Arm

Arm Co-founder Hauser Warns of AI Bubble Risk

Hermann Hauser, co-founder of Arm and Acorn Computers and an investor via Amadeus Capital, told CNBC’s The Tech Download podcast that the AI revolution will likely create more value than prior technology waves but carries significant bubble and valuation risks. He warned some valuations have run ahead of fundamentals and pointed to circular financing deals as a concern, while noting large, well-capitalised players such as OpenAI and Anthropic can survive turbulence. Hauser highlighted current constraints in AI compute — cost, cooling, and memory bottlenecks — and flagged emerging approaches like in-memory and photonic computing as potential architectural shifts. He also argued Europe must preserve close cooperation with the U.S. while avoiding technological dependence and urged building stronger European capabilities and sovereignty.

Rust portable SIMD targets GPUs via VectorWare

VectorWare announced a technical implementation that allows Rust's portable SIMD (core::simd) to run natively on GPUs by mapping Rust Simd<T, N> vectors to GPU warps. The approach enables the same Rust SIMD code to compile to GPU warp instructions (e.g., NVIDIA) or CPU vector instructions (e.g., AVX on x86) without separate CUDA/OpenCL kernels. The implementation currently requires VectorWare's GPU runtime rather than stock rustc, and performance data is limited. If adopted more broadly, this could let Rust numerical libraries, game engines, and ML frameworks gain GPU support with minimal code changes.

AMD: No Single 'Agentic Rack' — Agentic CPUs Explained

Madhu Rangarajan, Corporate VP at AMD for Compute and Enterprise AI Products, explains why agentic AI infrastructure cannot be reduced to a single machine type and outlines AMD's multi-tier server strategy. He argues that agentic workflows create significant CPU demand because GPUs produce tokens while CPUs run tool calls, sandboxes and verification loops. AMD divides the server market into host nodes (to feed GPUs), general-purpose servers, and a new tier for agent orchestration/sandboxes. AMD’s Venice 256-core, ~400W SKU is positioned to “maximize threads per megawatt” for high-concurrency agent workloads. Rangarajan also discusses tokenomics (routing work to smaller models or on-prem hardware to reduce spend), the prevalence of agents running decoupled from GPUs, and the expectation that open orchestration (eventually Kubernetes-style) will win out over bespoke stacks.