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 GTC DC, NVIDIA outlined DOE-scale AI systems, debuted NVQLink to couple GPUs and quantum, partnered with Nokia on AI-RAN to 6G, mapped Uber robotaxis for 2027, and highlighted Synopsys’ GPU gains.
Storage architecture becomes the invisible force determining whether AI deployments, now rapidly moving beyond pilot projects, generate profit or burn cash on throttled tokens.
While enterprises pour resources into more GPUs, up to 30% of that computing power sits idle waiting for data. The solution isn't more hardware; it's smarter network architecture.
Design shifted to rack-scale. Power and cooling span the full path. Liquid is table stakes. Three takeaways from OCP 2025—and why CelLink’s PowerPlane fits an AI-factory mindset.
Converging forces, including affordable SSDs, ransomware requiring fast restoration capabilities, and AI workloads needing assured data integrity, are redefining protection strategies at unprecedented scale.
From analytics to AI leadership, TechArena Voice of Innovation Banani Mohapatra (Walmart) shares how experimentation, ethics, and human creativity shape the next era of data-driven innovation.
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.