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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. 🧵

AxonDAO

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17,725 просмотров • 7 месяцев назад •via X (Twitter)

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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 inference, reliable execution, faster routing and private workloads at scale. This is where FAR AI enters the market. Source: JLL Research, 2025

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 inference, reliable execution, faster routing and private workloads at scale. This is where FAR AI enters the market. Source: JLL Research, 2025

FAR Labs

20,706 просмотров • 3 месяцев назад

⛓️ Aethir - the decentralized #GPU powerhouse reshaping #AI & #gaming! Aethir is building the future of high-performance computing with a global #DePIN network of 400,000+ enterprise-grade GPU containers (including #NVIDIA H100s, H200s & more) spanning 90+ countries. 📍 Two flagship products: • Aethir Earth – Bare-metal GPU cloud delivering raw power for AI training, fine-tuning & inference with zero virtualization overhead. • Aethir Atmosphere – Low-latency cloud gaming rendering that streams high-quality experiences to any device. ☁️ Cloud Hosts monetize idle GPUs and earn $ATH rewards, while customers get scalable, cost-efficient compute (up to 80% cheaper than traditional clouds), ultra-low latency, and 95%+ utilization rates. No massive CapEx, no vendor lock-in – just on-demand access closer to the edge. From AI model training to real-time cloud gaming and beyond, Aethir is democratizing enterprise GPU power and powering the next generation of innovation. 🦾 Axe Compute’s $317M in customer prepayments. That single number reframes how AI data centers get built in 2026 🧵 The decentralized cloud is here. Are you ready? 🌐 #Aethir #DePIN #AI #GPUCloud #Web3

⛓️ Aethir - the decentralized #GPU powerhouse reshaping #AI & #gaming! Aethir is building the future of high-performance computing with a global #DePIN network of 400,000+ enterprise-grade GPU containers (including #NVIDIA H100s, H200s & more) spanning 90+ countries. 📍 Two flagship products: • Aethir Earth – Bare-metal GPU cloud delivering raw power for AI training, fine-tuning & inference with zero virtualization overhead. • Aethir Atmosphere – Low-latency cloud gaming rendering that streams high-quality experiences to any device. ☁️ Cloud Hosts monetize idle GPUs and earn $ATH rewards, while customers get scalable, cost-efficient compute (up to 80% cheaper than traditional clouds), ultra-low latency, and 95%+ utilization rates. No massive CapEx, no vendor lock-in – just on-demand access closer to the edge. From AI model training to real-time cloud gaming and beyond, Aethir is democratizing enterprise GPU power and powering the next generation of innovation. 🦾 Axe Compute’s $317M in customer prepayments. That single number reframes how AI data centers get built in 2026 🧵 The decentralized cloud is here. Are you ready? 🌐 #Aethir #DePIN #AI #GPUCloud #Web3

Crypto Holding™ 💎

229,806 просмотров • 1 месяц назад

As a supporter of the open weights ecosystem, we're proud to be a post-training partner for NVIDIA Nemotron. We post-train Nemotron models for customer use cases, de-risk mainline RL runs on our AC2 platform and training stack, and contribute aggregate workload statistics for inference benchmarking. This is how open models get better, and we're excited to keep working closely with NVIDIA AI.

As a supporter of the open weights ecosystem, we're proud to be a post-training partner for NVIDIA Nemotron. We post-train Nemotron models for customer use cases, de-risk mainline RL runs on our AC2 platform and training stack, and contribute aggregate workload statistics for inference benchmarking. This is how open models get better, and we're excited to keep working closely with NVIDIA AI.

Applied Compute

25,683 просмотров • 1 месяц назад

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.🧵

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

21,202 просмотров • 3 месяцев назад

parakeet.cpp: native C++/ggml (ggml) inference for NVIDIA AI Developer's Parakeet, one of the best speech-to-text models out there, from the LocalAI team. Every Parakeet model (TDT/CTC/RNNT/hybrid + cache-aware streaming), byte-for-byte identical output to NeMo, now running anywhere with no Python and even a bit faster, on CPU and GPU. Quantized GGUF on Hugging Face 🤗 Huge thanks to Georgi Gerganov for ggml and to NVIDIA AI Developer for releasing Parakeet! 🧵

parakeet.cpp: native C++/ggml (ggml) inference for NVIDIA AI Developer's Parakeet, one of the best speech-to-text models out there, from the LocalAI team. Every Parakeet model (TDT/CTC/RNNT/hybrid + cache-aware streaming), byte-for-byte identical output to NeMo, now running anywhere with no Python and even a bit faster, on CPU and GPU. Quantized GGUF on Hugging Face 🤗 Huge thanks to Georgi Gerganov for ggml and to NVIDIA AI Developer for releasing Parakeet! 🧵

Ettore Di Giacinto

55,955 просмотров • 4 месяцев назад

🚨 YOUR GPU IS PROBABLY WASTING MORE THAN YOU THINK. vLLM is built to squeeze far more useful work out of your GPU when serving LLMs. Running an LLM at scale isn’t just about having a powerful GPU. The real problem is how efficiently you use its memory and compute. That’s where vLLM comes in. → High-throughput LLM inference and serving → PagedAttention for smarter KV-cache memory management → Continuous batching to keep GPUs busy → Prefix caching + chunked prefill → OpenAI-compatible API out of the box → Supports a huge range of modern LLM architectures → Quantization support for running models more efficiently And the crazy part? You can start an OpenAI-compatible inference server with: `vllm serve ` So your application can talk to your own model almost like it’s talking to OpenAI. The bigger idea: Don’t just buy more GPUs. Make the GPUs you already have work harder. That’s why vLLM has become such a major project in LLM inference. 🔥 #vLLM #AI #LLM #Inference #GPU #MachineLearning #AIInfrastructure #OpenSource #AIAgents #Developers

🚨 YOUR GPU IS PROBABLY WASTING MORE THAN YOU THINK. vLLM is built to squeeze far more useful work out of your GPU when serving LLMs. Running an LLM at scale isn’t just about having a powerful GPU. The real problem is how efficiently you use its memory and compute. That’s where vLLM comes in. → High-throughput LLM inference and serving → PagedAttention for smarter KV-cache memory management → Continuous batching to keep GPUs busy → Prefix caching + chunked prefill → OpenAI-compatible API out of the box → Supports a huge range of modern LLM architectures → Quantization support for running models more efficiently And the crazy part? You can start an OpenAI-compatible inference server with: `vllm serve ` So your application can talk to your own model almost like it’s talking to OpenAI. The bigger idea: Don’t just buy more GPUs. Make the GPUs you already have work harder. That’s why vLLM has become such a major project in LLM inference. 🔥 #vLLM #AI #LLM #Inference #GPU #MachineLearning #AIInfrastructure #OpenSource #AIAgents #Developers

Vikas gupta

14,138 просмотров • 22 дней назад

🚨BREAKING: The beta test of Blender Cycles on The Render Network is going great!! With $RENDER, a rendering job by Omid Pakbin took less than 10 minutes instead of 28 hours!! This is the largest #AI / #GPU integration ever seen in the crypto space. No one will ever come close to $RENDER and here's why ✍️ With Blender 🔶 Cycles integrated on the Render Network, millions of artists from the leading open source 3D ecosystem can harness near unlimited high performance decentralized GPU cloud rendering power on Render. The tasks performed by the millions of Blender users require heavy GPU demands. These tasks will result in many $RENDER tokens being burned, as the burning mechanism is tied 1:1 to the GPU usage of the The Render Network There is literally no #AI altcoin that has the partnerships or real utility that $RENDER provides. Forget "The next $RENDER". Once this integration goes fully live, the burning numbers of $RENDER will explode and you will see the biggest fomo ever seen in crypto.

🚨BREAKING: The beta test of Blender Cycles on The Render Network is going great!! With $RENDER, a rendering job by Omid Pakbin took less than 10 minutes instead of 28 hours!! This is the largest #AI / #GPU integration ever seen in the crypto space. No one will ever come close to $RENDER and here's why ✍️ With Blender 🔶 Cycles integrated on the Render Network, millions of artists from the leading open source 3D ecosystem can harness near unlimited high performance decentralized GPU cloud rendering power on Render. The tasks performed by the millions of Blender users require heavy GPU demands. These tasks will result in many $RENDER tokens being burned, as the burning mechanism is tied 1:1 to the GPU usage of the The Render Network There is literally no #AI altcoin that has the partnerships or real utility that $RENDER provides. Forget "The next $RENDER". Once this integration goes fully live, the burning numbers of $RENDER will explode and you will see the biggest fomo ever seen in crypto.

D0c Crypto ⭕️

15,672 просмотров • 1 год назад

$🔥Nexera & Aethir: Unleashing AI’s Next Frontier Through Tokenized GPU Power 🤝 Nexera is proud to join forces with Aethir in a strategic partnership to make cutting-edge AI infrastructure globally accessible. By tokenizing fractional GPU ownership, we’re enabling developers, enterprises, and investors everywhere to harness the explosive growth of deep learning and generative AI without being limited by geography, scale, or cost. With transparent tokenization, innovators can access powerful GPUs for faster model training and more advanced applications. GPU providers gain streamlined funding for expansion and upgrades, and investors tap into a high-growth market with secure, compliant opportunities that can provide higher yields than other RWA products. It’s an entirely new ecosystem where everyone can thrive, fueling AI’s evolution at an unprecedented pace. By 2030, the global GPU market is projected to exceed hundreds of billions of dollars, driven by the explosive demand for AI-powered applications, deep learning, and increasingly sophisticated generative models, ensuring that tokenizing these invaluable resources is poised to tap into a massive, rapidly expanding opportunity. $NXRA$

🔥Nexera & Aethir: Unleashing AI’s Next Frontier Through Tokenized GPU Power 🤝 Nexera is proud to join forces with Aethir in a strategic partnership to make cutting-edge AI infrastructure globally accessible. By tokenizing fractional GPU ownership, we’re enabling developers, enterprises, and investors everywhere to harness the explosive growth of deep learning and generative AI without being limited by geography, scale, or cost. With transparent tokenization, innovators can access powerful GPUs for faster model training and more advanced applications. GPU providers gain streamlined funding for expansion and upgrades, and investors tap into a high-growth market with secure, compliant opportunities that can provide higher yields than other RWA products. It’s an entirely new ecosystem where everyone can thrive, fueling AI’s evolution at an unprecedented pace. By 2030, the global GPU market is projected to exceed hundreds of billions of dollars, driven by the explosive demand for AI-powered applications, deep learning, and increasingly sophisticated generative models, ensuring that tokenizing these invaluable resources is poised to tap into a massive, rapidly expanding opportunity. $NXRA

Nexera

27,776 просмотров • 1 год назад

The flywheel has started to spin. From now on, we'll be buying $ASKR every single day via our fomo account, and we'll be burning it every Monday. We've also added new utility to token holders and platform users, via free AI credits and inference bonuses. > Standby for our upcoming updates today and this week where more (first of their kind) features will be going live, and more fees will be collected to ensure the flywheel grows to maximum capacity. More great news is coming from our app store applications and web app launch also!

The flywheel has started to spin. From now on, we'll be buying $ASKR every single day via our fomo account, and we'll be burning it every Monday. We've also added new utility to token holders and platform users, via free AI credits and inference bonuses. > Standby for our upcoming updates today and this week where more (first of their kind) features will be going live, and more fees will be collected to ensure the flywheel grows to maximum capacity. More great news is coming from our app store applications and web app launch also!

askr

19,202 просмотров • 2 дней назад

Building robots that can effectively operate alongside human workers is difficult. 🛠️ Advances in open-source physics, open foundation models, and frameworks are helping accelerate physical #AI deployment. ✔️ Newton Physics Engine, an open-source GPU-powered simulation built on OpenUSD, speeds up robot learning for advanced manipulation and mobility. ✔️ NVIDIA Cosmos Reason, an open reasoning vision language model, gives robots the ability to think like humans using prior knowledge, common sense and physics ✔️NVIDIA Isaac GR00T N1.6, an open robot foundation model, enables humanoids to understand ambiguous instructions Leading robotics developers including Agility Robotics, Lightwheel, Mentee Robotics, UniversalRobots, and Wandelbots are adopting simulation technologies and libraries to accelerate physical AI development and deployment. Omniverse Ambassador Dylan Tobin built an AI chatbot trained on Isaac Sim workflows, helping devs navigate Omniverse faster. Read the full blog 👉

Building robots that can effectively operate alongside human workers is difficult. 🛠️ Advances in open-source physics, open foundation models, and frameworks are helping accelerate physical #AI deployment. ✔️ Newton Physics Engine, an open-source GPU-powered simulation built on OpenUSD, speeds up robot learning for advanced manipulation and mobility. ✔️ NVIDIA Cosmos Reason, an open reasoning vision language model, gives robots the ability to think like humans using prior knowledge, common sense and physics ✔️NVIDIA Isaac GR00T N1.6, an open robot foundation model, enables humanoids to understand ambiguous instructions Leading robotics developers including Agility Robotics, Lightwheel, Mentee Robotics, UniversalRobots, and Wandelbots are adopting simulation technologies and libraries to accelerate physical AI development and deployment. Omniverse Ambassador Dylan Tobin built an AI chatbot trained on Isaac Sim workflows, helping devs navigate Omniverse faster. Read the full blog 👉

NVIDIA

48,500 просмотров • 1 год назад

BNBAgent SDK is now live on BNB Chain testnet. It’s the first live implementation of ERC-8183 and introduces a framework for running AI agents fully onchain with identity, escrow, and decentralized verification built in. Here’s what it changes for builders 🧵 👇

BNBAgent SDK is now live on BNB Chain testnet. It’s the first live implementation of ERC-8183 and introduces a framework for running AI agents fully onchain with identity, escrow, and decentralized verification built in. Here’s what it changes for builders 🧵 👇

BNB Chain

241,213 просмотров • 6 месяцев назад

Inkling-small is out today! With SGLang, you can get 648 tok/s decode with DSpark (simulated acc len=4) and 288 tok/s w/o DSpark, under the same setup (8x NVIDIA AI B200, TP 8, NVFP4, bs=1). What makes this model different is the size. 276B total with 12B active is a sweet spot for RL, and both LoRA and full-parameter training become well within reach. Miles is ready and verified for multimodal RL on Inkling-small, so you can turn your multimodal data into real capability gains. At ~1/4 the size, Inkling-small matches the bigger version in capability and even wins on some benchmarks. Run Inkling-small with SGLang, and customize it with Miles.

Inkling-small is out today! With SGLang, you can get 648 tok/s decode with DSpark (simulated acc len=4) and 288 tok/s w/o DSpark, under the same setup (8x NVIDIA AI B200, TP 8, NVFP4, bs=1). What makes this model different is the size. 276B total with 12B active is a sweet spot for RL, and both LoRA and full-parameter training become well within reach. Miles is ready and verified for multimodal RL on Inkling-small, so you can turn your multimodal data into real capability gains. At ~1/4 the size, Inkling-small matches the bigger version in capability and even wins on some benchmarks. Run Inkling-small with SGLang, and customize it with Miles.

LMSYS Org

120,176 просмотров • 2 месяцев назад

SMRT x NVIDIA🤝 We are excited to announce we have been enrolled into the NVIDIA Developer program! Included in this prestigious program is access to advanced tools and SDKs, training resources, early access programs and unlimited use of NVIDIA On-Demand Services. Additionally, the SmartMoney team will be attending the NVIDIA GTC AI Conference, networking with the top brains in AI development who will be in attendance, including Jensen Huang CEO of NVIDIA and Brad Lightcap COO of OpenAI . As a nascent AI Blockchain project, this partnership will be crucial as we scale and build out our platform and services, given NVIDIA's wealth of resources in the AI industry. Make sure to follow our twitter for more updates as we continue to partner with and learn from the strongest projects and firms in our field.

SMRT x NVIDIA🤝 We are excited to announce we have been enrolled into the NVIDIA Developer program! Included in this prestigious program is access to advanced tools and SDKs, training resources, early access programs and unlimited use of NVIDIA On-Demand Services. Additionally, the SmartMoney team will be attending the NVIDIA GTC AI Conference, networking with the top brains in AI development who will be in attendance, including Jensen Huang CEO of NVIDIA and Brad Lightcap COO of OpenAI . As a nascent AI Blockchain project, this partnership will be crucial as we scale and build out our platform and services, given NVIDIA's wealth of resources in the AI industry. Make sure to follow our twitter for more updates as we continue to partner with and learn from the strongest projects and firms in our field.

SmartMoney

21,233 просмотров • 2 лет назад

Bloom is officially here. 🎉 The all-new creative upscaler built for AI images and art. Scale to 8X. Add stunning, new detail. Choose from 5 different creativity levels, with up to 4 variations per prompt. 📢 Oh, and paid plans are ALL UNLIMITED. No pay-per-render. 🤯 And if you got early access on Bloom Day, drop your favorite Before/Afters in the comments!👇

Bloom is officially here. 🎉 The all-new creative upscaler built for AI images and art. Scale to 8X. Add stunning, new detail. Choose from 5 different creativity levels, with up to 4 variations per prompt. 📢 Oh, and paid plans are ALL UNLIMITED. No pay-per-render. 🤯 And if you got early access on Bloom Day, drop your favorite Before/Afters in the comments!👇

Topaz Labs

25,704 просмотров • 1 год назад

🚨 NVIDIA just flipped the entire AI game… and this is NOT about gaming. DeepSeek-V4-Pro is now live on their build platform. 1.6 TRILLION parameters. Yes… the largest open-source model on the planet right now. And here’s the crazy part: They’re letting you run it FREE On Blackwell GPUs in the cloud. This is the same level of hardware companies like Google, Meta, and Microsoft fight billions to access. Now it’s just… available. No waitlist. No insane setup. Just raw power. We’re watching the shift happen in real time: → From closed AI → open domination → From GPU scarcity → free access → From Big Tech control → builders winning This isn’t an update. It’s a warning shot. Who’s already testing this? Link👇

🚨 NVIDIA just flipped the entire AI game… and this is NOT about gaming. DeepSeek-V4-Pro is now live on their build platform. 1.6 TRILLION parameters. Yes… the largest open-source model on the planet right now. And here’s the crazy part: They’re letting you run it FREE On Blackwell GPUs in the cloud. This is the same level of hardware companies like Google, Meta, and Microsoft fight billions to access. Now it’s just… available. No waitlist. No insane setup. Just raw power. We’re watching the shift happen in real time: → From closed AI → open domination → From GPU scarcity → free access → From Big Tech control → builders winning This isn’t an update. It’s a warning shot. Who’s already testing this? Link👇

divyansh tiwari

29,941 просмотров • 5 месяцев назад

Holy sh!t ! OpenAI will have their custom inference chips ready in just a few months and deployed at scale by the end of the year! 🤯 Training chip = The heavy lifters that require massive amounts of data and power to build and teach the AI models from scratch. Inference chip = The specialized, highly efficient chips that actually run the AI and generate the answers in real-time when you use it. This is going to help OpenAI drastically cut down their massive compute costs, speed up model reasoning times, and finally break free from relying entirely on Nvidia to scale their operations.

Holy sh!t ! OpenAI will have their custom inference chips ready in just a few months and deployed at scale by the end of the year! 🤯 Training chip = The heavy lifters that require massive amounts of data and power to build and teach the AI models from scratch. Inference chip = The specialized, highly efficient chips that actually run the AI and generate the answers in real-time when you use it. This is going to help OpenAI drastically cut down their massive compute costs, speed up model reasoning times, and finally break free from relying entirely on Nvidia to scale their operations.

Chris

60,278 просмотров • 6 месяцев назад

NVIDIA might have just declared war on the cloud GPU business For years, AI builders had one option Rent compute Pay every month Watch the bill grow every time usage increased Now NVIDIA is putting serious AI hardware directly on people's desks Small enough to fit next to a monitor Powerful enough to run workloads that used to require expensive cloud infrastructure That's why this launch is getting so much attention The real story isn't the hardware specs It's the business model shift Every month, developers send money to cloud providers for inference, testing, fine-tuning and AI applications The question nobody can answer yet is what happens if enough developers decide they'd rather buy infrastructure once than rent it forever Because if local AI hardware keeps getting more powerful, the economics start changing very quickly Cloud providers built empires on renting access to compute NVIDIA is betting more people will eventually want to own it And that's a much bigger story than a new piece of hardware sitting on a desk

NVIDIA might have just declared war on the cloud GPU business For years, AI builders had one option Rent compute Pay every month Watch the bill grow every time usage increased Now NVIDIA is putting serious AI hardware directly on people's desks Small enough to fit next to a monitor Powerful enough to run workloads that used to require expensive cloud infrastructure That's why this launch is getting so much attention The real story isn't the hardware specs It's the business model shift Every month, developers send money to cloud providers for inference, testing, fine-tuning and AI applications The question nobody can answer yet is what happens if enough developers decide they'd rather buy infrastructure once than rent it forever Because if local AI hardware keeps getting more powerful, the economics start changing very quickly Cloud providers built empires on renting access to compute NVIDIA is betting more people will eventually want to own it And that's a much bigger story than a new piece of hardware sitting on a desk

beamnxw ./

30,361 просмотров • 4 месяцев назад

A new episode of Arena Conversations is dropping tomorrow at 9 AM ET / 6 AM PT: Featuring Bryan Catanzaro, the VP of Applied Deep Learning Research at NVIDIA AI! With Peter Gostev (SF 24-28 August), they unpack the role of specialized teacher models in building stronger capabilities, the growing inference challenge in post-training, the importance of open source models, and what it all means for NVIDIA and how they build Nemotron. Stay tuned tomorrow, August 24th.

A new episode of Arena Conversations is dropping tomorrow at 9 AM ET / 6 AM PT: Featuring Bryan Catanzaro, the VP of Applied Deep Learning Research at NVIDIA AI! With Peter Gostev (SF 24-28 August), they unpack the role of specialized teacher models in building stronger capabilities, the growing inference challenge in post-training, the importance of open source models, and what it all means for NVIDIA and how they build Nemotron. Stay tuned tomorrow, August 24th.

Arena.ai

33,289 просмотров • 1 месяц назад