AI
articles
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.
Under the Hood: The Alphabet Soup of Car Connectivity
Modern software-defined cars blend multiple links—CAN/LIN, MIPI, SerDes, and Ethernet/TSN—to shrink wiring and cost, manage EMI, and deliver reliable, deterministic timing from sensors to actuators.
Agentic AI in Engineering: From Vision to Workforce Transformation
At the crossroads of Synopsys and Microsoft innovation , agentic AI is no longer a future vision – it’s a catalyst for technical acceleration and a redefinition of engineering roles.
Ansys + Rohde & Schwarz: Hardware Meets Virtual Cities
Through digital twin modeling and hardware testing, this Ansys and Rohde & Schwarz collaboration empowers developers to optimize RF systems in lab environments with real-world fidelity.
Stanford’s Daniel Wu on Trust, Agents & the Future of AI
From agentic and embodied AI to trust and human capacity, Stanford’s Daniel Wu shares how infrastructure and intentionality will shape the next era of AI transformation.
From GPU to Model: Together AI Powers the AI Pipeline
From open-source models to enterprise partnerships, Together AI drives multidimensional growth — accelerating adoption, engagement, and impact across the entire AI development lifecycle.
Mid-Year Report: Semiconductor Shakeout Reshapes Auto Tech
Robert Bielby assesses his 2025 predictions for the automotive industry and examines Intel’s exit, China’s BYD beating Tesla, German market woes, and 8K display adoption.
Silicon Shakeups & More: Allyson Klein's 2025 Predictions Scorecard
From AI scandals to quantum breakthroughs, Allyson Klein shares what’s tracking with her 2025 tech forecast — and what caught her off guard halfway through the year.
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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.
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.
Data Insights at OCP: DataraAI on Edge Robotics
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.
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.
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.
Data Insights at OCP: DataraAI on Edge Robotics
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.
