Research Notes
Everpure: Data Intelligence and Data Stream Advance AI-Ready Data-Primacy
Everpure’s Data Stream and Data Intelligence automate AI data pipelines and governance. See how they compare to Dell, HPE, VAST Data, and NetApp.
Qualcomm Acquires Modular for its Hardware-Agnostic AI Software Layer
Qualcomm announced its intent to acquire Modular, an AI infrastructure software company, in a stock transaction valued at approximately $3.9 billion. The deal pairs Qualcomm’s silicon roadmap with Modular’s Mojo programming language and MAX inference engine, a software stack that runs AI models across CPU, GPU, NPU, and custom ASIC architectures without requiring per-accelerator rewrites.
HPE Discover: Agentic Governance, Vera CPU, and Confidential Computing added to AI Factory w/ NVIDIA
Hewlett Packard Enterprise extended its HPE AI Factory with NVIDIA to support production-ready agentic AI deployments at its just-wrapped HPE Discover 2026. The announcements add governance, security, and compute capabilities for organizations moving AI agents into operational production environments.
HPE Discover: Self-Driving Networks and AI Data Center Switching for the Agentic Enterprise
At its recent HPE Discover event in Las Vegas, Hewlett Packard Enterprise announced a broad set of networking updates spanning AI data center switching, autonomous network operations, and unified secure access, extending its “self-driving” networking strategy into general availability across AI factories, data centers, campus, and edge environments.
Arista Networks’ Next-Generation 1.6 Terabit Portfolio for AI Fabrics
Arista Networks recently announced its new 7060XE7 Series, a portfolio of 1.6 Terabit (1.6T) Ethernet switching platforms designed for rack-scale AI infrastructure. The announcement extends Arista’s Etherlink architecture from 800G to 1.6T and introduces three hardware configurations for air-cooled, liquid-cooled, and high-density 128-port deployments.
IBM’s LLM-Guided Evolutionary Framework for Quantum Error Correction Code Discovery
IBM Research recently published a paper on an LLM-guided evolutionary framework for discovering quantum error-correction (QEC) codes, accompanied by the open-source release of OpenEvolve on GitHub. The framework applies evolutionary artificial intelligence techniques, originally developed for general program synthesis, to the domain of quantum low-density parity-check (qLDPC) codes.
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