Reports
AI-generated structured vendor updates
ARM Builds Its First Chip in 35 Years: AGI CPU Targets AI Data Centers, Meta First Customer
ARM announces its first in-house CPU in 35 years, the AGI CPU, targeting AI and data center workloads. Meta is the launch customer. Built on TSMC's 3nm process, the chip focuses on performance-per-watt, directly challenging x86 dominance and fundamentally restructuring ARM's business model from IP licensor to merchant silicon vendor.
Meta Partners with Arm to Develop New AI Data Center CPUs
Meta partners with Arm to co-develop data center CPUs optimized for AI workloads. The first product, the Arm AGI CPU, aims to boost rack performance density for large-scale AI deployments. It will be available through Arm's ecosystem, with board designs to be open-sourced via the Open Compute Project.
ARM Launches AGI CPU for Agentic AI Infrastructure Era
ARM introduces the Arm AGI CPU, its first silicon product, designed for agentic AI infrastructure on Neoverse. Optimized for massively parallel workloads, it supports 272 cores per blade in a 1OU design, delivering 8160 cores per rack and over 2x performance vs. x86 systems.
ARM Launches AGI CPU Silicon for AI Infrastructure Market
ARM introduced its first production AGI CPU silicon in March 2026, marking a strategic shift from IP licensing to full silicon solutions provider. Designed for next-gen AI infrastructure, this move may reshape the data center processor ecosystem.
Arm Neoverse Reshapes Control Layer in AI Infrastructure
ARM introduces Neoverse infrastructure CPU cores optimized for cloud, AI, and HPC workloads, adopted by NVIDIA, AWS, Microsoft, and Google for their AI platforms, delivering performance gains and energy efficiency. This architecture enables high-density AI workload deployment in cloud and edge environments with enhanced multi-tenant security.
HPE Enhances AI Security Architecture for Adoption Risks
HPE introduces SRX400 Series Firewalls, expanded hybrid mesh security, and AI governance capabilities to secure AI adoption. Features include AI app visibility, prompt-level inspection, and identity-based protection to mitigate data exposure risks.
NVIDIA IGX Thor: 8x Edge AI Compute with ConnectX-7 Network Lock-In
NVIDIA launches IGX Thor edge AI platform with Blackwell GPU, up to 5,581 FP4 TFLOPS, dual 200GbE RDMA via ConnectX-7, and ISO 26262 safety. Pin-compatible with Jetson Thor and 10-year lifecycle enable seamless migration, but create vendor lock-in through proprietary networking and GPU dependencies.
ARM and NVIDIA Drive Localization Revolution in AI Workstations
ARM and NVIDIA jointly launch DGX Spark AI workstations based on GB10 Grace Blackwell chips, with eight major OEMs releasing products simultaneously. The solution features unified memory architecture supporting 200B parameter models locally, with third-party tests showing 41% faster rendering and 3.2x AI processing speed versus x86 alternatives, enabling seamless cloud-to-edge toolchain migration.
NVIDIA Launches OpenShell, Establishing Runtime Sandbox for Secure Autonomous AI Agents
NVIDIA introduces OpenShell, an open-source project designed as a secure-by-design runtime for autonomous AI agents. It employs a "browser tab" model, isolating agent operations from policy enforcement at the system level to prevent policy overrides and data leaks. NVIDIA is collaborating with key security vendors to establish a unified policy layer for enterprise AI agents.
Check Point AI Factory Blueprint: Security Control Shifts to NVIDIA DPU and LLM Layer
Check Point unveils AI Factory Security Blueprint, tightly integrating its firewall with NVIDIA BlueField DPU via DOCA. The architecture enforces security at four layers: LLM, AI infrastructure, perimeter, and workload. The new AI Factory Firewall delivers hardware-accelerated threat prevention without consuming CPU/GPU cycles, aiming to embed security into the AI fabric.
AMD and Samsung Deepen HBM4 and CXL Memory Technology Collaboration
AMD and Samsung expanded strategic collaboration to co-develop next-gen AI memory solutions, focusing on HBM4 and CXL technologies. The partnership will optimize memory controllers, PHY layers and packaging to enhance AI computing platform performance. Joint efforts will advance HBM4 standardization and explore CXL applications in memory pooling.
AMD and NAVER Cloud Collaborate on Sovereign AI Infrastructure in Korea
AMD and NAVER Cloud announced a strategic collaboration to accelerate sovereign AI infrastructure in Korea. NAVER Cloud will expand deployment of AMD EPYC "Venice" CPUs and gain early access to next-gen Instinct MI455X GPUs, with joint optimization of AI services and software stacks on AMD platforms.
AMD and Samsung Deepen Collaboration, Locking HBM4 Supply and Exploring Foundry Partnership
AMD and Samsung signed an MOU, designating Samsung as the primary HBM4 supplier for the next-gen Instinct MI455X GPU and collaborating on DDR5 memory optimized for 6th Gen EPYC CPUs. The companies will also explore opportunities for Samsung to provide foundry services for future AMD products.
NVIDIA and Telecom Operators Build AI Grids to Redistribute AI Inference
NVIDIA is partnering with global telecom operators like AT&T and Comcast to transform existing distributed network sites into 'AI Grids' for edge AI inference. This initiative aims to deploy AI compute closer to users and data, reducing latency and cost per token. It represents a strategic shift for telcos from being data carriers to distributed AI computing platforms.
HPE Unveils AI Grid Solution for AI WAN Fabric with NVIDIA
HPE announced a collaboration with NVIDIA to launch the AI Grid Solution, securely scaling edge AI. The solution transforms WAN into an AI WAN fabric, connecting distributed inference sites with AI factories for consistent policy and predictable performance. It enables service providers to evolve from connectivity to AI services.
HPE Deepens AI Factory Partnership with NVIDIA, Unveils Full-Stack Supercomputing Solutions
At GTC 2026, HPE announced enhancements to its NVIDIA AI Computing portfolio, introducing full-stack solutions for large-scale AI factories and supercomputers. The offerings integrate compute, GPUs, networking, liquid cooling, software, and services to improve deployment efficiency and time-to-insight.
HPE Positions AI Data Pipeline as the Platform, Outlining Pillars for Production AI
HPE argues enterprise AI is shifting from experimentation to production, reliant on an infrastructure platform comprising the data pipeline, unified storage, and accelerated compute. It highlights three pillars for success: consistent performance, predictable scaling, and long-term cost efficiency, addressing the complexities of AI workloads in production.
NVIDIA Warp: Differentiable Physics Simulation for AI Training on GPU
NVIDIA Warp is a framework for GPU-accelerated, differentiable physics simulation. It enables writing high-performance kernels in Python, with automatic differentiation, and integrates with PyTorch/JAX. The 2D Navier-Stokes example demonstrates end-to-end optimization, reducing the cost of generating training data for physics AI.
Introducing The Anthropic Institute \ Anthropic
AnnouncementsIntroducing The Anthropic InstituteMar 11, 2026We’re launching The Anthropic Institute, a new effort to confront the most significant challenges that powerful AI will pose to our societie...
NVIDIA Extends CUDA Tile Programming Model to Julia Language
NVIDIA introduces its CUDA Tile high-level GPU programming model to the Julia ecosystem via the cuTile.jl package. This move aims to lower the barrier to high-performance GPU kernel development by abstracting low-level thread and memory management with a tile-based data model, while maintaining high syntax and performance parity with the Python version.