Research Notes
Research Note: VAST Data/Cisco AI Collaboration
VAST Data and Cisco announced a new collaboration to deliver a robust, high-performance AI data infrastructure that integrates seamlessly with an Ethernet-based AI fabric designed to handle data at an exabyte scale. Each company brings specialized expertise to create a unified, high-performance AI data platform.
Research Note: Fortinet Acquires Lacework
Fortinet, a converged networking and security market player, announced its definitive agreement to acquire Lacework, a data-driven cloud security company known for its AI-powered platform. This acquisition will bolster Fortinet’s already robust Security Fabric, delivering enhanced security solutions from code to cloud for its vast customer base.
Research Note: AMD Computex MI325x & MI350 Accelerator Announcements
At the 2024 Computex event in Taiwan, AMD CEO Lisa Su revealed details about AMD’s upcoming MI350 and MI325X accelerators, follow-ons to its current MI300x products, highlighting significant advancements in AI performance and memory capacity. The new products are positioned as key components in AMD’s strategy to lead the AI accelerator market.
Research Note: Red Hat Summit 2024 AI Announcements
At its recent Red Hat Summit, Red Hat announced several new products and enhancements, many of which simplify or enable the use of AI within the enterprise. These include its new OpenShift AI, OpenShift LightSpeed enhancements, and a new RHEL AI release.
Research Note: UALink Alliance & Accelerator Interconnect Specification
UALink is a new open standard designed to rival NVIDIA’s proprietary NVLink technology. It facilitates high-speed, direct GPU-to-GPU communication crucial for scaling out complex computational tasks across multiple graphics processing units (GPUs) or accelerators within servers or computing pods.
Research Note: IBM InstructLab LLM Tool Kit
At IBM’s 2024 Think conference in Boston, IBM Research unveiled InstructLab, developed in collaboration with Red Hat, to address the inefficiencies of existing training approaches by enabling collaborative, cost-effective model customization.