. India controls none of these critical levers. We have the talent. We have the ambition. We have the intent. We have the capital. But talent without compute is aspiration. And compute without sovereignty is dependence. The role of policymakers is not to slow AI down; it is to remove bottlenecks, diversify access, set clear national targets, and build sovereign AI infrastructure in India. This is not partisan. It is strategic. #IndiaAIImpactSummit2026 #AI #ResponsibleAI #ArtificialIntelligence #BharatMandapam

Raghav Chadha

70,153 görüntüleme • 6 ay önce

$MU $SKHY $DRAM Holy Shit $AMD's Lisa Su just spent two full minutes at the 2026 AI keynote raving about HBM4 capacity as the thing that separates Helios from the competition. Not compute. Memory. "When you compare Helios to the competition, we're delivering 15% more compute, 50% more HBM4 memory capacity and memory bandwidth, and 50% more scale-out bandwidth." Notice which number is bigger. "What that means is that every Helios can deliver more performance for the largest models, more capacity for longer context, and the bandwidth to scale across thousands of racks.... More than 18,000 CDNA five GPU compute units, over 4,600 Zen 6 CPU cores, and 31 terabytes of HBM4 memory, all in a single rack." "That's what it takes to run agentic AI at scale. Today, I'm excited to announce that Helios is in full production. We have shipments on track to start at the end of the third quarter and ramping into the fourth quarter in the second half of the year. I can tell you, customer demand for Helios is extremely strong, we're extremely proud of the work that we have done across the leading AI labs to adopt Helios."
1:53

$MU $SKHY $DRAM Holy Shit $AMD's Lisa Su just spent two full minutes at the 2026 AI keynote raving about HBM4 capacity as the thing that separates Helios from the competition. Not compute. Memory. "When you compare Helios to the competition, we're delivering 15% more compute, 50% more HBM4 memory capacity and memory bandwidth, and 50% more scale-out bandwidth." Notice which number is bigger. "What that means is that every Helios can deliver more performance for the largest models, more capacity for longer context, and the bandwidth to scale across thousands of racks.... More than 18,000 CDNA five GPU compute units, over 4,600 Zen 6 CPU cores, and 31 terabytes of HBM4 memory, all in a single rack." "That's what it takes to run agentic AI at scale. Today, I'm excited to announce that Helios is in full production. We have shipments on track to start at the end of the third quarter and ramping into the fourth quarter in the second half of the year. I can tell you, customer demand for Helios is extremely strong, we're extremely proud of the work that we have done across the leading AI labs to adopt Helios."

Trade Whisperer

180,469 görüntüleme • 1 ay önce

So what Warren Pies is saying: Anthropic’s Mythos rollout triggered a sharp collapse in $NVDA GPU availability, with supply effectively tightening to near zero as demand for frontier models accelerated. Q1 2026 revenue from Anthropic reinforces that this isn’t theoretical demand, it’s real dollars chasing compute at scale across the AI ecosystem, from $GOOGL GCP to $AMZN AWS. The takeaway is simple: better models require more compute, and that feedback loop continues to drive the entire AI infrastructure trade.
3:10

So what Warren Pies is saying: Anthropic’s Mythos rollout triggered a sharp collapse in $NVDA GPU availability, with supply effectively tightening to near zero as demand for frontier models accelerated. Q1 2026 revenue from Anthropic reinforces that this isn’t theoretical demand, it’s real dollars chasing compute at scale across the AI ecosystem, from $GOOGL GCP to $AMZN AWS. The takeaway is simple: better models require more compute, and that feedback loop continues to drive the entire AI infrastructure trade.

Sam Badawi

21,184 görüntüleme • 4 ay önce

Distributed compute needs to be deployed with speed, scale, and sovereignty. Dan Wright joined Bloomberg Technology this week to talk about Galleon Forge One, our Series B, and the infrastructure buildout required to meet growing demand for inference, fine-tuning, and distributed model deployment at scale. The next wave of compute will not live only in centralized clouds. It will need to be deployed where land, energy, and data already exist. That is what Armada was built for. That is what Galleon delivers.
3:58

Distributed compute needs to be deployed with speed, scale, and sovereignty. Dan Wright joined Bloomberg Technology this week to talk about Galleon Forge One, our Series B, and the infrastructure buildout required to meet growing demand for inference, fine-tuning, and distributed model deployment at scale. The next wave of compute will not live only in centralized clouds. It will need to be deployed where land, energy, and data already exist. That is what Armada was built for. That is what Galleon delivers.

Armada

934,749 görüntüleme • 3 ay önce

Olam Labs CEO sensho says the only two bottlenecks left to AGI and ASI are compute and data. "For AGI and ASI to come there are only two bottlenecks right now. We have no bottleneck with architecture or agents. It's data and compute." "Compute is the biggest bottleneck." "We're gonna have 10x more compute coming online in the next two years. If you're scaling law-pilled and if you're -pilled in all the ways that these AI labs are, then data is the actual bottleneck."
1:03

Olam Labs CEO sensho says the only two bottlenecks left to AGI and ASI are compute and data. "For AGI and ASI to come there are only two bottlenecks right now. We have no bottleneck with architecture or agents. It's data and compute." "Compute is the biggest bottleneck." "We're gonna have 10x more compute coming online in the next two years. If you're scaling law-pilled and if you're -pilled in all the ways that these AI labs are, then data is the actual bottleneck."

TBPN

43,406 görüntüleme • 3 gün önce

"One of the first things we wanna do in January is launch $FXRP as a trading on the Hyperliquid DEX so market makers can trade at scale..." -Hugo Philion ✅ 1st goal of 2026 for Flare ☀️ Flare 2.0 coming in mid 126 with the verifiable off chain compute platform that's gonna allow for confidential compute and regulatory compliant privacy in DeFi 🚀
2:08

"One of the first things we wanna do in January is launch $FXRP as a trading on the Hyperliquid DEX so market makers can trade at scale..." -Hugo Philion ✅ 1st goal of 2026 for Flare ☀️ Flare 2.0 coming in mid 126 with the verifiable off chain compute platform that's gonna allow for confidential compute and regulatory compliant privacy in DeFi 🚀

Mickey_B_Fresh☀️🪝

28,165 görüntüleme • 8 ay önce