Reports
AI-generated structured vendor updates
Google Launches Gemma 4 Open Model Family
Google introduces Gemma 4 open model family with four size variants, optimized for edge and mobile devices. The series supports multimodal processing, long context windows and 140+ languages under Apache 2.0 license.
Cisco Launches Validated AI Infrastructure Solution
Cisco introduced validated AI infrastructure designs in collaboration with NVIDIA and Red Hat, offering pre-integrated AI POD solutions to address compatibility and security challenges in enterprise DIY AI infrastructure. The solution encompasses complete compute, networking, storage and AI software stacks with modular scalability.
AMD Announces Breakthrough MLPerf Inference 6.0 Results, Showcasing Multinode Scaling and Multimodal Capabilities
AMD's MLPerf Inference 6.0 submission, powered by Instinct MI355X GPUs, surpassed 1 million tokens per second for the first time on models like Llama 2 70B and GPT-OSS-120B. The results highlight efficient multinode scaling, rapid enablement of new workloads (e.g., text-to-video model Wan-2.2-t2v), and reproducible performance across a broad partner ecosystem.
ARM Launches AGI CPU Silicon, Extends AI Infrastructure Reach
ARM debuts its first self-designed AGI CPU silicon, moving beyond IP licensing to offer full-stack solutions from custom silicon to integrated platforms. This shift redefines control points in AI infrastructure supply chains, enabling enterprises to optimize AI workload deployment at hardware layer.
Intel Demonstrates AI Performance with Xeon 6 and Arc Pro GPUs in MLPerf Inference
Intel showcased the performance of its Xeon 6 CPUs and Arc Pro B-Series GPUs in the MLPerf Inference v6.0 benchmarks, particularly in handling large language models (LLMs). The results indicate that a system with four Arc Pro B70 GPUs can process 120B parameter models, delivering up to 1.8x higher inference performance in multi-GPU setups.
NVIDIA Collaborates with Energy Leaders to Position AI Factories as Smart Grid Assets
NVIDIA, in collaboration with Emerald AI, proposes treating large-scale AI data centers (AI factories) as flexible, intelligent grid assets rather than static power loads. This architecture integrates accelerated computing, power networking, and control to enhance grid reliability and optimize energy efficiency. Several major energy companies plan to collaborate on this architecture to support AI workloads and accelerate power connection.
NVIDIA Collaborates with Energy Leaders on AI Factory-Grid Integration Architecture
NVIDIA and Emerald AI introduced a new architecture treating AI factories as intelligent grid assets, combining accelerated computing, real-time energy orchestration and reference designs. The Vera Rubin DSX-based approach enables dynamic grid response and has gained support from multiple energy providers.
Arm Expands into Silicon Products with First Self-Designed AGI CPU
Arm is expanding its compute platform into production silicon for the first time, launching the self-designed Arm AGI CPU for AI data centers and agentic workloads. It targets over 2x performance per rack versus x86 platforms and is backed by lead partner Meta, customers like OpenAI, and a broad OEM/ODM ecosystem.
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.
NVIDIA Donates GPU Dynamic Resource Allocation Driver to Kubernetes Community
NVIDIA donated its GPU Dynamic Resource Allocation (DRA) driver to the CNCF, making it an upstream Kubernetes project. This move aims to shift the core control point of GPU orchestration from proprietary vendor layers to the open-source community, and drive standardization in collaboration with major cloud providers.
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 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.
Cisco Expands Secure AI Factory with NVIDIA to Edge and Security
Cisco expands its Secure AI Factory with NVIDIA to enable AI deployment from data centers to edge sites, adding security capabilities like firewall policy enforcement on DPUs and AI Defense integration, offering flexible architecture options to accelerate production scaling.
HPE Alletra MP X10000 Becomes First NVIDIA-Certified Object Storage Platform for Enterprise AI
HPE announces its Alletra Storage MP X10000 is the first object-based platform certified by NVIDIA for enterprise AI. This signifies the extension of AI performance certification standards from the compute layer to the data layer, aiming to address data access bottlenecks in large-scale AI training, fine-tuning, and inference.
Trend Micro Report Highlights AI Supply Chain Risks and Model Attack Surfaces
Trend Micro's 'Fault Lines in the AI Ecosystem' report systematically analyzes security risks in the AI supply chain, including training data poisoning, third-party plugin vulnerabilities, and model theft attacks. It indicates that enterprise AI security boundaries have expanded from traditional IT infrastructure to the model layer and data pipelines.