In 2025, the internet’s fragility and AI’s complexity collided in public. The big vendors responded by buying the pieces they need to sell the integrated story that they have AI risk under control.
Robots aren’t going to fold your laundry by February. But Voice of Innovation Niv Sundaram predicts that an urgent caregiver shortage will move humanoids “from warehouses to living rooms” in 2026.
From circularity to U.S. assembly, Giga Computing lays out a rack-scale roadmap tuned for the next phase of AI—where inference drives scale and regional supply chains become a competitive edge.
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.
At Commvault SHIFT, “ResOps” and AI resilience were framed as the next operating model for enterprises facing AI-driven threats and cloud sprawl, raising the bar for what “clean” recovery should mean.
AI is turning product development into a living, experiment-led system, where causal inference, data and automation form a feedback loop that learns from releases to build smarter products faster.
From WEKA’s memory grid and exabyte storage to 800G fabrics, liquid-cooled AI factories, edge clusters, and emerging quantum accelerators, SC25 proved HPC is now about end-to-end AI infrastructure.
Stepping into a new cybersecurity leadership role, the smartest first move isn’t a new tool or policy, but questions. Use these 15 to map risk, culture, and influence before you start changing anything.
At KubeCon + CloudNativeCon in Atlanta, Devtron, Komodor, and Dynatrace showed how AI is reshaping Kubernetes ops—from self-healing fleets + spot-friendly migration to AI observability + business ROI.
CNCF + SlashData’s latest report counts 15.6M cloud-native developers as IDPs pull backend teams into the fold; hybrid + multi-cloud rise with AI demand while inference stacks + agentic frameworks coalesce.
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.