Reports
AI-generated structured vendor updates
AMD and OpenAI Contribute MRC Protocol to OCP for Scalable AI Networking
AMD, in collaboration with OpenAI, Microsoft, and others, contributed the MRC (Multipath Reliable Connection) protocol, designed for large-scale AI training, to the Open Compute Project (OCP). AMD co-authored the specification and has already deployed MRC on its programmable Pensando DPU/NIC products, positioning its networking technology as a key enabler for resilient and adaptive AI infrastructure.
NVIDIA Opens MRC Protocol via OCP, Pushing Standardization of AI Ethernet Fabrics
NVIDIA announced the opening of its MRC (Multipath Reliable Connection) RDMA transport protocol via the Open Compute Project (OCP). The protocol, proven on Spectrum-X Ethernet hardware, aims to enhance throughput, resilience, and GPU utilization for large-scale AI training clusters through multi-path load balancing and hardware-level failure bypass.
AMD and OpenAI Introduce MRC, a Next-Gen Transport Protocol for AI Training
AMD, in collaboration with OpenAI, Microsoft, and other industry leaders, has released the specification for the Multipath Reliable Connection (MRC) protocol. MRC addresses performance bottlenecks of RoCEv2 in hyperscale AI training clusters through intelligent packet spraying, selective retransmission, and network-signaled congestion control, aiming to improve bandwidth utilization and job resilience.
AMD Showcases Heterogeneous Computing Strategy for Enterprise AI with Dell
At Dell Technologies World, AMD highlighted its heterogeneous computing portfolio, aiming to match the right compute engine to specific enterprise AI workloads, while emphasizing hardware-based security and manageability. This signals a shift in AI infrastructure from generic solutions to fine-tuned, scenario-specific deployments.
AMD Proposes New AI Infrastructure Networking Paradigm: From Lossless Fabrics to Intelligent Endpoints
AMD published a blog outlining seven key questions for building large-scale AI infrastructure, arguing that traditional lossless Ethernet or InfiniBand architectures face cost and complexity bottlenecks. It advocates shifting network intelligence and reliability functions from expensive, specialized switches to intelligent NICs, enabling reliable transport over standard (potentially lossy) Ethernet to reduce TCO and simplify operations.
AMD and Liquid AI Discuss Efficient AI Architecture from Silicon to Systems
AMD's CTO and Liquid AI's CEO discuss the evolution of AI architecture, emphasizing efficiency as key to extending AI from the cloud to edge and endpoint devices. They argue that co-design from silicon to systems enables low-power, responsive AI inference, supporting always-on agents and multi-model orchestration.
AMD Extends Edge AI Architecture to Space, Defining Orbital Computing Paradigm
AMD's CTO proposes applying the core principles of 'performance-per-watt' and 'mission-critical reliability' from terrestrial edge AI to space computing. The company is providing a repeatable platform foundation for in-orbit satellite intelligence and future orbital data centers through heterogeneous computing, open software stacks, and modular system design.
AMD Highlights AI PC as Critical Infrastructure for Enterprise Agentic AI in IDC White Paper
AMD released an IDC white paper indicating that over 80% of enterprises are planning, piloting, or deploying AI PCs to support scaled Agentic AI. The report highlights high-performance NPUs and on-device AI processing as critical for enabling real-time, secure workflows, signaling a shift in enterprise AI infrastructure from cloud to endpoint.
Google Cloud Next '26: Agent Gateway Seizes Control Plane, TPU 8i Locks Inference
Google Cloud Next '26 announces 8th-gen TPUs (8t for training, 8i for inference), Agent Platform with Agent Gateway, Agent Identity, Agent-to-Agent Orchestration, Agentic Data Cloud, and Agentic Defense integrating Wiz. The move shifts control from infrastructure to agent orchestration, locking enterprises into a vertically integrated stack.
Google Launches Gemma 4 Open Models, Targeting Edge Inference and AI Agent Architecture
Google introduces the Gemma 4 open model family, with four sizes from 2B to 31B parameters, emphasizing breakthrough intelligence-per-parameter and native support for agentic workflows, multimodality, and long context. The small models are engineered for edge devices, aiming to bring frontier reasoning to mobile and IoT scenarios.
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.
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.
AMD Achieves Breakthrough MLPerf Inference Results
AMD reports its Instinct MI300X accelerators achieved outstanding performance in MLPerf Inference 6.0 benchmarks, setting new records in natural language processing tasks. This demonstrates AMD's growing technical competitiveness in AI inference infrastructure.
AMD Highlights Use of Its High-Reliability Compute Products in Space Missions
AMD published a promotional article highlighting that its processors and FPGAs have provided compute support for multiple space missions, including NASA's lunar rovers and landers. The article aims to demonstrate the reliability and durability of its products in extreme environments.
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.
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.
SK Hynix Jumps to TSMC 3nm for HBM4E Logic Die to Counter Samsung's 4nm Lead
SK Hynix plans to use TSMC's 3nm process for the logic die in its 7th-gen HBM4E, a leap from the 12nm used in HBM4. This aims to reverse the performance gap with Samsung (which used 4nm logic in HBM4) and deliver higher bandwidth and power efficiency for next-gen AI chips like NVIDIA's Vera Rubin Ultra.
AMD Defines Agent Computer Vision for Edge AI Architecture
AMD releases 2026 AI PC roadmap, proposing Agent Computer concept with expanded Ryzen AI stack featuring NPU-GPU-CPU heterogeneous architecture. Enables local multimodal AI agents, shifting PC from productivity tool to proactive AI partner.
AMD and Celestica Launch Rack-Scale AI Platform Helios
AMD partners with Celestica to launch Helios rack-scale AI platform, integrating Instinct accelerators and EPYC processors for chip-to-rack optimization. The platform targets AI training and inference workloads with performance and efficiency enhancements for data center and cloud providers.
AMD Highlights CPU's Critical Role in Agentic AI Orchestration and Inference
AMD states Agentic AI workloads require serial decision-making and context management, better suited for CPUs. The company emphasizes high-core-count, high-memory-bandwidth server CPUs will lead in agent orchestration and lightweight inference, complementing GPUs in training. This signals a strategic repositioning of CPUs in AI data center architecture.