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.
Two new genAI tests (Llama 3.1 8B, Flux.1) align with production stacks as multi-node results climb. NVIDIA posts many fastest times; University of Florida, Wiwynn, and Datacrunch expand the ecosystem.
Allyson Klein talks with author and Google/Intel alum Wanjiku Kamau on moving past AI skepticism, learning fast, and using new tools with intention—so readers start where they are and explore AI with hope.
AI racks are blowing past air’s limits. Here’s a frank framework for when cold plate still wins, when it fails, and how to plan the pivot to immersion—without stranding today’s investments.
On Day 1 of KubeCon + CloudNativeCon Atlanta, CNCF unveiled Kubernetes AI Conformance to make workloads portable—arriving as inference surges to ~1.33 quadrillion tokens/month across Google’s systems.
FinTech expert Anusha Nerella shares insights on staying ahead of fraud, navigating regulation, and building collaborative teams to scale responsible AI across the financial services sector.
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.