AI
articles
Cloud-Native 2025 by the Numbers: The Developer Tent Just Got Bigger
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.
MLPerf Training v5.1: GenAI Drives, Scale Ramps, Field Widens
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.
Wanjiku Kamau on Her Book: Out of the Loop, Into the Algorithm
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.
Cooling the Future: Where Does Cold Plate End and Immersion Begin?
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.
KubeCon Atlanta: CNCF Sets AI Standard for Kubernetes
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.
How Financial Services Can Responsibly Scale AI
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.
PhoenixNAP's Bare Metal Cloud Meets AI's Data Center Demands
Allyson Klein reflects on her chat with PhoenixNAP’s Ian McClarty, covering AI's impact on data centers, the advantages of bare metal cloud, and the push for sustainable high-performance computing.
Why a Self-Driving Car Might Run a “STOB” Sign: To ViT or Not To ViT
Automotive expert Robert Bielby compares Convolutional Neural Networks and Vision Transformers in self-driving cars, discussing tradeoffs between the need for training data and accuracy, as well as the emergence of hybrid models.
Recap Report: 2024 AI Hardware and Edge AI Summit
Check out our in-depth look at key takeaways from AI Hardware and Edge AI Summit, highlighting how advancements in AI infrastructure, acceleration, and connectivity are transforming the future of computing.
Alphawave Semi Advances with New Solutions, Chiplet Innovation
Gain insights from Alphawave's Letizia Guiliano on revolutionizing AI infrastructure through high-speed interconnects, chiplet innovation, and open standards.
OmniPath Taking on InfiniBand for AI Fabric Leadership
Lisa Spelman leads Cornelis Networks to challenge NVIDIA with Omni-Path, offering AI infrastructures superior scalability, and a competitive edge for future-proofing next-gen AI deployments.
With Lemony, Uptime Industries Stacks Up AI at the Deskside
In a recent discussion with Sascha Buehrle of Uptime Industries, we explored how their Lemony platform brings scalable, secure, and accessible AI to the deskside for small and mid-sized businesses.
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Podcasts
How Hedgehog Brings Hyperscaler Networking to Enterprise AI
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.
How Rose-Hulman Modernized Its Data Center for Student Success
Rose-Hulman Institute of Technology shares how Azure Local, AVD, and GPU-powered infrastructure are transforming IT operations and enabling device-agnostic access to high-performance engineering software.
Nebius at SC25: Building the Neocloud for Enterprise AI
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.
Inside Runpod’s GPU Cloud for Long-Running AI Agents
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.
Walmart and Cornelis Expose the Costs of Network Inefficiency
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.
Giga Computing on Rack-Scale AI: From Training to Inference
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.
How Hedgehog Brings Hyperscaler Networking to Enterprise AI
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.
How Rose-Hulman Modernized Its Data Center for Student Success
Rose-Hulman Institute of Technology shares how Azure Local, AVD, and GPU-powered infrastructure are transforming IT operations and enabling device-agnostic access to high-performance engineering software.
Nebius at SC25: Building the Neocloud for Enterprise AI
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.
Inside Runpod’s GPU Cloud for Long-Running AI Agents
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.
Walmart and Cornelis Expose the Costs of Network Inefficiency
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.
Giga Computing on Rack-Scale AI: From Training to Inference
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.
