In Part 2 of Matty Bakkeren’s 2026 predictions series, he explores how regulation, sovereignty, and public trust will push data centers to behave more like utilities than tech projects.
Marvell is inking a deal for optical interconnect startup Celestial AI in a massive bet that the industry has shifted from being compute-constrained to bandwidth-constrained.
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.
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.