AI
articles
AMD’s 38x Efficiency Leap Sets Stage for Ambitious 2030 Goal
AMD improved energy efficiency 38x—roughly a 97% drop in energy for the same compute—and now targets 20x rack-scale gains by 2030, reimagining AI training, inference, and data-center design.
Dell Highlights Four Shifts Powering the AI Storage Revolution
Dell outlines how flash-first design, unified namespaces, and validated architectures are reshaping storage into a strategic enabler of enterprise AI success.
5 Fast Facts on Compute Efficiency with Flex’s Chris Butler
Exploring how Flex is rethinking data center power and cooling – from 97.5% efficient power shelves to liquid cooling and “grid to chip” solutions – with Chris Butler, President of Embedded & Critical Power.
Innovation with Empathy: A Q&A with Vivek Venkatesan
Vanguard lead data engineer and IEEE senior member Vivek Venkatesan shares how a pivotal Botswana project shaped his path, how trust turns innovation into impact , and much more.
Mark Grodzinsky on Building Ecosystems That Last
From Wi-Fi to AI, Mark Grodzinsky shares how chance turns, mentors, and market inflection points shaped his career – and why true innovation is about impact, not hype.
Compass & Schneider Launch Prefab Pod for AI Data Centers
The new EcoStruxure™ Pod accelerates data center readiness, reducing complexity, cost, and risk while boosting sustainability and AI workload support.
PhoenixNAP's Bare Metal Cloud Meets AI's Data Center Demands
Allyson Klein reflects on her chat with PhoenixNAP’s Ian McClarty, covering AI's impact on data centers, the advantages of bare metal cloud, and the push for sustainable high-performance computing.
Why a Self-Driving Car Might Run a “STOB” Sign: To ViT or Not To ViT
Automotive expert Robert Bielby compares Convolutional Neural Networks and Vision Transformers in self-driving cars, discussing tradeoffs between the need for training data and accuracy, as well as the emergence of hybrid models.
Recap Report: 2024 AI Hardware and Edge AI Summit
Check out our in-depth look at key takeaways from AI Hardware and Edge AI Summit, highlighting how advancements in AI infrastructure, acceleration, and connectivity are transforming the future of computing.
Alphawave Semi Advances with New Solutions, Chiplet Innovation
Gain insights from Alphawave's Letizia Guiliano on revolutionizing AI infrastructure through high-speed interconnects, chiplet innovation, and open standards.
OmniPath Taking on InfiniBand for AI Fabric Leadership
Lisa Spelman leads Cornelis Networks to challenge NVIDIA with Omni-Path, offering AI infrastructures superior scalability, and a competitive edge for future-proofing next-gen AI deployments.
With Lemony, Uptime Industries Stacks Up AI at the Deskside
In a recent discussion with Sascha Buehrle of Uptime Industries, we explored how their Lemony platform brings scalable, secure, and accessible AI to the deskside for small and mid-sized businesses.
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Podcasts
How Hedgehog Brings Hyperscaler Networking to Enterprise AI
Hedgehog CEO Marc Austin joins Data Insights to break down open-source, automated networking for AI clusters—cutting cost, avoiding lock-in, and keeping GPUs fed from training to inference.
How Rose-Hulman Modernized Its Data Center for Student Success
Rose-Hulman Institute of Technology shares how Azure Local, AVD, and GPU-powered infrastructure are transforming IT operations and enabling device-agnostic access to high-performance engineering software.
Nebius at SC25: Building the Neocloud for Enterprise AI
From SC25 in St. Louis, Nebius shares how its neocloud, Token Factory PaaS, and supercomputer-class infrastructure are reshaping AI workloads, enterprise adoption, and efficiency at hyperscale.
Inside Runpod’s GPU Cloud for Long-Running AI Agents
Runpod head of engineering Brennen Smith joins a Data Insights episode to unpack GPU-dense clouds, hidden storage bottlenecks, and a “universal orchestrator” for long-running AI agents at scale.
Walmart and Cornelis Expose the Costs of Network Inefficiency
Billions of customer interactions during peak seasons expose critical network bottlenecks, which is why critical infrastructure decisions must happen before you write a single line of code.
Giga Computing on Rack-Scale AI: From Training to Inference
Recorded at #OCPSummit25, Allyson Klein and Jeniece Wnorowski sit down with Giga Computing’s Chen Lee to unpack GIGAPOD and GPM, DLC/immersion cooling, regional assembly, and the pivot to inference.
How Hedgehog Brings Hyperscaler Networking to Enterprise AI
Hedgehog CEO Marc Austin joins Data Insights to break down open-source, automated networking for AI clusters—cutting cost, avoiding lock-in, and keeping GPUs fed from training to inference.
How Rose-Hulman Modernized Its Data Center for Student Success
Rose-Hulman Institute of Technology shares how Azure Local, AVD, and GPU-powered infrastructure are transforming IT operations and enabling device-agnostic access to high-performance engineering software.
Nebius at SC25: Building the Neocloud for Enterprise AI
From SC25 in St. Louis, Nebius shares how its neocloud, Token Factory PaaS, and supercomputer-class infrastructure are reshaping AI workloads, enterprise adoption, and efficiency at hyperscale.
Inside Runpod’s GPU Cloud for Long-Running AI Agents
Runpod head of engineering Brennen Smith joins a Data Insights episode to unpack GPU-dense clouds, hidden storage bottlenecks, and a “universal orchestrator” for long-running AI agents at scale.
Walmart and Cornelis Expose the Costs of Network Inefficiency
Billions of customer interactions during peak seasons expose critical network bottlenecks, which is why critical infrastructure decisions must happen before you write a single line of code.
Giga Computing on Rack-Scale AI: From Training to Inference
Recorded at #OCPSummit25, Allyson Klein and Jeniece Wnorowski sit down with Giga Computing’s Chen Lee to unpack GIGAPOD and GPM, DLC/immersion cooling, regional assembly, and the pivot to inference.
