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Introducing NodeAI's High-Performance GPUs! From RTX A5000 to H100 NVL PCI-E, our server-grade GPUs are now available for deployment. Scale your AI & compute-heavy apps effortlessly with our global decentralized network.

Node AI | $GPU

37,234 subscribers

30,391 次观看 • 1 年前 •via X (Twitter)

科学技术健康养生

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Private livecam show

8 条评论

CryptoBit 🔔 的头像

CryptoBit 🔔1 年前

$GPU 👀 There is no second best!

JM 🦍 的头像

JM 🦍1 年前

$GPU

Woooooooptii🍀 的头像

Woooooooptii🍀1 年前

Bullish 🙌🙌🙌 #GPU @NodeAIETH

egg 的头像

egg1 年前

$gpu

SpungePump 的头像

SpungePump1 年前

Billions billions Billions!!!! $GPU @NodeAIETH 🚀🟢🚀🟢🚀🟢🚀🟢💎

Jola 的头像

Jola1 年前

THIS 📈💎 $GPU

Mafioso 的头像

Mafioso1 年前

$GPU WILL PRINT $$$

Kuma 的头像

Kuma1 年前

Yesss! My #1 feature request for $GPU - more 1-click deployment options! Super excited about this!

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🤖 AI agents need serious compute. 🌐 NodeAI brings it—100,000+ server-grade GPUs in one decentralized network. Train, deploy, and scale agents instantly, without bottlenecks or sticker shock. Power your AI with NodeAI. ⚡️ #NodeAI #GPU #AI

🤖 AI agents need serious compute. 🌐 NodeAI brings it—100,000+ server-grade GPUs in one decentralized network. Train, deploy, and scale agents instantly, without bottlenecks or sticker shock. Power your AI with NodeAI. ⚡️ #NodeAI #GPU #AI

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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.

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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12,895 次观看 • 7 个月前

GPU Network Upgrade Incoming! We’re expanding to 100K+ server-grade GPUs via our new aggregator. - $GPU holders get deeper deployment discounts. - Stakers earn a larger share of the boosted revenue. Scale faster, earn more—update goes live soon! ⚡️ #AI #GPU #NodeAI

GPU Network Upgrade Incoming! We’re expanding to 100K+ server-grade GPUs via our new aggregator. - $GPU holders get deeper deployment discounts. - Stakers earn a larger share of the boosted revenue. Scale faster, earn more—update goes live soon! ⚡️ #AI #GPU #NodeAI

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10,159 次观看 • 1 年前

Scale your AI inference, graphics, and analytics workloads with the GPU power to get you there. Amazon EC2 G7 instances are now generally available—accelerated by @NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs, first on AWS.

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We are excited to share a preview of our peer-to-peer decentralized inference stack Engineered for consumer GPUs and high-latency networks — plus a research roadmap to scale it to a planetary-scale decentralized inference engine.

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Introducing Supermicro Solutions Featuring NVIDIA RTX PRO™ Blackwell Server Edition GPUs

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Everyone’s still talking about GPUs. Meanwhile, memory is now the real constraint for AI at scale. From GTC, Patrick Moorhead & Daniel Newman are joined by Paul Cho & Indong Kim from Samsung Semiconductor US to discuss why bandwidth, not compute, is starting to define AI performance.

Everyone’s still talking about GPUs. Meanwhile, memory is now the real constraint for AI at scale. From GTC, Patrick Moorhead & Daniel Newman are joined by Paul Cho & Indong Kim from Samsung Semiconductor US to discuss why bandwidth, not compute, is starting to define AI performance.

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$Successfully deployed Deepseek R1 Distilled 70B (AWQ) across 8x NVIDIA RTX 3080 10G GPUs, achieving 60 tokens/s with full tensor parallelism via PCIe. Total hardware cost: $6,400 This demonstrates that consumer GPUs can deliver substantial ML inference capabilities at a fraction of the cost of datacenter hardware. For perspective, a single A100 80G costs $17,550, while a H100 80G runs $25,000. Our testing validates an often-overlooked opportunity: millions of idle crypto mining rigs could be repurposed into a powerful, distributed AI infrastructure. The performance-to-cost ratio of consumer GPUs, especially when properly optimized for tensor operations, presents a compelling case for decentralized AI compute. We're excited to share more insights as we continue pushing the boundaries of consumer hardware in AI workloads.$

Successfully deployed Deepseek R1 Distilled 70B (AWQ) across 8x NVIDIA RTX 3080 10G GPUs, achieving 60 tokens/s with full tensor parallelism via PCIe. Total hardware cost: $6,400 This demonstrates that consumer GPUs can deliver substantial ML inference capabilities at a fraction of the cost of datacenter hardware. For perspective, a single A100 80G costs $17,550, while a H100 80G runs $25,000. Our testing validates an often-overlooked opportunity: millions of idle crypto mining rigs could be repurposed into a powerful, distributed AI infrastructure. The performance-to-cost ratio of consumer GPUs, especially when properly optimized for tensor operations, presents a compelling case for decentralized AI compute. We're excited to share more insights as we continue pushing the boundaries of consumer hardware in AI workloads.

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