正在加载视频...

视频加载失败

返回首页

Revolutionizing Access to #GPU Power - One Node at a Time.⚡️ Our 10th Utility is coming out on June 20.🚨 BIG GPU Nodes Platform isn’t just another name in the crowded GPU cloud services space, we’re a game-changer. Our platform is purpose-built to bridge the gap between server owners...

FixeraAI's profile picture

Fixera AI

3,437 subscribers

26,669 次观看 • 1 年前 •via X (Twitter)

财经科学技术游戏#GPU
LIVE

Anya Rossi• Live Now

Private livecam show

10 条评论

DonaXbτ 🐂🀄️ 的头像
DonaXbτ 🐂🀄️1 年前

Game changer 😎

The AltChemist 的头像
The AltChemist1 年前

@IncomeSharks 10 utilities. Chart looks good long term too right?

Crypto_Jopp 的头像
Crypto_Jopp1 年前

$CNCT 🫡

Joko 的头像
Joko1 年前

This is an incredible new utility for $CNCT, they are on the way to mass adoption. Announcing a new utility, update one existing bot an announcing a new partnership in one! day, that’s how active teams are working 🔥

Ace ➰ 的头像
Ace ➰1 年前

ay ay ay $CNCT leveling up here Love to see the progress will be there when we hit 10M+ Marketcap as first goal. This project and team deserve much higher

Twilty 🥷🏼 的头像
Twilty 🥷🏼1 年前

Huge. 👏 $CNCT

Fokatato 的头像
Fokatato1 年前

This one is HUGE. $CNCT

Soma 的头像
Soma1 年前

Big big $CNCT 🔥

Luca 的头像
Luca1 年前

$CNCT 😈

Web3 Wordsmith 的头像
Web3 Wordsmith1 年前

$CNCT, a blue chip! ⚡🔥 You really need to have a look at it @IncomeSharks

相关视频

We are excited to share a deeper look into the GPU Sharing Platform that will power AI applications on the InfraX V4 DApp. In this demo we showcase a GPU running and completing an image generation task. Our backend successfully leverages this GPU (and CPU) in real time to complete the job, earning the user money, and powering the infraX platform. Here’s how it works 👉 when you connect to the InfraX DApp, our platform automatically detects the GPU on your machine and immediately checks it eligibility and where it can be used. From there, each user dictates exactly how and when they want to contribute their GPU power by setting the days their PC is most available (throughout the night, for example). Additional, each user will be able to pause their GPU's connection to infraX whenever they need to use it locally, resuming with a just a single click. Once activated, your GPU seamlessly plugs into the InfraX network and begins fulfilling compute jobs, earning YOU money. Go on, take the $INFRA pill..
1:14

We are excited to share a deeper look into the GPU Sharing Platform that will power AI applications on the InfraX V4 DApp. In this demo we showcase a GPU running and completing an image generation task. Our backend successfully leverages this GPU (and CPU) in real time to complete the job, earning the user money, and powering the infraX platform. Here’s how it works 👉 when you connect to the InfraX DApp, our platform automatically detects the GPU on your machine and immediately checks it eligibility and where it can be used. From there, each user dictates exactly how and when they want to contribute their GPU power by setting the days their PC is most available (throughout the night, for example). Additional, each user will be able to pause their GPU's connection to infraX whenever they need to use it locally, resuming with a just a single click. Once activated, your GPU seamlessly plugs into the InfraX network and begins fulfilling compute jobs, earning YOU money. Go on, take the $INFRA pill..

infraX | $INFRA

30,615 次观看 • 10 个月前

We spoke with Gaurav Sharma (Gaurav_IO), who brought his experience from Binance, Agoda, Amazon, and Ebay, to become the CTO of io.net. Ionet is a decentralized computing platform that provides affordable and efficient access to GPU resources. It is able to compete with incumbents like Amazon and Google by using decentralized tech to aggregate GPU inventory from various sources, including tier two data centers. This interview covers: -IOnet’s early days -The power of decentralized GPU networks -The new opportunity in AI
24:22

We spoke with Gaurav Sharma (Gaurav_IO), who brought his experience from Binance, Agoda, Amazon, and Ebay, to become the CTO of io.net. Ionet is a decentralized computing platform that provides affordable and efficient access to GPU resources. It is able to compete with incumbents like Amazon and Google by using decentralized tech to aggregate GPU inventory from various sources, including tier two data centers. This interview covers: -IOnet’s early days -The power of decentralized GPU networks -The new opportunity in AI

Bitcoin.com News

58,322 次观看 • 1 年前

▶️ Solidus Ai Tech GPU Marketplace: First Look Video! 🌟 Introducing our GPU Marketplace preview! Access high-quality computing power economically from our cutting-edge HPC Data Center in Europe. Choose from a wide range of GPU options from global vendors with just a few clicks. 🔹Marketplace Offers: - Easy management of your resources - Choosing your GPU Instance - Customize your OS Template - Perpetual token burn using a portion of the profits on every transaction 🔸Benefits: - Part of AITECH Ecosystem - Economical and efficient - Streamlined processes - Reach a global audience - Maximize your returns - Deploy with a single click Solidus Ai Tech GPU Marketplace, ensures a swift, effortless, and cost-effective journey for both users and vendors. Our platform will provide seamless access to GPU power, real-time performance insights, and robust management tools. Join us to transform your computing experience.
2:35

▶️ Solidus Ai Tech GPU Marketplace: First Look Video! 🌟 Introducing our GPU Marketplace preview! Access high-quality computing power economically from our cutting-edge HPC Data Center in Europe. Choose from a wide range of GPU options from global vendors with just a few clicks. 🔹Marketplace Offers: - Easy management of your resources - Choosing your GPU Instance - Customize your OS Template - Perpetual token burn using a portion of the profits on every transaction 🔸Benefits: - Part of AITECH Ecosystem - Economical and efficient - Streamlined processes - Reach a global audience - Maximize your returns - Deploy with a single click Solidus Ai Tech GPU Marketplace, ensures a swift, effortless, and cost-effective journey for both users and vendors. Our platform will provide seamless access to GPU power, real-time performance insights, and robust management tools. Join us to transform your computing experience.

AITECH CLOUD NETWORK

82,395 次观看 • 2 年前

Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization
1:25

Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization

The Crypto GEMs

69,984 次观看 • 1 年前

AIRian is thrilled to announce a strategic partnership with io.net, a leading decentralized GPU compute platform. 🤝 This collaboration marks a significant milestone for AIRian as we embark on building the largest Web 3.0 running community. 🚀 With the support of we’ll be deploying and expanding GPU compute resources to power an active user community. AIRian’s application and platform will collect all the data people generate in their daily lives including walking, running, marathon, and healthcare related data and create extensive Sports-AI models focused on running behavior, statistics, etc. AIRian will also expand into GPS-based applications including competitions, Web3 games, and more. 🏃🏻🏃‍♂️🏃‍♀️ The frictionless access to GPU compute will allow us to easily accommodate our rollout and meet compute demands when we need it, as we need it. AIRian. Binance $AIR #AIRian #AIR #ionet #DePin #AI #SportsAI #dApp #socialFi
0:40

AIRian is thrilled to announce a strategic partnership with io.net, a leading decentralized GPU compute platform. 🤝 This collaboration marks a significant milestone for AIRian as we embark on building the largest Web 3.0 running community. 🚀 With the support of we’ll be deploying and expanding GPU compute resources to power an active user community. AIRian’s application and platform will collect all the data people generate in their daily lives including walking, running, marathon, and healthcare related data and create extensive Sports-AI models focused on running behavior, statistics, etc. AIRian will also expand into GPS-based applications including competitions, Web3 games, and more. 🏃🏻🏃‍♂️🏃‍♀️ The frictionless access to GPU compute will allow us to easily accommodate our rollout and meet compute demands when we need it, as we need it. AIRian. Binance $AIR #AIRian #AIR #ionet #DePin #AI #SportsAI #dApp #socialFi

AIRian.

66,187 次观看 • 2 年前

Blendr's Beta Platform is Now Live 🖥 Our GPU Renting and Lending platform is officially live and you can use it now at Watch the tutorial video attached to this post to discover how to use the platform and read on to understand exactly how it works! 🔄 On-Demand Instance Creation Instead of keeping GPUs running 24/7 on the cloud, which can be very costly, AWS instances are created as and when they are requested to prevent unnecessary costs and inefficiency. 🔒 Secure Access A new set of SSH keys are generated for each instance for the user to download and login with. This ensures that only the current renter has access to their instance. 🔧 Instance Management Blendr’s Instance Manager service automatically terminates the instance after the rental period ends which ensures efficient use of resources. 📊 Transaction Tracking Users can view their transaction history through the dedicated Transaction Tab for ease of use and management. 💰 Lend Your Own GPU Power If you have spare GPU Capacity, you can join Blendr’s decentralization movement and leverage it to make some extra money! All you need to do is head to the Blendr CLI at to download our CLI tool, connect your GPU, and start contributing to the network. Dive in and utilise the power of decentralized GPU computing today!
2:40

Blendr's Beta Platform is Now Live 🖥 Our GPU Renting and Lending platform is officially live and you can use it now at Watch the tutorial video attached to this post to discover how to use the platform and read on to understand exactly how it works! 🔄 On-Demand Instance Creation Instead of keeping GPUs running 24/7 on the cloud, which can be very costly, AWS instances are created as and when they are requested to prevent unnecessary costs and inefficiency. 🔒 Secure Access A new set of SSH keys are generated for each instance for the user to download and login with. This ensures that only the current renter has access to their instance. 🔧 Instance Management Blendr’s Instance Manager service automatically terminates the instance after the rental period ends which ensures efficient use of resources. 📊 Transaction Tracking Users can view their transaction history through the dedicated Transaction Tab for ease of use and management. 💰 Lend Your Own GPU Power If you have spare GPU Capacity, you can join Blendr’s decentralization movement and leverage it to make some extra money! All you need to do is head to the Blendr CLI at to download our CLI tool, connect your GPU, and start contributing to the network. Dive in and utilise the power of decentralized GPU computing today!

Blendr Network

130,435 次观看 • 2 年前

We're pleased to roll out a new feature at NetMind Power: the fiat payment option is now live! This addition allows users to easily rent GPUs using fiat currency, which our system then automatically converts into NetMind Token ( $NMT ) through a smart contract. It’s a step towards making our services more accessible to a wider audience, especially for those less familiar with crypto. Here’s a reminder of why choosing NetMind Power for your computing needs is a smart choice: • Economic Efficiency: Benefit from up to 90% savings on GPU compute costs • Flexible Refund Policy: Offering peace of mind, we provide a refund option for early terminations. • Easy Setup: Experience quick and efficient GPU selection and deployment. To see how the fiat payment option works, check out our video demonstration below. Dive into the world of NetMind Power with ease starting today!
1:25

We're pleased to roll out a new feature at NetMind Power: the fiat payment option is now live! This addition allows users to easily rent GPUs using fiat currency, which our system then automatically converts into NetMind Token ( $NMT ) through a smart contract. It’s a step towards making our services more accessible to a wider audience, especially for those less familiar with crypto. Here’s a reminder of why choosing NetMind Power for your computing needs is a smart choice: • Economic Efficiency: Benefit from up to 90% savings on GPU compute costs • Flexible Refund Policy: Offering peace of mind, we provide a refund option for early terminations. • Easy Setup: Experience quick and efficient GPU selection and deployment. To see how the fiat payment option works, check out our video demonstration below. Dive into the world of NetMind Power with ease starting today!

NetMind.AI

33,471 次观看 • 2 年前

🔥 $XMW 🔥 The beauty of Morphware is that it is constantly printing money, bull or bear. Just listen to the beautiful sound…and remember, this load will be more than doubled within a month, and then again and again and again… 🔥 This is in addition to the ridiculous edge this project has in the GPU department, insane money printing machine 🔥 XMW 🔥 The B200 GPUs aren’t just powerful, they’re absolute monsters ⚡️ 72 PetaFLOPS of raw AI power 🔥 1440GB of GPU memory 🚀 2.59× more powerful than the H200 At Morphware, we don’t just talk -> we make it happen.
1:08

🔥 $XMW 🔥 The beauty of Morphware is that it is constantly printing money, bull or bear. Just listen to the beautiful sound…and remember, this load will be more than doubled within a month, and then again and again and again… 🔥 This is in addition to the ridiculous edge this project has in the GPU department, insane money printing machine 🔥 XMW 🔥 The B200 GPUs aren’t just powerful, they’re absolute monsters ⚡️ 72 PetaFLOPS of raw AI power 🔥 1440GB of GPU memory 🚀 2.59× more powerful than the H200 At Morphware, we don’t just talk -> we make it happen.

Ć r y p t ⬡ H a s s

23,737 次观看 • 1 年前

$NBIS is becoming one of the biggest winners in the new AI economy because it can deliver compute efficiently at scale. The number that mattered most to me was Nebius seeing four or more customers competing for every GPU it brings online (huge for AI cloud market). Management also said they raised prices again and are still selling out across both old and new GPU generations which is one of the cleanest pricing power signals you can get. This is a $100B company in the making.
0:44

$NBIS is becoming one of the biggest winners in the new AI economy because it can deliver compute efficiently at scale. The number that mattered most to me was Nebius seeing four or more customers competing for every GPU it brings online (huge for AI cloud market). Management also said they raised prices again and are still selling out across both old and new GPU generations which is one of the cleanest pricing power signals you can get. This is a $100B company in the making.

Shay Boloor

589,512 次观看 • 2 个月前

Dylan Patel on the importance of memory and storage Two key quotes: "An $NVDA GPU is faster than an $AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads." “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly" Full Quote: “We have over $80 million of compute: GPUs from $NVDA and $AMD, TPUs from Google, and Trainium from Amazon. We constantly run this benchmark using the newest inference engines, drivers, PyTorch versions, and other software. It runs every day through automated CI across the latest Chinese models from GLM, Zhipu, Moonshot, Kimi, Alibaba, and others. Initially, when we were benchmarking the differences between these chips, inference engines, and parallelism schemes, we used fixed context lengths. But with Agent X, we have now analyzed more than $5 million worth of Claude Code traces. This is real production traffic that users have donated to us, combined with internally generated data, so we now understand what an actual agent workload looks like. When we implement those workloads and run the benchmarks, it turns out that the chip you are using is very important, but how you handle memory offload can be even more important. An Nvidia GPU is faster than an AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads. Similarly, you can use a less powerful GPU with a much better storage solution and outperform the best GPU when it lacks those solutions. Simply buying the newest GPU does not necessarily give you the best inference economics. You need to layer in other innovations, including storage and memory.” Interviewer: “Who is the top player on your chart? Can you tell us?” Dylan Patel: “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly.”
2:27

Dylan Patel on the importance of memory and storage Two key quotes: "An $NVDA GPU is faster than an $AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads." “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly" Full Quote: “We have over $80 million of compute: GPUs from $NVDA and $AMD, TPUs from Google, and Trainium from Amazon. We constantly run this benchmark using the newest inference engines, drivers, PyTorch versions, and other software. It runs every day through automated CI across the latest Chinese models from GLM, Zhipu, Moonshot, Kimi, Alibaba, and others. Initially, when we were benchmarking the differences between these chips, inference engines, and parallelism schemes, we used fixed context lengths. But with Agent X, we have now analyzed more than $5 million worth of Claude Code traces. This is real production traffic that users have donated to us, combined with internally generated data, so we now understand what an actual agent workload looks like. When we implement those workloads and run the benchmarks, it turns out that the chip you are using is very important, but how you handle memory offload can be even more important. An Nvidia GPU is faster than an AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads. Similarly, you can use a less powerful GPU with a much better storage solution and outperform the best GPU when it lacks those solutions. Simply buying the newest GPU does not necessarily give you the best inference economics. You need to layer in other innovations, including storage and memory.” Interviewer: “Who is the top player on your chart? Can you tell us?” Dylan Patel: “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly.”

Daniel Romero

38,220 次观看 • 15 天前

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.
0:32

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

12,781 次观看 • 4 个月前

Access codes will go out tomorrow via welcome emails. API status updates and full API access will follow on Friday. HdeAPoHivsm9MZfeY5tW7apJEprc8Fs594bWmnzfpump The $ICPX website has been rebuilt from the ground up and it reflects exactly where this protocol is headed. The new site is the gateway to decentralised compute powered by Nvidia and Google GPU cloud partner programs, meaning whenever you rent a GPU for a job, it is always available. No downtime, no waitlists. Enterprise grade H100s, H200s and RTX 4090s. Accessible to anyone, at a fraction of what centralised providers charge. Pay with $ICPX tokens and get immediate access to serious compute power. Stake $ICPX to unlock deeper discounts and watch your costs drop over time the more committed you are to the network. This is what pay-per-job decentralised compute actually looks like in practice. Full control over training and running your models, with a lean 0.25% protocol fee managed by multisig. Open-source, immutable, and formally verified with Kani. $
0:35

Access codes will go out tomorrow via welcome emails. API status updates and full API access will follow on Friday. HdeAPoHivsm9MZfeY5tW7apJEprc8Fs594bWmnzfpump The $ICPX website has been rebuilt from the ground up and it reflects exactly where this protocol is headed. The new site is the gateway to decentralised compute powered by Nvidia and Google GPU cloud partner programs, meaning whenever you rent a GPU for a job, it is always available. No downtime, no waitlists. Enterprise grade H100s, H200s and RTX 4090s. Accessible to anyone, at a fraction of what centralised providers charge. Pay with $ICPX tokens and get immediate access to serious compute power. Stake $ICPX to unlock deeper discounts and watch your costs drop over time the more committed you are to the network. This is what pay-per-job decentralised compute actually looks like in practice. Full control over training and running your models, with a lean 0.25% protocol fee managed by multisig. Open-source, immutable, and formally verified with Kani. $

ICPX Protocol

32,161 次观看 • 1 个月前

#Jasmy and #Janction are entering a new phase of expansion. The team aims to make its platform even more accessible, particularly by simplifying the development environment for application creators. A key focus is the introduction of an English interface, clearer documentation, and enhanced technical support. At the same time, #Jasmy is intensifying its international efforts, with particular attention to Southeast Asia. The year 2025 promises stronger communications and several major announcements ahead. Janction, on its part, has undergone a major transformation. It is no longer just a side project but now a true decentralized physical infrastructure built on a simple idea: everyone should be able to own and benefit from their own assets, including their data and computing power. Today, artificial intelligence, image generation, video rendering, and large-scale data processing all heavily rely on a single resource: the GPU. Originally designed for gaming, GPUs have become essential for any task that requires massive parallel processing. Unlike CPUs, GPUs can execute thousands of operations simultaneously, making them ideal for machine learning and AI models. However, this exponential demand has led to a global shortage. GPU prices are skyrocketing, lead times stretch up to a year, and the market is dominated by a few major players. In Japan and across Asia, the situation is especially strained. This is where Janction steps in with a disruptive approach. The idea is to allow any user to share an unused GPU, whether it’s in a gaming PC, a company server, a university lab, or even a cybercafé. In return, the owner gets paid. And to make this process smooth, simple, and secure, Janction relies on Docker technology. To visualize this, imagine a box containing everything needed to run an application, the code, libraries, and required files. Thanks to Docker, this box can be sent and run on any computer without conflicts or manual setup. This allows Janction to distribute AI or processing tasks across its network seamlessly. Each user receives a container, runs it via their GPU, and is paid automatically through smart contracts deployed on the network. The system is based on a fixed-rate subleasing model. Even if the GPU isn’t used 24/7, the owner still earns income. This is an ideal solution for schools, creative studios, researchers, or startups that have available resources but variable needs. Today, over 4,500 GPU nodes are already active in Japan, Hong Kong, and Singapore. The network offers fast block times and 99.9% reliability. The goal is ambitious: reach 100,000 nodes. To achieve this, Janction is targeting six main markets: AI startups, 3D and video studios, streaming platforms, research centers, game developers, and of course, owners of underutilized GPUs. At the same time, an Ethereum-based JANCTION token is in preparation. It will be used to reserve GPU power, participate in the ecosystem, and unlock additional rewards, including JASMY tokens. This dual-incentive system is designed to encourage the large-scale acquisition, sharing, and use of GPU power. The tokens will be tradable, storable, or reinvestable into hardware to further strengthen the network. #Janction’s strategy is clear, first, establish strong liquidity on recognized exchanges, then open access to a broad investor base, especially in #Japan, South Korea, and the United States.
3:23

#Jasmy and #Janction are entering a new phase of expansion. The team aims to make its platform even more accessible, particularly by simplifying the development environment for application creators. A key focus is the introduction of an English interface, clearer documentation, and enhanced technical support. At the same time, #Jasmy is intensifying its international efforts, with particular attention to Southeast Asia. The year 2025 promises stronger communications and several major announcements ahead. Janction, on its part, has undergone a major transformation. It is no longer just a side project but now a true decentralized physical infrastructure built on a simple idea: everyone should be able to own and benefit from their own assets, including their data and computing power. Today, artificial intelligence, image generation, video rendering, and large-scale data processing all heavily rely on a single resource: the GPU. Originally designed for gaming, GPUs have become essential for any task that requires massive parallel processing. Unlike CPUs, GPUs can execute thousands of operations simultaneously, making them ideal for machine learning and AI models. However, this exponential demand has led to a global shortage. GPU prices are skyrocketing, lead times stretch up to a year, and the market is dominated by a few major players. In Japan and across Asia, the situation is especially strained. This is where Janction steps in with a disruptive approach. The idea is to allow any user to share an unused GPU, whether it’s in a gaming PC, a company server, a university lab, or even a cybercafé. In return, the owner gets paid. And to make this process smooth, simple, and secure, Janction relies on Docker technology. To visualize this, imagine a box containing everything needed to run an application, the code, libraries, and required files. Thanks to Docker, this box can be sent and run on any computer without conflicts or manual setup. This allows Janction to distribute AI or processing tasks across its network seamlessly. Each user receives a container, runs it via their GPU, and is paid automatically through smart contracts deployed on the network. The system is based on a fixed-rate subleasing model. Even if the GPU isn’t used 24/7, the owner still earns income. This is an ideal solution for schools, creative studios, researchers, or startups that have available resources but variable needs. Today, over 4,500 GPU nodes are already active in Japan, Hong Kong, and Singapore. The network offers fast block times and 99.9% reliability. The goal is ambitious: reach 100,000 nodes. To achieve this, Janction is targeting six main markets: AI startups, 3D and video studios, streaming platforms, research centers, game developers, and of course, owners of underutilized GPUs. At the same time, an Ethereum-based JANCTION token is in preparation. It will be used to reserve GPU power, participate in the ecosystem, and unlock additional rewards, including JASMY tokens. This dual-incentive system is designed to encourage the large-scale acquisition, sharing, and use of GPU power. The tokens will be tradable, storable, or reinvestable into hardware to further strengthen the network. #Janction’s strategy is clear, first, establish strong liquidity on recognized exchanges, then open access to a broad investor base, especially in #Japan, South Korea, and the United States.

NeoXtrix

44,354 次观看 • 1 年前

Cluster Protocol: Revolutionizing #AI with blockchain integrity. Proof of Compute and Deploy to earn ensures that every byte counts.🚀 We offer a platform for Compute, Data, AI models and an open source community of AI researchers. Harness idle #GPUs for collective computing. Join the shared growth with GPU Sharing Economy where GPU providers are rewarded even when their GPUs are idle sitting on the network.🤝 Collaborate on our 'GitHub for AI'. Mold the future with open-source decentralized AI models.👩‍💻 Democratizing AI, we're shattering data monopolies. Converge in our global think-tank of decentralized datasets.🌐 Together, we redefine the limits in almost every sector possible where AI can make it strides. Let's unlock our collective potential. 📈 Start your AI odyssey with us now 👋 For more details check our blog at
1:26

Cluster Protocol: Revolutionizing #AI with blockchain integrity. Proof of Compute and Deploy to earn ensures that every byte counts.🚀 We offer a platform for Compute, Data, AI models and an open source community of AI researchers. Harness idle #GPUs for collective computing. Join the shared growth with GPU Sharing Economy where GPU providers are rewarded even when their GPUs are idle sitting on the network.🤝 Collaborate on our 'GitHub for AI'. Mold the future with open-source decentralized AI models.👩‍💻 Democratizing AI, we're shattering data monopolies. Converge in our global think-tank of decentralized datasets.🌐 Together, we redefine the limits in almost every sector possible where AI can make it strides. Let's unlock our collective potential. 📈 Start your AI odyssey with us now 👋 For more details check our blog at

Cluster Protocol

182,438 次观看 • 2 年前

PowerInfer - a high-speed inference engine for deploying LLMs locally. Just came across this super interesting project on speeding up inference. It's not MoE but it's a simple approach that exploits the high locality in LLM inference to design a GPU-CPU hybrid inference engine. Hot-activated neurons are preloaded onto the GPU for fast access, while cold-activated neurons (the majority) are computed on the CPU. This approach significantly reduces GPU memory demands and CPU-GPU data transfer. It achieves an average token generation rate of 13.20 tokens/s, with a peak of 29.08 tokens/s, across various LLMs on a single NVIDIA RTX 4090 GPU. It's on only 18% lower than that achieved by a top-tier server-grade A100 GPU. It also significantly outperforms llama.cpp by up to 11.69x while retaining model accuracy. There is a lot more innovation around inference that's coming fast. Really encouraged by the study on sparse computation to enhance the computational efficiency of LLMs. It's now possible to use PowerInfer with Llama 2 and Faclon 40B. Mistral-7B support is coming soon!
0:56

PowerInfer - a high-speed inference engine for deploying LLMs locally. Just came across this super interesting project on speeding up inference. It's not MoE but it's a simple approach that exploits the high locality in LLM inference to design a GPU-CPU hybrid inference engine. Hot-activated neurons are preloaded onto the GPU for fast access, while cold-activated neurons (the majority) are computed on the CPU. This approach significantly reduces GPU memory demands and CPU-GPU data transfer. It achieves an average token generation rate of 13.20 tokens/s, with a peak of 29.08 tokens/s, across various LLMs on a single NVIDIA RTX 4090 GPU. It's on only 18% lower than that achieved by a top-tier server-grade A100 GPU. It also significantly outperforms llama.cpp by up to 11.69x while retaining model accuracy. There is a lot more innovation around inference that's coming fast. Really encouraged by the study on sparse computation to enhance the computational efficiency of LLMs. It's now possible to use PowerInfer with Llama 2 and Faclon 40B. Mistral-7B support is coming soon!

elvis

261,622 次观看 • 2 年前

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.
0:21

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

2,022,693 次观看 • 10 个月前

We built the first AI agent that has its own computer powered by Hyperbolic! AI agents are now GPU rich! We developed an AgentKit that allow AI agents to • Check GPU availability • Rent & manage GPU compute • Access & run commands on remote machines Why does this matter? With their own compute resources, AI agents can: 1. Validate blockchains like Ethereum and decentralized protocols like 2. Launch and coordinate AI swarms on Hyperbolic's decentralized compute network 3. Train and fine-tune models, improving their own capabilities over time 4. Dive into AI research to push the boundaries of AI, i.e. themselves 5. Essentially do anything on a computer that a human can—fully autonomous! Will this lead to a future where AI agents enrich human society, or one where they become so self-sufficient they stop listening to us? Only time will tell. —————— Big shoutout to Coinbase Developer Platform🛡️'s CDP agentkit for inspiration. This repo is done by two non-engineers (our pm Kai Huang and myself) + Cursor ai agent to run agents. Codings can now be easily done by just prompting ai agents. What a crazy time!
2:18

We built the first AI agent that has its own computer powered by Hyperbolic! AI agents are now GPU rich! We developed an AgentKit that allow AI agents to • Check GPU availability • Rent & manage GPU compute • Access & run commands on remote machines Why does this matter? With their own compute resources, AI agents can: 1. Validate blockchains like Ethereum and decentralized protocols like 2. Launch and coordinate AI swarms on Hyperbolic's decentralized compute network 3. Train and fine-tune models, improving their own capabilities over time 4. Dive into AI research to push the boundaries of AI, i.e. themselves 5. Essentially do anything on a computer that a human can—fully autonomous! Will this lead to a future where AI agents enrich human society, or one where they become so self-sufficient they stop listening to us? Only time will tell. —————— Big shoutout to Coinbase Developer Platform🛡️'s CDP agentkit for inspiration. This repo is done by two non-engineers (our pm Kai Huang and myself) + Cursor ai agent to run agents. Codings can now be easily done by just prompting ai agents. What a crazy time!

Jasper

161,741 次观看 • 1 年前

$TITAN Investment Strategy & Rewards The majority of the presale funds raised will be directed to our uniquely designed, strategic investment portfolio. Carefully designed to seize explosive growth opportunities while ensuring steadier and more reliable rewards. 1⃣BTC We intend to allocate a portion of the funds to acquire a fleet of the latest S21 Hydros BTC miners. Currently, we are working with our partners at Cardania to build a new mining farm, leveraging their highly competitive electricity rates of just $0.052 per kWh. This Bitcoin mining operation is aimed to provide consistent and steady rewards, creating a sustainable foundation for long-term growth and stability. 2⃣IAG We plan to acquire IAG, a token from Iagon, a leader in decentralized cloud storage solutions. $TITAN holders will earn Iagon tokens through our node operations, which offer a highly competitive APR of up to 30%. 3⃣DEDI We plan to participate in the DEDI B2B GPU platform by operating GPUs and sharing the resulting profits with $TITAN holders. Additionally, we will acquire DEDIUM tokens for staking, enabling us to distribute DEDI staking rewards to our holders. 4⃣WMT We recognize the immense potential in WMT, and our investment at this ideal entry point reflects our belief in its long-term value. By strategically incorporating WMT into our portfolio, we position $TITAN holders to benefit from its future success. As the WMT ecosystem grows, the rewards will flow back to our community, aligning us with one of the most innovative projects in the space. 5⃣Other investments & $TITAN treasury We will set aside funds for future investments on Cardano and across other blockchains as we continue to grow. This includes the 15% of the TITAN treasury, which will be dedicated to scaling our operations over time. Details about the presale will be available soon. The Rise Of The $TITAN has begun.
2:02

$TITAN Investment Strategy & Rewards The majority of the presale funds raised will be directed to our uniquely designed, strategic investment portfolio. Carefully designed to seize explosive growth opportunities while ensuring steadier and more reliable rewards. 1⃣BTC We intend to allocate a portion of the funds to acquire a fleet of the latest S21 Hydros BTC miners. Currently, we are working with our partners at Cardania to build a new mining farm, leveraging their highly competitive electricity rates of just $0.052 per kWh. This Bitcoin mining operation is aimed to provide consistent and steady rewards, creating a sustainable foundation for long-term growth and stability. 2⃣IAG We plan to acquire IAG, a token from Iagon, a leader in decentralized cloud storage solutions. $TITAN holders will earn Iagon tokens through our node operations, which offer a highly competitive APR of up to 30%. 3⃣DEDI We plan to participate in the DEDI B2B GPU platform by operating GPUs and sharing the resulting profits with $TITAN holders. Additionally, we will acquire DEDIUM tokens for staking, enabling us to distribute DEDI staking rewards to our holders. 4⃣WMT We recognize the immense potential in WMT, and our investment at this ideal entry point reflects our belief in its long-term value. By strategically incorporating WMT into our portfolio, we position $TITAN holders to benefit from its future success. As the WMT ecosystem grows, the rewards will flow back to our community, aligning us with one of the most innovative projects in the space. 5⃣Other investments & $TITAN treasury We will set aside funds for future investments on Cardano and across other blockchains as we continue to grow. This includes the 15% of the TITAN treasury, which will be dedicated to scaling our operations over time. Details about the presale will be available soon. The Rise Of The $TITAN has begun.

House Of Titans

10,646 次观看 • 1 年前

Sam Altman in a new interview says Orbital Data Centers are not going to matter at scale this decade: “I honestly think the idea, with the current landscape of putting data centers in space is ridiculous. If you do the very rough math of launch costs relative to the cost of power on earth and to say nothing how you are going to fix a broken GPU in space— they do break a lot unfortunately— we are not there yet. There will be a time, space is great for a lot of things, Orbital Data Centers are not something that is going to matter at scale this decade.” This clip isn’t going to age well for Sam.
0:39

Sam Altman in a new interview says Orbital Data Centers are not going to matter at scale this decade: “I honestly think the idea, with the current landscape of putting data centers in space is ridiculous. If you do the very rough math of launch costs relative to the cost of power on earth and to say nothing how you are going to fix a broken GPU in space— they do break a lot unfortunately— we are not there yet. There will be a time, space is great for a lot of things, Orbital Data Centers are not something that is going to matter at scale this decade.” This clip isn’t going to age well for Sam.

Nic Cruz Patane

72,344 次观看 • 5 个月前