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✨ Personal AI is the next computing platform. AI is shifting from something you access to something you build with, locally, at the edge, and across systems. We’re unlocking new possibilities for developers: • AMD Ryzen AI Halo, a local-first developer system, preorder starting in June, develop AI without...

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Jack Huynh

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47,822 views • 2 months ago •via X (Twitter)

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The ultimate local AI developer platform is here. AMD Ryzen AI Halo presale is now live! Built for #AMDevs, Ryzen AI Halo delivers the performance, memory, and AI capabilities needed to build, test, and run agentic AI, generative AI, LLM applications, and more locally. Reserve yours now:
1:24

The ultimate local AI developer platform is here. AMD Ryzen AI Halo presale is now live! Built for #AMDevs, Ryzen AI Halo delivers the performance, memory, and AI capabilities needed to build, test, and run agentic AI, generative AI, LLM applications, and more locally. Reserve yours now:

AI at AMD

19,563 views • 1 month ago

Introducing AMD Ryzen AI Halo, an Agent Computer built to make local AI development fast and simple. • Ryzen AI Developer Center pre-installed • Pre-optimized from first power on • Built to reduce setup friction • Designed for local AI development AMD Ryzen AI Halo brings AI from the cloud into the hands of developers with Ryzen AI developer center pre-installed and optimized from first power on, developers can hit the ground running.
1:07

Introducing AMD Ryzen AI Halo, an Agent Computer built to make local AI development fast and simple. • Ryzen AI Developer Center pre-installed • Pre-optimized from first power on • Built to reduce setup friction • Designed for local AI development AMD Ryzen AI Halo brings AI from the cloud into the hands of developers with Ryzen AI developer center pre-installed and optimized from first power on, developers can hit the ground running.

AMD

26,042 views • 2 months ago

💥AI is no longer confined to the cloud. At Computex, Jack Huynh showcased the AMD Ryzen AI Halo and Ryzen AI Max PRO 400 Series processors. The next wave of innovation will be built, trained, and run locally. As AI evolves from chatbots to intelligent agents, developers and enterprises need the performance, memory capacity, and flexibility to bring these experiences to life directly on the device. ⚡ Ryzen AI Halo enables local AI development with support for models up to 200B parameters, up to 128GB of unified memory, ROCm optimization, and Windows + Linux support. ⚡ Ryzen AI Max PRO 400 Series combines AI, graphics, and compute in a single architecture, delivering workstation-class performance for next-gen Agent Computers and AI PCs. Some of the most impactful AI experiences will happen right at your desk, where latency, privacy, and control matter most. We're just getting started.
1:24

💥AI is no longer confined to the cloud. At Computex, Jack Huynh showcased the AMD Ryzen AI Halo and Ryzen AI Max PRO 400 Series processors. The next wave of innovation will be built, trained, and run locally. As AI evolves from chatbots to intelligent agents, developers and enterprises need the performance, memory capacity, and flexibility to bring these experiences to life directly on the device. ⚡ Ryzen AI Halo enables local AI development with support for models up to 200B parameters, up to 128GB of unified memory, ROCm optimization, and Windows + Linux support. ⚡ Ryzen AI Max PRO 400 Series combines AI, graphics, and compute in a single architecture, delivering workstation-class performance for next-gen Agent Computers and AI PCs. Some of the most impactful AI experiences will happen right at your desk, where latency, privacy, and control matter most. We're just getting started.

AMD

24,315 views • 2 months ago

WOW! OPENAI DID IT! They released their first TWO open weights models! This is HUGE news for the entire AI industry. It means you can RIGHT NOW run cutting edge AI models locally on your computer Here's all the benefits and how to set up the models locally yourself:
7:40

WOW! OPENAI DID IT! They released their first TWO open weights models! This is HUGE news for the entire AI industry. It means you can RIGHT NOW run cutting edge AI models locally on your computer Here's all the benefits and how to set up the models locally yourself:

Alex Finn

71,875 views • 1 year ago

I'm excited about the new @amd Ryzen AI Halo because we need more local hardware for AI builders! There's something fun and exciting about building on your own machines rather than sending to the cloud! Should we do our own Hugging Face hardware for AI builders at some point?
1:15

I'm excited about the new @amd Ryzen AI Halo because we need more local hardware for AI builders! There's something fun and exciting about building on your own machines rather than sending to the cloud! Should we do our own Hugging Face hardware for AI builders at some point?

clem 🤗

42,302 views • 2 months ago

Hugging Face CEO Clem Delangue predicts that a growing share of AI inference will run locally, on-device. It's faster. Cheaper. Private by default. And as open source AI moves from apps to machines, it could trigger “some sort of ChatGPT moment for robotics.” The next AI breakthrough will happen where intelligence becomes embodied, cheap, private, and open.
1:27

Hugging Face CEO Clem Delangue predicts that a growing share of AI inference will run locally, on-device. It's faster. Cheaper. Private by default. And as open source AI moves from apps to machines, it could trigger “some sort of ChatGPT moment for robotics.” The next AI breakthrough will happen where intelligence becomes embodied, cheap, private, and open.

vitrupo

37,764 views • 1 year ago

Agents are scaling. So are the token costs. CIOs are shifting to AI PCs as strategic nodes. Ryzen AI Max 400 series changes the equation with 192GB of memory for local LLMs and agent swarms. You overheard it here first at Computex.
1:29

Agents are scaling. So are the token costs. CIOs are shifting to AI PCs as strategic nodes. Ryzen AI Max 400 series changes the equation with 192GB of memory for local LLMs and agent swarms. You overheard it here first at Computex.

AMD

11,342 views • 1 month ago

Jensen Huang says the industry is shifting from generative AI to agentic AI The next major step is fusing public cloud frontier models with customized open-source systems running on enterprise servers But the end goal is physical: "moving intelligence from the cloud into industrial AI, factories and robotics"
1:25

Jensen Huang says the industry is shifting from generative AI to agentic AI The next major step is fusing public cloud frontier models with customized open-source systems running on enterprise servers But the end goal is physical: "moving intelligence from the cloud into industrial AI, factories and robotics"

Haider.

49,451 views • 7 months ago

Exciting update for AI developers! The Hugging Face Hub is now more natively integrated into Google Cloud Vertex AI Model Garden. Search through thousands of open Generative AI models from Hugging Face models & deploy them with one click to Vertex AI or GKE. 🤯 What's new: 🔎 Browse and search thousands of Hugging Face models directly within the Vertex AI Model Garden and filter based on what is currently trending in the community. 🚀 Accelerate your AI projects by leveraging readily available one-click deploy your model to Vertex AI or Google Kubernetes Engine (GKE). ⭐️ Featuring popular open models from BlackForestLabsAI - Unofficial FLUX.1, AI at Meta Llama 3.1, Mistral AI, Google DeepMind Gemma, and countless others. Get Started:
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Exciting update for AI developers! The Hugging Face Hub is now more natively integrated into Google Cloud Vertex AI Model Garden. Search through thousands of open Generative AI models from Hugging Face models & deploy them with one click to Vertex AI or GKE. 🤯 What's new: 🔎 Browse and search thousands of Hugging Face models directly within the Vertex AI Model Garden and filter based on what is currently trending in the community. 🚀 Accelerate your AI projects by leveraging readily available one-click deploy your model to Vertex AI or Google Kubernetes Engine (GKE). ⭐️ Featuring popular open models from BlackForestLabsAI - Unofficial FLUX.1, AI at Meta Llama 3.1, Mistral AI, Google DeepMind Gemma, and countless others. Get Started:

Philipp Schmid

34,754 views • 1 year ago

🌟 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
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🌟 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

44,310 views • 1 year ago

AI answers your questions in seconds, but behind that speed is something called inference—the compute-intensive process where trained models generate responses. At AWS, we've built custom chips like Trainium, intelligent routing systems, and unified infrastructure to make inference faster and more affordable. As AI agents handle complex multi-step tasks, inference accounts for 80-90% of AI computing power. We're engineering at planetary scale to keep those milliseconds reliable.
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AI answers your questions in seconds, but behind that speed is something called inference—the compute-intensive process where trained models generate responses. At AWS, we've built custom chips like Trainium, intelligent routing systems, and unified infrastructure to make inference faster and more affordable. As AI agents handle complex multi-step tasks, inference accounts for 80-90% of AI computing power. We're engineering at planetary scale to keep those milliseconds reliable.

Amazon Web Services

27,021 views • 5 months ago

The demand for AI capabilities is outpacing the computational capacity available today. As workloads become more complex, small language models are growing larger, with longer input sequences and rising resource demands. The relentless pursuit of near zero latency is now mission-critical as domain-specific models advance. This challenge inspired us to design something radically different — Strix Halo. In deep co-engineering partnership with HP, we’re incredibly proud to power the new ZBook Ultra G1a, the world’s best mobile workstation, and the Z2 Mini G1a, the world’s best mini workstation. Strix Halo shatters the limits of mobile performance, bringing workstation-level power into thin and light laptops. By unlocking access to 128GB of unified memory between CPU and GPU combined with 256GB/s of memory bandwidth, Strix Halo enables architects, engineers, creatives, and data scientists to tackle massive datasets, complex simulations, and AI workflows without compromise. Strix Halo is the world’s first AI PC processor capable of running 70 billion parameter models. Just five years ago, this kind of inference computing required a room full of servers — today, it fits in your backpack. This is a major step forward in the future of AI PCs. Stay tuned as we continue to break boundaries 🚀 #TogetherWeAdvance AMD
0:58

The demand for AI capabilities is outpacing the computational capacity available today. As workloads become more complex, small language models are growing larger, with longer input sequences and rising resource demands. The relentless pursuit of near zero latency is now mission-critical as domain-specific models advance. This challenge inspired us to design something radically different — Strix Halo. In deep co-engineering partnership with HP, we’re incredibly proud to power the new ZBook Ultra G1a, the world’s best mobile workstation, and the Z2 Mini G1a, the world’s best mini workstation. Strix Halo shatters the limits of mobile performance, bringing workstation-level power into thin and light laptops. By unlocking access to 128GB of unified memory between CPU and GPU combined with 256GB/s of memory bandwidth, Strix Halo enables architects, engineers, creatives, and data scientists to tackle massive datasets, complex simulations, and AI workflows without compromise. Strix Halo is the world’s first AI PC processor capable of running 70 billion parameter models. Just five years ago, this kind of inference computing required a room full of servers — today, it fits in your backpack. This is a major step forward in the future of AI PCs. Stay tuned as we continue to break boundaries 🚀 #TogetherWeAdvance AMD

Jack Huynh

11,960 views • 1 year ago

AI is rapidly evolving, and it’s reshaping how and where computing happens. From data center infrastructure to AI systems in the physical world, to the future of personal AI devices, intelligence is being distributed across a new compute landscape. At the edge, more agentic experiences are starting to show up, expanding what devices need to do. Tomorrow in New York, we’ll share what Qualcomm is building across it and how it will drive our next phase of growth. Stay tuned for #QCOMInvestorDay.
0:32

AI is rapidly evolving, and it’s reshaping how and where computing happens. From data center infrastructure to AI systems in the physical world, to the future of personal AI devices, intelligence is being distributed across a new compute landscape. At the edge, more agentic experiences are starting to show up, expanding what devices need to do. Tomorrow in New York, we’ll share what Qualcomm is building across it and how it will drive our next phase of growth. Stay tuned for #QCOMInvestorDay.

Cristiano R. Amon

15,607 views • 1 month ago

Open models are accelerating development and deployment across agentic AI, physical AI, and a growing range of industries. ✨ “We have billions of dollars of supercomputers in operation, so we can develop our open models,” said NVIDIA CEO Jensen Huang in a recent keynote. “That work is starting to attract attention across industries worldwide, as we build frontier AI models in many different domains.” This includes leading open models from NVIDIA, including: ⚙️ NVIDIA Nemotron for agentic AI ⚙️ NVIDIA Cosmos and GR00T for physical AI ⚙️ NVIDIA Alpamayo for autonomous vehicles ⚙️ NVIDIA Clara for biomedical AI Learn more about open source and AI ➡️
0:20

Open models are accelerating development and deployment across agentic AI, physical AI, and a growing range of industries. ✨ “We have billions of dollars of supercomputers in operation, so we can develop our open models,” said NVIDIA CEO Jensen Huang in a recent keynote. “That work is starting to attract attention across industries worldwide, as we build frontier AI models in many different domains.” This includes leading open models from NVIDIA, including: ⚙️ NVIDIA Nemotron for agentic AI ⚙️ NVIDIA Cosmos and GR00T for physical AI ⚙️ NVIDIA Alpamayo for autonomous vehicles ⚙️ NVIDIA Clara for biomedical AI Learn more about open source and AI ➡️

NVIDIA AI

19,296 views • 6 months ago

GT Protocol AI Digest No.82: AI Starts Running the System Here are five stories worth your attention 👇 💻 NVIDIA Pushes AI to Your Device NVIDIA showcased RTX PCs and DGX systems that can run AI models and agents locally. The shift is important. AI is no longer tied to the cloud, it is moving directly onto user devices. 🧠 Gemini Becomes Personal Google is rolling out personalized Gemini across the US. The assistant adapts to your context and activity, turning AI from a generic tool into a persistent, tailored system. 🎨 Adobe Lets You Train Your Own AI Adobe now allows users to train Firefly models on their own artwork. This gives creators more control over style, but also raises new questions around ownership and dataset boundaries. ⚡️ Smaller GPT-5.4 Models Go Wide OpenAI introduced GPT-5.4 mini and nano, optimized for efficiency and broader deployment. Strong models are no longer limited to heavy infrastructure. 💳 Visa Prepares for AI Payments Visa is building systems for transactions initiated by AI agents. This moves AI beyond interfaces and into real economic activity. Read the full digest on our Medium 👉
0:44

GT Protocol AI Digest No.82: AI Starts Running the System Here are five stories worth your attention 👇 💻 NVIDIA Pushes AI to Your Device NVIDIA showcased RTX PCs and DGX systems that can run AI models and agents locally. The shift is important. AI is no longer tied to the cloud, it is moving directly onto user devices. 🧠 Gemini Becomes Personal Google is rolling out personalized Gemini across the US. The assistant adapts to your context and activity, turning AI from a generic tool into a persistent, tailored system. 🎨 Adobe Lets You Train Your Own AI Adobe now allows users to train Firefly models on their own artwork. This gives creators more control over style, but also raises new questions around ownership and dataset boundaries. ⚡️ Smaller GPT-5.4 Models Go Wide OpenAI introduced GPT-5.4 mini and nano, optimized for efficiency and broader deployment. Strong models are no longer limited to heavy infrastructure. 💳 Visa Prepares for AI Payments Visa is building systems for transactions initiated by AI agents. This moves AI beyond interfaces and into real economic activity. Read the full digest on our Medium 👉

GT Protocol

40,085 views • 4 months ago

At Google I/O, I sat down with Omar Sanseviero and 👩‍💻 Paige Bailey from Google DeepMind to talk about Gemma, open models, AI Studio, on-device AI, sovereign AI and the future of AI development. A great conversation on how building with AI is becoming more open, local and accessible.
26:51

At Google I/O, I sat down with Omar Sanseviero and 👩‍💻 Paige Bailey from Google DeepMind to talk about Gemma, open models, AI Studio, on-device AI, sovereign AI and the future of AI development. A great conversation on how building with AI is becoming more open, local and accessible.

Chubby♨️

13,741 views • 2 months ago

Hyra AI Reborn. Stronger. Faster. Decentralized. 🔥 Reimagined. A new direction. A new era of decentralized intelligence. From privacy-first edge compute → to a global AI mesh owned by the people. From inference on your device → to digital sovereignty at scale. ✨ Every device is now a node. ✨ Every user is a Hyrasapien. ✨ Every action builds the future of AI. We’re not just rebranding ~ we’re reshaping the narrative of AI. Together, let’s build an AI infrastructure that’s secure, verifiable, and community-owned. 🔑 Your Device. Your Power. Your Sovereignty. 🌐 Explore the new era:
0:35

Hyra AI Reborn. Stronger. Faster. Decentralized. 🔥 Reimagined. A new direction. A new era of decentralized intelligence. From privacy-first edge compute → to a global AI mesh owned by the people. From inference on your device → to digital sovereignty at scale. ✨ Every device is now a node. ✨ Every user is a Hyrasapien. ✨ Every action builds the future of AI. We’re not just rebranding ~ we’re reshaping the narrative of AI. Together, let’s build an AI infrastructure that’s secure, verifiable, and community-owned. 🔑 Your Device. Your Power. Your Sovereignty. 🌐 Explore the new era:

Hyra AI

96,099 views • 10 months ago

🤝 Alphabet and NVIDIA are expanding their decade-long partnership to advance agentic AI, robotics, drug discovery, and more. This involves deep co-engineering with integrated platforms, open-source frameworks, and managed services. ✅ Google Cloud is one of the first to bring the NVIDIA Blackwell platform to the cloud. ✅ Google Distributed Cloud using NVIDIA Confidential Computing on #NVIDIABlackwell for enterprises to run Google Gemini on-premises. ✅ Integration of the NVIDIA AI platform across Vertex AI, Cluster Director and Google Kubernetes Engine. ✅ Bringing the NVIDIA Nemotron family of open models to Vertex AI Model Garden. Watch the full video to learn more ➡️
0:30

🤝 Alphabet and NVIDIA are expanding their decade-long partnership to advance agentic AI, robotics, drug discovery, and more. This involves deep co-engineering with integrated platforms, open-source frameworks, and managed services. ✅ Google Cloud is one of the first to bring the NVIDIA Blackwell platform to the cloud. ✅ Google Distributed Cloud using NVIDIA Confidential Computing on #NVIDIABlackwell for enterprises to run Google Gemini on-premises. ✅ Integration of the NVIDIA AI platform across Vertex AI, Cluster Director and Google Kubernetes Engine. ✅ Bringing the NVIDIA Nemotron family of open models to Vertex AI Model Garden. Watch the full video to learn more ➡️

NVIDIA AI Infrastructure

268,567 views • 6 months ago

Sam Altman recently said: “GPT-OSS has strong real-world performance comparable to o4-mini—and you can run it locally on your phone.” Many believed running a 20B-parameter model on mobile devices was still years away. At Nexa AI, we’ve built our foundation on deep on-device AI technology—turning that vision into reality. Today, GPT-OSS is running fully local on mobile devices through our app, Nexa Studio. Real performance on Snapdragon Gen 5: - 17 tokens/sec decoding speed - < 3 seconds Time-to-First-Token Developers can now use NexaSDK to build their own local AI apps powered by GPT-OSS. What this unlocks: - Real reasoning models running locally - The next wave of AI Agent use cases—without cloud limits - True data privacy: your data never leaves your device Appreciation to OpenAI Sam Altman Greg Brockman and the entire leadership team for pushing the boundaries of the open-source AI community. Thanks to Qualcomm for the partnership, and to Manoj Khilnani and Chun-Po (Jerry) Chang for the incredible collaboration.
0:31

Sam Altman recently said: “GPT-OSS has strong real-world performance comparable to o4-mini—and you can run it locally on your phone.” Many believed running a 20B-parameter model on mobile devices was still years away. At Nexa AI, we’ve built our foundation on deep on-device AI technology—turning that vision into reality. Today, GPT-OSS is running fully local on mobile devices through our app, Nexa Studio. Real performance on Snapdragon Gen 5: - 17 tokens/sec decoding speed - < 3 seconds Time-to-First-Token Developers can now use NexaSDK to build their own local AI apps powered by GPT-OSS. What this unlocks: - Real reasoning models running locally - The next wave of AI Agent use cases—without cloud limits - True data privacy: your data never leaves your device Appreciation to OpenAI Sam Altman Greg Brockman and the entire leadership team for pushing the boundaries of the open-source AI community. Thanks to Qualcomm for the partnership, and to Manoj Khilnani and Chun-Po (Jerry) Chang for the incredible collaboration.

NEXA AI

197,453 views • 10 months ago