As AI reshapes compute, memory, and networking, chipmakers are racing to rethink design workflows, embrace agentic AI, and overcome the next wave of data, power, and talent constraints.
From Chinese hackers hiding in US power grids for 300 days to AI agents that fight back autonomously, security expert Sean Grimaldi reveals which 2025 predictions hit, and what’s coming next.
OnLogic's Hunter Golden reveals how enterprises can deploy effective AI at the edge with right-sized hardware, lower costs, and even better performance than cloud alternatives.
Gina Rosenthal discusses how AI is transforming everything from cybercrime and fraud detection to government operations this year, revealing both breakthrough innovations and costly failures.
The merger creates a “silicon to systems” engineering powerhouse, unifying chip design and simulation to tackle AI complexity and reshape the future of smart product development.
Matty Bakkeren checks in on how data center trends are playing out in 2025, from nations pouring billions into AI supremacy projects to how data centers are trying to offset massive energy needs.
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.
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.
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.