As AI training pushes data centers to unprecedented power densities, researchers reveal an affordable solution that lets computing thrive on fluctuating renewable energy.
In Part 1 of Voice of Innovation Matty Bakkeren’s 2026 predictions series, he explores how AI, power, cooling, and supply chains are reshaping data center infrastructure for a utility-scale future.
As up to 10 million jobs disappear and quality content moves behind paywalls, the question isn’t if AI will reshape society. It’s whether 2026 is the year we’ll control the burn or watch it spread.
New liquid cooling solutions have created a critical new system for data centers, and the company's “magic dust” additive packages are proving essential to keep AI running.
Intel veteran and Machani Robotics CSO/CTO Niv Sundaram, one of TechArena’s newest voices of innovation, talks emotionally intelligent AI, companion humanoids, and why real innovation starts and ends with human wellbeing.
With AI racks exceeding 100kW, immersion cooling isn’t optional anymore. Midas’s operator-driven design delivers hot-swappable maintenance and thermal recovery economics.
From GPU and storage servers to turnkey rack-scale solutions, Giga Computing showcases its expanding OCP portfolio and the evolution of Giga PODs for high-density, high-efficiency data centers.
Open Compute EMEA Summit featured announcements of major rack and power architecture innovations that address AI-driven data center challenges with advanced cooling and engineering solutions.
From 122TB QLC SSDs to rack-scale liquid cooling, Solidigm and Supermicro are redefining high-density, power-efficient AI infrastructure—scaling storage to 3PB in just 2U of rack space.
At NVIDIA’s GTC, Supermicro and Solidigm showcased advanced storage and cooling technologies, addressing the growing demands of AI and data center infrastructure.
At OCP Dublin, Bel Power’s Cliff Gore shares how the company is advancing high-efficiency, high-density power shelves—preparing to meet AI’s demand for megawatt-class rack-scale infrastructure.
At OCP Dublin, ZeroPoint’s Nilesh Shah explains how NeoCloud data centers are reshaping AI infrastructure needs—and why memory and storage innovation is mission-critical for LLM performance.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.