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Gradient goes beyond static content, utilizing idle compute resources from edge devices, personal computers, and local servers to perform real-time processing tasks. The thesis is similar to Pipe’s: operations like AI inference or serverless functions can happen closer to the user, reducing latency. Gradient reported surpassing 20,000 connected nodes... show more

Solana

3,993,743 subscribers

326,604 次观看 • 1 年前 •via X (Twitter)

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Solana1 年前

Delivering content quickly from servers to end users is crucial for apps and services, whether it's static files like images or dynamic data like AI responses. Slow delivery can ruin user experience—think buffering videos or lagging web pages. Solana-based DePIN networks @pipenetwork and @Gradient_HQ incentivize users to contribute excess storage and compute power, respectively. By leveraging a larger network of nodes and tapping into existing infrastructure, they can potentially offer faster delivery, lower costs, and greater reliability.

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Solana1 年前

Pipe Network is a decentralized content delivery network (dCDN). Traditional CDNs cache content (for e.g., images, videos, and webpages) across distributed servers. When users request content, it’s delivered by the closest server, reducing latency compared to an origin server. @pipenetwork takes this design further by incentivizing people to contribute their excess storage and bandwidth. The thesis is simple: more nodes = higher chance a node is closer to the user = faster delivery. The development team behind Pipe recently announced a $10 million raise led by @multicoincap, with plans to launch mainnet in 2025. Learn more from @DavidRhodus' product keynote at Breakpoint:

Solana 的头像

Solana1 年前

What Solana DePIN projects are you excited about? If you’re curious about the broader landscape beyond content delivery DePIN, check out @yashhsm’s report: plus @Syndica_io’s recently released Aug 2024 Solana DePIN Deep Dive

⚡ rift 🐐 🛡💚🌙꧁IP꧂ 的头像

⚡ rift 🐐 🛡💚🌙꧁IP꧂1 年前

Bullish on @Gradient_HQ — The open layer for edge compute on Solana. Set up your #GradientSentry Node and be part of the future. " DePin Is The Future " #GradientNetwork #Solana #DePIN

XRP_Cro 🔥 AI / Gaming / DePIN 的头像

XRP_Cro 🔥 AI / Gaming / DePIN1 年前

💵Earn passive income with Gradient Network - The open layer for edge compute on @Solana ✅ Backed by top tier VCs: @SolanaFndn, @multicoincap, @PanteraCapital and @sequoia Sign up here: 👉 Stay online for 72 hours of uptime to earn #DePIN $GRASS

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MarmZzz1 年前

10% Bonus use this ref link

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Kaorychang1 年前

@Gradient_HQ

Joy Osaretin. (Ø,G) 的头像

Joy Osaretin. (Ø,G)1 年前

@Gradient_HQ What are u waiting for UZOM1Z

crypto mania ❤❤❤ 的头像

crypto mania ❤❤❤1 年前

@Gradient_HQ Use my CODE: BQH3RJ

artemis || 🌳 的头像

artemis || 🌳1 年前

🚀Join me on @Gradient_HQ — The open layer for edge compute on Solana. Set up your #GradientSentry Node and be part of the future. #GradientNetwork

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cromatoforo1 年前

Use code 𝗡𝗦𝗤𝗧𝗜𝟴 for extra awesomeness

相关视频

Started with 100 users. Now Gradient runs on 1M+ nodes across 190 countries. is building the open compute layer AI needs — using the devices we already have. This is DePIN on Solana.

Started with 100 users. Now Gradient runs on 1M+ nodes across 190 countries. is building the open compute layer AI needs — using the devices we already have. This is DePIN on Solana.

Solana

971,481 次观看 • 1 年前

Meet Gradient — turning everyday devices into a decentralized global network that powers faster streaming, content delivery, and compute 🛜

Meet Gradient — turning everyday devices into a decentralized global network that powers faster streaming, content delivery, and compute 🛜

Solana

229,346 次观看 • 1 年前

Blockchains should be accessible, fast, and frictionless. Hear from the co-founders of Orca 🌊, Yutaro Mori & Ori | cofounder of @orca_so, about how Solana’s low latency and high throughput enables them to focus on building their product 🐋 #OnlyPossibleOnSolana

Blockchains should be accessible, fast, and frictionless. Hear from the co-founders of Orca 🌊, Yutaro Mori & Ori | cofounder of @orca_so, about how Solana’s low latency and high throughput enables them to focus on building their product 🐋 #OnlyPossibleOnSolana

Solana

72,803 次观看 • 2 年前

SoloHost Emerges to Improve Pi's Private AI & Distributed Computing Future On Pi2Day 2026, Pi Network unveiled SoloHost in its Beta phase on Desktop, giving developers an open, permissionless way to publish self-hosted apps and Node utilities. Pioneers can now install local AI agents on their own computers. What's more, all data and processing stay on-device for maximum privacy, without cloud sharing. With 420,000+ Pi Nodes, SoloHost also unlocks distributed computing. Nodes can soon contribute spare power to AI tasks and earn Pi, while developers can easily reach millions of Pioneers. By removing complex setup barriers, SoloHost transforms Pi Nodes from blockchain infrastructure into practical tools for privacy-first AI and real compute utility.

SoloHost Emerges to Improve Pi's Private AI & Distributed Computing Future On Pi2Day 2026, Pi Network unveiled SoloHost in its Beta phase on Desktop, giving developers an open, permissionless way to publish self-hosted apps and Node utilities. Pioneers can now install local AI agents on their own computers. What's more, all data and processing stay on-device for maximum privacy, without cloud sharing. With 420,000+ Pi Nodes, SoloHost also unlocks distributed computing. Nodes can soon contribute spare power to AI tasks and earn Pi, while developers can easily reach millions of Pioneers. By removing complex setup barriers, SoloHost transforms Pi Nodes from blockchain infrastructure into practical tools for privacy-first AI and real compute utility.

BSCN

31,693 次观看 • 16 天前

The Gemini Solana Credit Card is here. Earn SOL back on every fiat dollar you spend — and automatically stake your rewards. The physical card is 16 grams of matte metal shimmering with Solana's gradient, available as a limited edition. 👇

The Gemini Solana Credit Card is here. Earn SOL back on every fiat dollar you spend — and automatically stake your rewards. The physical card is 16 grams of matte metal shimmering with Solana's gradient, available as a limited edition. 👇

Solana

458,202 次观看 • 9 个月前

🌟 Another Epic Sneak Peek: OptimAI Core Node’s Edge AI Computing Power! We’re excited to continue unveiling the upcoming OptimAI Core Node features! This time, we’re introducing Edge AI Computing, a game-changing feature that will make your devices even more powerful in contributing to the OptimAI Network. 🔥 What is Edge AI Computing? With the OptimAI Core Node, your device’s idle computing resources (CPU/GPU) and storage will be put to work, powering critical AI computing tasks, including: 🔸Edge Inference: Running real-time AI predictions directly on your device without sending data to centralized servers. 🔸Hot LLM Models: Accelerating large language models for high-speed NLP tasks. 🔸Generative AI Models and More: Contributing to the training and inference of cutting-edge generative AI, like text-to-image models, deep learning, and more. More Contributions, Bigger Rewards Await! This Edge AI Computing feature allows us to leverage the full potential of decentralized computing power, reducing latency, increasing efficiency, and making AI more accessible. The more you contribute, the bigger the rewards!🔥 Stay in the Loop—Start Today with OptimAI Lite Node! While the OptimAI Core Node is still in the works, you don’t have to wait to join the action. The more you contribute, the greater the rewards! Let’s build a stronger, smarter, and more decentralized AI network together. Stay tuned for more exciting updates! 🔸Extension Node: 🔸Telegram Node: 🔸Register at: #DePIN

🌟 Another Epic Sneak Peek: OptimAI Core Node’s Edge AI Computing Power! We’re excited to continue unveiling the upcoming OptimAI Core Node features! This time, we’re introducing Edge AI Computing, a game-changing feature that will make your devices even more powerful in contributing to the OptimAI Network. 🔥 What is Edge AI Computing? With the OptimAI Core Node, your device’s idle computing resources (CPU/GPU) and storage will be put to work, powering critical AI computing tasks, including: 🔸Edge Inference: Running real-time AI predictions directly on your device without sending data to centralized servers. 🔸Hot LLM Models: Accelerating large language models for high-speed NLP tasks. 🔸Generative AI Models and More: Contributing to the training and inference of cutting-edge generative AI, like text-to-image models, deep learning, and more. More Contributions, Bigger Rewards Await! This Edge AI Computing feature allows us to leverage the full potential of decentralized computing power, reducing latency, increasing efficiency, and making AI more accessible. The more you contribute, the bigger the rewards!🔥 Stay in the Loop—Start Today with OptimAI Lite Node! While the OptimAI Core Node is still in the works, you don’t have to wait to join the action. The more you contribute, the greater the rewards! Let’s build a stronger, smarter, and more decentralized AI network together. Stay tuned for more exciting updates! 🔸Extension Node: 🔸Telegram Node: 🔸Register at: #DePIN

OptimAI Network

44,249 次观看 • 1 年前

When we first met Tom, his obsession with energy markets came through immediately. Seemed random, but it's "actually" central to what he's building at Actual Computer. The thesis is that local inference is inevitable. Open source models are getting good enough, people don't want to feed their thoughts to AI labs, and demand for compute will continue to be insatiable. But the main forcing function is that chips aren't the bottleneck anymore - power is. Compute is derivative of energy, and the massive data center buildout has created an energy shortage where GPUs sit idle waiting for power to come online. Yet one place that already has power, and always will, is everywhere else. Homes. Businesses. Universities. Collectively, they have more compute than all the data centers combined. Tom Lynch goal is to build a distributed network of people plugging in their local compute (devices like Mac minis to consumer Nvidia cards) to serve inference demand. The substrate he's chosen is Bittensor, on Subnet 95. Actual Computer has an exceptional team behind it, and this is one of the projects that's gotten me most excited in a long time. Enjoy this conversation with the two of us!

When we first met Tom, his obsession with energy markets came through immediately. Seemed random, but it's "actually" central to what he's building at Actual Computer. The thesis is that local inference is inevitable. Open source models are getting good enough, people don't want to feed their thoughts to AI labs, and demand for compute will continue to be insatiable. But the main forcing function is that chips aren't the bottleneck anymore - power is. Compute is derivative of energy, and the massive data center buildout has created an energy shortage where GPUs sit idle waiting for power to come online. Yet one place that already has power, and always will, is everywhere else. Homes. Businesses. Universities. Collectively, they have more compute than all the data centers combined. Tom Lynch goal is to build a distributed network of people plugging in their local compute (devices like Mac minis to consumer Nvidia cards) to serve inference demand. The substrate he's chosen is Bittensor, on Subnet 95. Actual Computer has an exceptional team behind it, and this is one of the projects that's gotten me most excited in a long time. Enjoy this conversation with the two of us!

Sami Kassab

35,706 次观看 • 5 个月前

Sub-agents in (latent) space! We’ve been working on a side project. As far as I know, this is the first massively multiplayer, completely LLM-driven game. Come play Gradient Bang with us. See if you can catch me on the leaderboard. This whole thing started because I wanted to explore a bunch of things I’m currently obsessed with, in an application of non-trivial size, that felt both new and old at the same time. So … a retro-style space trading game built entirely around interacting with and managing multiple LLMs. Factorio, but instead of clicking, you cajole your ship AI into tasking other AIs to do things for you. Some of the things we’ve been thinking about as we hack on Gradient Bang: - Sub-agent orchestration - Partial context sharing between multiple LLM inference loops - Managing very long contexts, and episodic memory across user sessions - World events and large volumes of structured data input as part of human/agent conversations - Dynamic user interfaces, driven/created on the fly by LLMs - And, of course, voice as primary input If you’ve been building coding harnesses, or writing Open Claw agents, or doing pretty much anything that pushes the boundaries of AI-native development these days, you’re probably thinking about these things too! This is all built with Pipecat AI, the back end is Supabase, the React front end is deployed to Vercel, and all the code is open source.

Sub-agents in (latent) space! We’ve been working on a side project. As far as I know, this is the first massively multiplayer, completely LLM-driven game. Come play Gradient Bang with us. See if you can catch me on the leaderboard. This whole thing started because I wanted to explore a bunch of things I’m currently obsessed with, in an application of non-trivial size, that felt both new and old at the same time. So … a retro-style space trading game built entirely around interacting with and managing multiple LLMs. Factorio, but instead of clicking, you cajole your ship AI into tasking other AIs to do things for you. Some of the things we’ve been thinking about as we hack on Gradient Bang: - Sub-agent orchestration - Partial context sharing between multiple LLM inference loops - Managing very long contexts, and episodic memory across user sessions - World events and large volumes of structured data input as part of human/agent conversations - Dynamic user interfaces, driven/created on the fly by LLMs - And, of course, voice as primary input If you’ve been building coding harnesses, or writing Open Claw agents, or doing pretty much anything that pushes the boundaries of AI-native development these days, you’re probably thinking about these things too! This is all built with Pipecat AI, the back end is Supabase, the React front end is deployed to Vercel, and all the code is open source.

kwindla

454,497 次观看 • 3 个月前

CEO of phygitals explains why they chose to build on Solana "I think one thing Solana does really well and they're hard to beat at is both foundation and ecosystem support from builders and founders. They have the Superteam initiative, which is a great initiative where you can get tons of resources and learnings and free resources to build. And then the general community and collector community within Solana is very vibrant. Our whole go to market was pretty much utilizing ungraded/cheap Pokémon cards that we acquired while we didn't have much funding or profits. We gave these out to top Solana NFT communities and through the liveliness in the ecosystem, Phygitals was created. The initial user base was all Solana NFT collectors or traders and in that sense they have such a large user base, which makes it incredibly easy to build on."

CEO of phygitals explains why they chose to build on Solana "I think one thing Solana does really well and they're hard to beat at is both foundation and ecosystem support from builders and founders. They have the Superteam initiative, which is a great initiative where you can get tons of resources and learnings and free resources to build. And then the general community and collector community within Solana is very vibrant. Our whole go to market was pretty much utilizing ungraded/cheap Pokémon cards that we acquired while we didn't have much funding or profits. We gave these out to top Solana NFT communities and through the liveliness in the ecosystem, Phygitals was created. The initial user base was all Solana NFT collectors or traders and in that sense they have such a large user base, which makes it incredibly easy to build on."

Solana

48,231 次观看 • 2 个月前

BREAKING: Stephen from Metaplex announces first public launch of the Genesis SDK, a way for anyone to build their own fair launch platform or access token data

BREAKING: Stephen from Metaplex announces first public launch of the Genesis SDK, a way for anyone to build their own fair launch platform or access token data

Solana

31,515 次观看 • 7 个月前

Pipe (Pipe Network) is a decentralized content delivery network (dCDN) that accelerates delivery by leveraging users’ excess storage & bandwidth. More nodes = faster delivery. More from David Rhodus 🇺🇸 at Breakpoint '24

Pipe (Pipe Network) is a decentralized content delivery network (dCDN) that accelerates delivery by leveraging users’ excess storage & bandwidth. More nodes = faster delivery. More from David Rhodus 🇺🇸 at Breakpoint '24

Solana

78,975 次观看 • 1 年前

Today Sam Asante and I are releasing Typeahead 2.0 on Product Hunt. Sam and I started this company because we think local AI software is going to become a much bigger part of how people use their computers. Typeahead is the first product from that thesis. The first version made the idea clear. AI autocomplete should work in the apps where writing already happens. Since then, we have been shipping toward the product that idea deserves. The app feels faster and more natural. Suggestions are easier to control. The experience is more native to the Mac. It's getting better at staying out of the way until the exact moment it can help. That matters because writing is personal. The best AI writing help keeps you in the sentence. You stay in flow and keep your voice. The machine helps without taking over. Typeahead works across your Mac, runs locally, works offline, and is built to feel like software you own. We’re live on Product Hunt today.

Today Sam Asante and I are releasing Typeahead 2.0 on Product Hunt. Sam and I started this company because we think local AI software is going to become a much bigger part of how people use their computers. Typeahead is the first product from that thesis. The first version made the idea clear. AI autocomplete should work in the apps where writing already happens. Since then, we have been shipping toward the product that idea deserves. The app feels faster and more natural. Suggestions are easier to control. The experience is more native to the Mac. It's getting better at staying out of the way until the exact moment it can help. That matters because writing is personal. The best AI writing help keeps you in the sentence. You stay in flow and keep your voice. The machine helps without taking over. Typeahead works across your Mac, runs locally, works offline, and is built to feel like software you own. We’re live on Product Hunt today.

Hiten Shah

26,881 次观看 • 12 天前

Why We Ship: raposa. From surviving one of the biggest rugs to winning the People's Award at Breakpoint. SOK built Raposa to give back to the ecosystem, not extract from it.

Why We Ship: raposa. From surviving one of the biggest rugs to winning the People's Award at Breakpoint. SOK built Raposa to give back to the ecosystem, not extract from it.

Solana

73,460 次观看 • 3 个月前

BREAKING NEWS: For the first time, Solana Breakpoint 2026 will be hosted in London 🇬🇧 November 15-17 at Olympia FOR 24 HOURS ONLY, we're offering subsidized tickets to Solana's premier event in 2026:

BREAKING NEWS: For the first time, Solana Breakpoint 2026 will be hosted in London 🇬🇧 November 15-17 at Olympia FOR 24 HOURS ONLY, we're offering subsidized tickets to Solana's premier event in 2026:

Solana

930,074 次观看 • 7 个月前

Orbit AI Satellite Successfully Achieve World’s First Orbital AI Deployment and Launching Digital AI Sovereignty Decentralized Orbital AI Network Orbit AI Orbit AI🛰️ today announced that the first satellite, “OAI Genesis-1,” has successfully launched and entered Low Earth Orbit (LEO). Amidst fierce competition from tech giants (e.g., Starlink Starlink Elon Musk , Google AI Project Suncatcher) in space AI computing, this launch signifies Orbit AI’s position as the first to achieve real-world AI deployment, formally inaugurating its "Orbit AI Cloud Platform." Genesis-1 is equipped with NVIDIA NVIDIA AI Compute Cores, running a 2.6B parameter AI model for real-time analysis of infrared remote sensing data in space. By processing data on orbit, Genesis-1 drastically reduces critical information retrieval time (e.g., disaster alerts, maritime monitoring) from hours to mere seconds, while cutting transmission bandwidth costs by over 90%. Furthermore, Orbit AI has partnered with from energy company Powerbank (NASDAQ: SUUN) ( utilizing infinite solar power to achieve carbon-neutral computing and projecting a reduction in overall energy operational costs by 60%. Following its triumph at the BNB Chain Hackathon ( Orbit AI protocol is committed to creating an ultimate censorship-resistant deployment environment: Developers can deploy AI models, privacy applications, financial algorithms, and even blockchain nodes on the satellite network. This ensures that code and data operate in a physically isolated, neutral environment beyond the jurisdiction of major nations, guaranteeing extreme digital sovereignty and service resilience. Orbit AI will also leverage the RWA (Real World Assets) mechanism to allow community users to purchase satellite NFT shares, becoming co-owners of this space infrastructure and sharing in its compute revenues, thus building a community-owned orbital AI economy.

Orbit AI Satellite Successfully Achieve World’s First Orbital AI Deployment and Launching Digital AI Sovereignty Decentralized Orbital AI Network Orbit AI Orbit AI🛰️ today announced that the first satellite, “OAI Genesis-1,” has successfully launched and entered Low Earth Orbit (LEO). Amidst fierce competition from tech giants (e.g., Starlink Starlink Elon Musk , Google AI Project Suncatcher) in space AI computing, this launch signifies Orbit AI’s position as the first to achieve real-world AI deployment, formally inaugurating its "Orbit AI Cloud Platform." Genesis-1 is equipped with NVIDIA NVIDIA AI Compute Cores, running a 2.6B parameter AI model for real-time analysis of infrared remote sensing data in space. By processing data on orbit, Genesis-1 drastically reduces critical information retrieval time (e.g., disaster alerts, maritime monitoring) from hours to mere seconds, while cutting transmission bandwidth costs by over 90%. Furthermore, Orbit AI has partnered with from energy company Powerbank (NASDAQ: SUUN) ( utilizing infinite solar power to achieve carbon-neutral computing and projecting a reduction in overall energy operational costs by 60%. Following its triumph at the BNB Chain Hackathon ( Orbit AI protocol is committed to creating an ultimate censorship-resistant deployment environment: Developers can deploy AI models, privacy applications, financial algorithms, and even blockchain nodes on the satellite network. This ensures that code and data operate in a physically isolated, neutral environment beyond the jurisdiction of major nations, guaranteeing extreme digital sovereignty and service resilience. Orbit AI will also leverage the RWA (Real World Assets) mechanism to allow community users to purchase satellite NFT shares, becoming co-owners of this space infrastructure and sharing in its compute revenues, thus building a community-owned orbital AI economy.

Orbit AI🛰️

24,771 次观看 • 7 个月前

Founders: the next breakout game won’t come from a AAA studio. Hear from justin waldron on building at the cutting edge of crypto and AI at Accelerate this May in NYC 🗽

Founders: the next breakout game won’t come from a AAA studio. Hear from justin waldron on building at the cutting edge of crypto and AI at Accelerate this May in NYC 🗽

Solana

286,936 次观看 • 1 年前

A Perfect Pairing! 5G & Edge Computing: Together they enhance responsiveness, capacity and reliability by processing #data closer to where it’s generated! 🌟See🔗 ◀️T-Mobile Business 🔸This is critical for applications such as augmented reality #AR and #customer interaction and especially in contexts where low latency and near-real-time data processing are critical ✅ 🌟 MEC allows data processing closer to the source, reducing latency, improving efficiency, and enhancing resilience, whilst moving computing closer to users. It reduces latency and centralizes data processing. 🔸This is useful for scenarios that demand rapid data action, data #confidentiality or the ability to function without relying on distant #Cloud servers ☁️ Although only about 10% of enterprise data is currently processed outside central servers, this figure is anticipated to grow to 75% by 2025 🌟MEC can help in industries like #manufacturing 🏭#Retail 🛍️#warehousing 🚚#agriculture🌾and #logistics 🚛through faster decision-making, lower costs and more reliable data processing. Fixed and mobile edge applications are emerging, with mobile edge becoming a key area for future growth. 🔸5G's speed, low latency, and #security make it a natural fit with MEC, offering solutions to businesses' needs for faster responses, local data processing and reliable operations ✅ 📈Business Adoption: Though still early, it is anticipated that some 75% of #enterprise data will be processed at the #edge by 2025, driven by advancements in #Smart devices and routers with built-in processing capabilities 📶 💡To find out more, please explore the 🎞️resource below 🔽 See🔗 ⬅️#5G #EdgeComputing #TechNews #TFBPartner BusinessIntelligence Franco Ronconi 🇮🇹 #IoT Jean CAYEUX #RaviVisvesvarayaSharadaPrasad #Telecom #InfoTech Yann Marchand Tony Moroney #DigitalTransformation #Telco Knut Jägersberg Jean-Baptiste Lefevre 💙 #TechForGood 💙 #Sustainability Fati Sule Aurelien Lallemant #IA 🔎 & #RSE 🌎 Lionel Costes #AI Mack ipfconline Greg Valancius Dr. Marcell Vollmer #StaySafe #CES2026 #IoT Dev Khanna Baskaran Ambalavanan Anand Narang #CX Ian Jones Hana Laurent Alaus Xavier Gomez Pinna Pierre Dr. Khulood Almani | د.خلود المانع Eric T. #VR Enrico Molinari #VivaTech2025 Chidambara .ML. Smaksked Skåne AB 🌐

A Perfect Pairing! 5G & Edge Computing: Together they enhance responsiveness, capacity and reliability by processing #data closer to where it’s generated! 🌟See🔗 ◀️T-Mobile Business 🔸This is critical for applications such as augmented reality #AR and #customer interaction and especially in contexts where low latency and near-real-time data processing are critical ✅ 🌟 MEC allows data processing closer to the source, reducing latency, improving efficiency, and enhancing resilience, whilst moving computing closer to users. It reduces latency and centralizes data processing. 🔸This is useful for scenarios that demand rapid data action, data #confidentiality or the ability to function without relying on distant #Cloud servers ☁️ Although only about 10% of enterprise data is currently processed outside central servers, this figure is anticipated to grow to 75% by 2025 🌟MEC can help in industries like #manufacturing 🏭#Retail 🛍️#warehousing 🚚#agriculture🌾and #logistics 🚛through faster decision-making, lower costs and more reliable data processing. Fixed and mobile edge applications are emerging, with mobile edge becoming a key area for future growth. 🔸5G's speed, low latency, and #security make it a natural fit with MEC, offering solutions to businesses' needs for faster responses, local data processing and reliable operations ✅ 📈Business Adoption: Though still early, it is anticipated that some 75% of #enterprise data will be processed at the #edge by 2025, driven by advancements in #Smart devices and routers with built-in processing capabilities 📶 💡To find out more, please explore the 🎞️resource below 🔽 See🔗 ⬅️#5G #EdgeComputing #TechNews #TFBPartner BusinessIntelligence Franco Ronconi 🇮🇹 #IoT Jean CAYEUX #RaviVisvesvarayaSharadaPrasad #Telecom #InfoTech Yann Marchand Tony Moroney #DigitalTransformation #Telco Knut Jägersberg Jean-Baptiste Lefevre 💙 #TechForGood 💙 #Sustainability Fati Sule Aurelien Lallemant #IA 🔎 & #RSE 🌎 Lionel Costes #AI Mack ipfconline Greg Valancius Dr. Marcell Vollmer #StaySafe #CES2026 #IoT Dev Khanna Baskaran Ambalavanan Anand Narang #CX Ian Jones Hana Laurent Alaus Xavier Gomez Pinna Pierre Dr. Khulood Almani | د.خلود المانع Eric T. #VR Enrico Molinari #VivaTech2025 Chidambara .ML. Smaksked Skåne AB 🌐

Sen. Sally Eaves

10,484 次观看 • 1 年前

We're teaming up with mtndao 🗻 to host their first ever Demo Day on February 25th 🏔️ This will be the first stop on our mission to find and showcase the best new builders and products of 2026, on the road to Breakpoint

We're teaming up with mtndao 🗻 to host their first ever Demo Day on February 25th 🏔️ This will be the first stop on our mission to find and showcase the best new builders and products of 2026, on the road to Breakpoint

Solana

284,187 次观看 • 5 个月前

Elon Musk: “I want to live long enough to see the Mass Driver on the moon, because that’s going to be incredibly epic” SpaceX’s Lunar Mass Driver is a planned electromagnetic launch system on the Moon, similar to a coilgun-style catapult, designed to launch solar powered AI compute satellites into orbit or deep space at very low cost The idea is to build these satellites on the Moon using local resources, making it possible to scale AI infrastructure far beyond Earth’s limits, potentially reaching more than 100 terawatts per year compared with roughly 100 gigawatts per year from Earth via Starship The Moon makes this practical because of its low gravity, lack of atmosphere, and abundant solar power, which allow payloads to be accelerated efficiently to about 2.4 km/s escape velocity. The concept was revealed in February 2026 during an xAI all hands after the SpaceX and xAI merger, with renders showing a long launch track at “Moonbase Alpha” Elon Musk called it “incredibly epic” and important for beyond terawatt AI, and footage released in March 2026 showed a conceptual version of how it could work

Elon Musk: “I want to live long enough to see the Mass Driver on the moon, because that’s going to be incredibly epic” SpaceX’s Lunar Mass Driver is a planned electromagnetic launch system on the Moon, similar to a coilgun-style catapult, designed to launch solar powered AI compute satellites into orbit or deep space at very low cost The idea is to build these satellites on the Moon using local resources, making it possible to scale AI infrastructure far beyond Earth’s limits, potentially reaching more than 100 terawatts per year compared with roughly 100 gigawatts per year from Earth via Starship The Moon makes this practical because of its low gravity, lack of atmosphere, and abundant solar power, which allow payloads to be accelerated efficiently to about 2.4 km/s escape velocity. The concept was revealed in February 2026 during an xAI all hands after the SpaceX and xAI merger, with renders showing a long launch track at “Moonbase Alpha” Elon Musk called it “incredibly epic” and important for beyond terawatt AI, and footage released in March 2026 showed a conceptual version of how it could work

SMX 🇺🇸

25,635 次观看 • 3 个月前

Today, we give robots a /skills library that self-evolves and compounds indefinitely! Introducing ASPIRE: a robot solving its 100th task is no longer as clueless as solving its first. Coding agents observe multimodal sensory traces from simulation and real robots, launch an evolutionary search over control programs, and distill the best know-how into an ever-expanding library. ASPIRE is a new type of continual learning: "training" is skill refinement instead of gradient descent. "Trained model" is a repo of sensorimotor skills instead of floating weights. “Distributed training” is a panel of agents each practicing a different skill instead of sharded minibatches. Here's the beauty: ASPIRE gives the tired terms "sim2real transfer" and "cross-embodiment transfer" a whole new meaning. Bridging the sim-to-real gap is notoriously brutal. An end-to-end policy has to swallow both the visual shift (sim looks toyish next to a real camera) and the subtle contact physics it never quite gets right. ASPIRE sidesteps the mess, because it doesn't ship pixels or weights across the gap, but ships the know-how. The robot still has to practice in the real world, not zero-shot, but it gets there way faster because it isn't rediscovering the strategy from scratch. Same for going single-arm to bimanual hardware, which usually requires new data and retraining from zero. ASPIRE achieves up to ~10x cut in "transfer learning” tokens (yes, tokens are the new unit of *training* compute ;) Check out our gallery of 150+ tasks and 90+ skills the robots taught themselves, all on the website! Kind of wild that we can ship the "learned weights" as an HTML page rather than a GGUF. We'll open-source the full stack so your own robot library starts compounding from ours! Deep dive in thread:

Today, we give robots a /skills library that self-evolves and compounds indefinitely! Introducing ASPIRE: a robot solving its 100th task is no longer as clueless as solving its first. Coding agents observe multimodal sensory traces from simulation and real robots, launch an evolutionary search over control programs, and distill the best know-how into an ever-expanding library. ASPIRE is a new type of continual learning: "training" is skill refinement instead of gradient descent. "Trained model" is a repo of sensorimotor skills instead of floating weights. “Distributed training” is a panel of agents each practicing a different skill instead of sharded minibatches. Here's the beauty: ASPIRE gives the tired terms "sim2real transfer" and "cross-embodiment transfer" a whole new meaning. Bridging the sim-to-real gap is notoriously brutal. An end-to-end policy has to swallow both the visual shift (sim looks toyish next to a real camera) and the subtle contact physics it never quite gets right. ASPIRE sidesteps the mess, because it doesn't ship pixels or weights across the gap, but ships the know-how. The robot still has to practice in the real world, not zero-shot, but it gets there way faster because it isn't rediscovering the strategy from scratch. Same for going single-arm to bimanual hardware, which usually requires new data and retraining from zero. ASPIRE achieves up to ~10x cut in "transfer learning” tokens (yes, tokens are the new unit of training compute ;) Check out our gallery of 150+ tasks and 90+ skills the robots taught themselves, all on the website! Kind of wild that we can ship the "learned weights" as an HTML page rather than a GGUF. We'll open-source the full stack so your own robot library starts compounding from ours! Deep dive in thread:

Jim Fan

198,213 次观看 • 18 天前