AI
articles
How Health Technology Innovations, Inc. is using AI to accelerate pharma research
Discover how AI is transforming pharma research, accelerating drug development, and reducing costs. This blog highlights key innovations like Health Technology Innovations, Inc.'s Cryo-FAST platform, which speeds up early-stage research. Learn about AI's impact through real-world examples of collaboration and implementation.
Sema4.ai Delivers Agents of Change
The pace of AI innovation is accelerating, and Sema4.ai’s vision goes beyond large language models (LLMs) to the transformative potential of AI agents. These agents, unlike traditional software, complete tasks autonomously, acting as knowledge workers that can reason, collaborate, and deliver work products. Sema4 pioneers this technology, offering AI agents optimized for specific industries, enhancing productivity significantly.
Cornelis Networks Aims for AI Fabric Growth with Lisa Spelman at the Helm
Lisa Spelman introduced as new CEO of Cornelis Networks
Advanced Semiconductor Packaging: The Secret Hero for the AI Infrastructure Era
Unveiling the Role of Advanced Semiconductor Packaging in Powering AI: Explore the innovations in 2.5D and 3D packaging, high bandwidth memory, and chiplet solutions driving AI infrastructure into the future.
Microsoft Stuns with Speed of AI Innovation and Integration at MS Build
TechArena’s take from Satya Nadella’s keynote at MSBuild 2024. This post covers infrastructure, silicon collaborations and service delivery.
The Rise of Custom Silicon in the Generative AI Era: An Interview with Alphawave Semi's Mohit Gupta
TechArena’s take on custom silicon advancements in the AI era with Alphawave Semi.
15 Questions Every Cybersecurity Leader Should Ask on Day One
Stepping into a new cybersecurity leadership role, the smartest first move isn’t a new tool or policy, but questions. Use these 15 to map risk, culture, and influence before you start changing anything.
Inside KubeCon 2025: How AI Is Rewriting Kubernetes Operations
At KubeCon + CloudNativeCon in Atlanta, Devtron, Komodor, and Dynatrace showed how AI is reshaping Kubernetes ops—from self-healing fleets + spot-friendly migration to AI observability + business ROI.
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.
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Podcasts
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.
Cornelis Networks & AMD on Scaling AI Without the Chaos
From CPU orchestration to scaling efficiency in networks, leaders reveal how to assess your use case, leverage existing infrastructure, and productize AI instead of just experimenting.
Cornelis and OCP Examine Why AI Infrastructure Must Evolve
From the OCP Global Summit, hear why 50% GPU utilization is a “civilization-level” problem, and why open standards are key to unlocking underutilized compute capacity.
How Axelera Scales Inference From Edge to Data Center
In the Arena: Allyson Klein with Axelera CMO Alexis Crowell on inference-first AI silicon, a customer-driven SDK, and what recent tapeouts reveal about the roadmap.
Data Insights: AI in Healthcare with Dr. Rohith Vangalla
In this episode of Data Insights, host Allyson Klein and co-host Jeniece Wnorowski sit down with Dr. Rohith Vangalla of Optum to discuss the future of AI in healthcare.
Metrum AI’s Steen Graham on Multi-Agent AI and Smarter Storage
From OCP Summit, Metrum AI CEO Steen Graham unpacks multi-agent infrastructure, SSD-accelerated RAG, and the memory-to-storage shift—plus a 2026 roadmap to boost GPU utilization, uptime, and time-to-value.
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.
Cornelis Networks & AMD on Scaling AI Without the Chaos
From CPU orchestration to scaling efficiency in networks, leaders reveal how to assess your use case, leverage existing infrastructure, and productize AI instead of just experimenting.
Cornelis and OCP Examine Why AI Infrastructure Must Evolve
From the OCP Global Summit, hear why 50% GPU utilization is a “civilization-level” problem, and why open standards are key to unlocking underutilized compute capacity.
How Axelera Scales Inference From Edge to Data Center
In the Arena: Allyson Klein with Axelera CMO Alexis Crowell on inference-first AI silicon, a customer-driven SDK, and what recent tapeouts reveal about the roadmap.
Data Insights: AI in Healthcare with Dr. Rohith Vangalla
In this episode of Data Insights, host Allyson Klein and co-host Jeniece Wnorowski sit down with Dr. Rohith Vangalla of Optum to discuss the future of AI in healthcare.
Metrum AI’s Steen Graham on Multi-Agent AI and Smarter Storage
From OCP Summit, Metrum AI CEO Steen Graham unpacks multi-agent infrastructure, SSD-accelerated RAG, and the memory-to-storage shift—plus a 2026 roadmap to boost GPU utilization, uptime, and time-to-value.
