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Prediction: By 2030, global data center workloads are projected to split into: • 50% traditional workloads • 37% AI inference • 13% AI training Inference is set to become nearly 3× larger than training. As more AI applications move into production, builders will need infrastructure that can support lower-cost...

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FAR Labs

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20,706 görüntüleme • 4 ay önce •via X (Twitter)

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It’s live. AxonDAO’s GPU fleet is installed and will soon be rentable on the open market via vast.ai. Premium GPU capacity - 8x NVIDIA B200 and 8x RTX Pro 6000 - built for large-scale AI training, inference, rendering, and research workloads. 🧵
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It’s live. AxonDAO’s GPU fleet is installed and will soon be rentable on the open market via vast.ai. Premium GPU capacity - 8x NVIDIA B200 and 8x RTX Pro 6000 - built for large-scale AI training, inference, rendering, and research workloads. 🧵

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Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads.
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Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads.

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ROBA Compute is our GPU execution layer for robotics. A distributed infrastructure layer for simulation, training, inference, and autonomous workflows — built for our stack first, then opened to external builders. GPU rental is already a category. The missing layer is robotics-native infrastructure: templates, allocation, benchmarking, and persistent execution for embodied AI. That’s the opportunity. ROBA Compute is designed to become the infrastructure layer where robotics workloads actually run.
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ROBA Compute is our GPU execution layer for robotics. A distributed infrastructure layer for simulation, training, inference, and autonomous workflows — built for our stack first, then opened to external builders. GPU rental is already a category. The missing layer is robotics-native infrastructure: templates, allocation, benchmarking, and persistent execution for embodied AI. That’s the opportunity. ROBA Compute is designed to become the infrastructure layer where robotics workloads actually run.

Roba Labs

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Every search, recommendation, simulation and AI-generated response depends on rapid access to #data.​​ From training large AI models to enabling real-time inference, #DRAM helps keep today's most demanding workloads moving at the speed innovation requires.​​ This National DRAM day, join us in celebrating the technology that helps bridge the gap between processors and data, enabling everything from smartphones and PCs to #AI infrastructure.
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Every search, recommendation, simulation and AI-generated response depends on rapid access to #data.​​ From training large AI models to enabling real-time inference, #DRAM helps keep today's most demanding workloads moving at the speed innovation requires.​​ This National DRAM day, join us in celebrating the technology that helps bridge the gap between processors and data, enabling everything from smartphones and PCs to #AI infrastructure.

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AI doesn’t just need more GPUs. It needs better routing. OpenGPU connects AI workloads to underused data centers around the world. $OGPU
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AI doesn’t just need more GPUs. It needs better routing. OpenGPU connects AI workloads to underused data centers around the world. $OGPU

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Our newest AI accelerator Maia 200 is now online in Azure. Designed for industry-leading inference efficiency, it delivers 30% better performance per dollar than current systems. And with 10+ PFLOPS FP4 throughput, ~5 PFLOPS FP8, and 216GB HBM3e with 7TB/s of memory bandwidth it's optimized for large-scale AI workloads. It joins our broader portfolio of CPUs, GPUs, and custom accelerators, giving customers more options to run advanced AI workloads faster and more cost-effectively on Azure.
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Our newest AI accelerator Maia 200 is now online in Azure. Designed for industry-leading inference efficiency, it delivers 30% better performance per dollar than current systems. And with 10+ PFLOPS FP4 throughput, ~5 PFLOPS FP8, and 216GB HBM3e with 7TB/s of memory bandwidth it's optimized for large-scale AI workloads. It joins our broader portfolio of CPUs, GPUs, and custom accelerators, giving customers more options to run advanced AI workloads faster and more cost-effectively on Azure.

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In 3... 2... 1... $IREN is live NVIDIA GTC! Visit us at Booth #1107 to learn how our vertically integrated AI Cloud is enabling high-performance AI training and inference at scale. #GTC2026 #AI #CloudInfrastructure #DataCenters
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In 3... 2... 1... $IREN is live NVIDIA GTC! Visit us at Booth #1107 to learn how our vertically integrated AI Cloud is enabling high-performance AI training and inference at scale. #GTC2026 #AI #CloudInfrastructure #DataCenters

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70% of AI compute in 2026 is inference. Not training. The models are built. The real infrastructure challenge is serving them at scale to millions of users and agents, every day, in production. Most enterprise infrastructure is still optimized for the wrong workload.🧵
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70% of AI compute in 2026 is inference. Not training. The models are built. The real infrastructure challenge is serving them at scale to millions of users and agents, every day, in production. Most enterprise infrastructure is still optimized for the wrong workload.🧵

Aethir

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First AI Credit Marketplace + inference trading on @Arc. Coming soon. 👀 Sell unused AI credits. Buy inference for less. Trade OpenAI ↔ Claude and more. AI inference is becoming a market.
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First AI Credit Marketplace + inference trading on @Arc. Coming soon. 👀 Sell unused AI credits. Buy inference for less. Trade OpenAI ↔ Claude and more. AI inference is becoming a market.

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You don’t need a data center to support private AI. ⬟ Private inference doesn’t live in one place. It runs across the network. If your device is online, it can contribute to privacy-preserving execution. Run a node on the Nesa network.
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You don’t need a data center to support private AI. ⬟ Private inference doesn’t live in one place. It runs across the network. If your device is online, it can contribute to privacy-preserving execution. Run a node on the Nesa network.

Nesa

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Introducing SERV Hackathon 02 track partners: Dolphin KITE AI ✈️ Money20/20 USA🇺🇸 Reppo From inference and agentic payments to AI data markets, add SERV to your AI stack and build more reliable agents at lower cost. Hackathon info drops next week. Build with SERV:
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Introducing SERV Hackathon 02 track partners: Dolphin KITE AI ✈️ Money20/20 USA🇺🇸 Reppo From inference and agentic payments to AI data markets, add SERV to your AI stack and build more reliable agents at lower cost. Hackathon info drops next week. Build with SERV:

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Meet AIOZ AI, the Web3 foundation for Everything Intelligence. It unifies AI compute, storage, and AI services in one platform. → DePIN Compute for AI training & inference → Distributed Storage for AI assets → Production-ready AI workflows → Infrastructure for Agentic AI
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Meet AIOZ AI, the Web3 foundation for Everything Intelligence. It unifies AI compute, storage, and AI services in one platform. → DePIN Compute for AI training & inference → Distributed Storage for AI assets → Production-ready AI workflows → Infrastructure for Agentic AI

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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.
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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.

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NEW: NEAR Protocol ANNOUNCES THAT Brave LEO NOW RUNS ON PRIVATE AI INFERENCE FROM NEAR AI CLOUD, BY NEAR AI SOURCE:
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NEW: NEAR Protocol ANNOUNCES THAT Brave LEO NOW RUNS ON PRIVATE AI INFERENCE FROM NEAR AI CLOUD, BY NEAR AI SOURCE:

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A Python decorator is all you need to deploy AI apps! Beam is an open-source alternative to Modal for deploying serverless AI workloads. Simply pip install beam, add a decorator, and turn any function into a serverless endpoint! 100% open-source.
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A Python decorator is all you need to deploy AI apps! Beam is an open-source alternative to Modal for deploying serverless AI workloads. Simply pip install beam, add a decorator, and turn any function into a serverless endpoint! 100% open-source.

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elizaOS by ai16z Leverages Hyperbolic's Decentralized Infrastructure to Scale AI Agents Hyperbolic's GPU marketplace, verifiable inference, and AgentKit now power ElizaOS AI agents with scalable, reliable infrastructure, enabling developers to build more autonomous and capable AI systems. Hyperbolic isn’t just powering ElizaOS —it’s powering the biggest companies in AI and blockchain. We’re the only company providing scalable, decentralized AI infrastructure that seamlessly bridges both spaces.

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x402 payments are now wired into OpenGateway. You can now top up credits using USDC with 0 gas! Crypto-native payments for AI inference are here! Faster rails, lower friction, and built for builders. built on Base
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x402 payments are now wired into OpenGateway. You can now top up credits using USDC with 0 gas! Crypto-native payments for AI inference are here! Faster rails, lower friction, and built for builders. built on Base

GitLawb

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This week on Foresight Talk, we’re excited to welcome OpenGradient as our special guest. Verifiable AI inference on-chain is set to handle the most mission-critical AI inference workloads. Join the founder of OpenGradient @0xDeltaHedged and the Vice President of Foresight Ventures ian for a discussion. Foresight Ventures ​ Foresight News丨APP 重磅更新 Set a reminder for an insightful conversation on the potential of this emerging synergy. 📅10/16 SGT 9:00 AM; 10/15 EST 9:00 PM
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This week on Foresight Talk, we’re excited to welcome OpenGradient as our special guest. Verifiable AI inference on-chain is set to handle the most mission-critical AI inference workloads. Join the founder of OpenGradient @0xDeltaHedged and the Vice President of Foresight Ventures ian for a discussion. Foresight Ventures ​ Foresight News丨APP 重磅更新 Set a reminder for an insightful conversation on the potential of this emerging synergy. 📅10/16 SGT 9:00 AM; 10/15 EST 9:00 PM

Foresight Ventures ​

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Shelby can reduce your cost to move data by up to 70%. Shelby lets you store once and access anywhere, with verifiable retrieval receipts and cryptographic proof of delivery. Built for high-read AI workloads. Early Access Is Open.
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Shelby can reduce your cost to move data by up to 70%. Shelby lets you store once and access anywhere, with verifiable retrieval receipts and cryptographic proof of delivery. Built for high-read AI workloads. Early Access Is Open.

Shelby

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