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  • AMD 🤝 @OracleCloud

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    Physical AI is about more than how fast a model can run. It's about whether the entire system can act in time. Salil Raje, SVP and GM of the AMD Embedded business, explains why robotics needs a system-level approach, with the right compute for AI reasoning, real-time control and coordination. Read the blog: https://t.co/LC682ihgHv

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    Embedded development, meet agentic AI. Dive into @Forbes latest piece on AMD Ross, a new agentic AI assistant that dramatically accelerates the entire embedded design and development cycle by bringing natural-language tool interaction and expert-authored workflows together in a single agentic AI experience: https://t.co/IfW3OjWJ4E

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  • Agentic AI demands a new kind of infrastructure. At #OCPSummit26 we announced AMD Helion, bringing an open rack-scale design for CPU-centric agentic AI deployments, with flexible configurations for enterprises. Full story on @TomsHardware: https://t.co/HEANnt5FY1

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  • Scaling AI responsibly means getting more performance from every watt. As a software development engineer, Nathaniel Morris studies how AI workloads use power and helps optimize AMD GPU systems to improve performance per watt. Swipe through to learn how his work supports more efficient AI infrastructure.

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  • For physical AI, peak compute is only part of the equation. Robots must sense, reason and act within precise windows of time. That means CPUs, GPUs, NPUs, FPGAs, memory, networking, sensors and software need to work together as one coordinated system. In his latest blog, Salil Raje, SVP and GM of the AMD Embedded business, explains why physical AI requires a system-level approach – from putting the right compute on the right workload to designing safety into the architecture and measuring performance from sensor input to physical action. That’s the approach behind the AMD Kria AI portfolio: an open, heterogeneous compute foundation designed for the real-world demands of robotics. Read Salil’s perspective: https://lnkd.in/g2tPzAWT

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  • AI development needs room to move between local devices and the cloud. With Ryzen AI Halo, developers can experiment and iterate with models locally. Jack Huynh, AMD SVP and GM of the Computing and Graphics Group, shares his vision for how local AI can work alongside cloud and data center infrastructure as models continue to evolve.

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