AMD just rolled out its first small language model, AMD-135M, targeting private enterprise deployments. Available in base and code-specific versions, the Llama-family model was trained on AMD Instinct MI250 hardware and uses speculative decoding as a lightweight draft model to speed up larger LLM inference.
AMD just teamed up with TensorStack to release Amuse 2.0 Beta, a local AI suite that runs Stable Diffusion and ControlNet workflows without any command-line setup. The biggest perk is XDNA Super Resolution, which speeds up creation and doubles output resolution on supported Ryzen AI processors and Radeon RX 7000 GPUs. It gives PC users a seamless on-device sandbox that bypasses the cloud entirely.
Nvidia just swept all seven categories in the latest MLPerf inference benchmarks, showcasing its new H200 chip and TensorRT-LLM software optimizations. Inference now drives roughly 40% of Nvidia's data center revenue. Intel submitted results for Gaudi2 and 5th Gen Xeon, but AMD once again chose not to submit its MI300.
Microsoft just detailed DirectSR, a new Windows API built with Nvidia, AMD, and Intel to streamline AI super resolution across PC games. Instead of writing custom integrations for DLSS, FSR, and XeSS separately, developers can now support all three through a single code path. It rolls out soon via an Agility SDK preview.
Security firm Trail of Bits just disclosed a vulnerability dubbed LeftoverLocals impacting GPUs from Apple, AMD, and Qualcomm, allowing attackers to siphon up to 180 megabytes of data directly from local GPU memory. The flaw exposes user queries and model weights from locally run LLMs. Apple patched it on M3 and A17 chips, but millions of older devices remain vulnerable.
AMD just launched its Instinct MI300X accelerator and MI300A APU to challenge Nvidia’s dominance in large language model training and inference. The company claims the MI300X beats Nvidia’s H100 by 1.4x in Llama 2 inference, with Microsoft and Meta already lining up to deploy the hardware in cloud and data centers.
AMD just signed an agreement to acquire Nod.ai, an open-source AI software startup behind projects like SHARK and Torch-MLIR. The team specializes in automated compiler tech that speeds up model deployment across AMD GPUs and chips. Why it matters: software has long been AMD's weak link against Nvidia, and this deal shows it's doubling down on open-source tools to catch up.
The U.S. government just expanded its AI chip export restrictions beyond China, requiring Nvidia and AMD to secure licenses before shipping top-tier chips like the A100 and H100 to some Middle Eastern nations. Both chipmakers say the curbs won't immediately hit their revenues, but it shows Washington is tightening its grip on global compute.
Nvidia just reported a massive $6.188B in quarterly net profit, up 843% year over year on $13.5B in revenue. The surge was driven by its data center business, which reached a record $10.32B as demand for generative AI chips exploded. Basically, Nvidia is dominating the hardware race while projecting an even bigger $16B next quarter.
AMD just laid out its next-gen data center roadmap at its premiere event, officially making AI its top strategic priority. The spotlight was firmly on the multi-die Instinct MI300 accelerators, designed directly to challenge Nvidia's dominant Hopper architecture.
AMD just joined Hugging Face’s Hardware Partner Program to accelerate transformer models across its CPUs and GPUs. The partnership brings native ROCm support to the transformers library, optimizing training and inference for models like LLaMA and StarCoder on Instinct and Ryzen chips. It marks a serious push to give AI developers a viable, cost-effective alternative to Nvidia.
Microsoft is reportedly teaming up with AMD to boost the AI capabilities of AMD GPUs, offering engineering resources to help break Nvidia’s near-monopoly on hardware. A more competitive hardware market could dramatically slash server costs for running large generative models. Microsoft, however, flatly denied that AMD is involved with its internal Athena AI chip.
Nvidia is reportedly planning to optimize its GeForce graphics drivers using AI to squeeze out better gaming performance. Leaker CapFrameX claims the updates will tune instructions and hardware utilization, delivering an average 10% uplift and up to 30% in select titles. Why it matters: If true, AI-driven driver tuning could give Nvidia GPUs lasting performance gains over time without requiring new silicon.
AMD just unveiled its Ryzen 7040 series mobile processors, marking the first time an x86 chip features a dedicated on-die AI engine called Ryzen AI. Built on the XDNA adaptive architecture, AMD claims it outperforms Apple's M2 in both AI speed and battery efficiency. The first laptops powered by the chip will ship this March.
