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.
Storage Is the Catalyst Revolutionizing Enterprise AI
Learn how Solidigm SSDs are delivering 10x-20x performance gains and 40% cost savings for enterprise AI during Supermicro’s Open Storage Summit this August.
GPT-5 Lands With Market-Leading Performance, a Nod to Openness
OpenAI’s GPT-5 outperforms rivals in coding, context retention, and accuracy—setting a new bar for enterprise AI while signaling a subtle shift toward openness.
Mid-Year Report: AI’s Biggest 2025 Surprises Revealed
Market share shakeups, pricing shocks, and a tectonic shift in the open internet: Intel’s Lynn Comp unpacks developments in AI trends in 2025 that no one could have predicted.
MLPerf Storage v2.0 Eclipses Records in AI Benchmarking
Global surge in submissions reveals the pivotal role of storage in scaling AI training, with new checkpoint tests tackling failure resilience in massive accelerator clusters.
MLCommons Raises the Bar for AI PCs with MLPerf Client v1.0
MLCommons launches industry-standard benchmarks for LLM performance on PCs, cutting through marketing hype and giving developers and enterprises the transparent metrics they need.
AI’s New Canvas: The Visual Creators in the Zoo
From Midjourney to Firefly, Part 2 of our ‘AI Zoo’ series breaks down how today’s top image models work—and how TechArena uses them to create powerful, responsible visuals.
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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.
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.
Data Insights at OCP: DataraAI on Edge Robotics
Durgesh Srivastava unpacks a data-loop approach that powers reliable edge inference, captures anomalies, and encodes technician know-how so robots weld, inspect, and recover like seasoned operators.
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.
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.
Data Insights at OCP: DataraAI on Edge Robotics
Durgesh Srivastava unpacks a data-loop approach that powers reliable edge inference, captures anomalies, and encodes technician know-how so robots weld, inspect, and recover like seasoned operators.
