Product marketers have long relied on NIST for clarity and consistency — but with new frameworks emerging for AI, it's time to ask whether these guidelines go far enough in prioritizing fairness, safety, and accuracy.
At GTC 2025, a discussion between Deloitte and VAST showed how their partnership is scaling enterprise AI with secure, auditable infrastructure—bringing business value for next-gen, agentic AI adoption.
Verge.io’s George Crump shares how a unified infrastructure approach is driving efficiency, performance, and AI-readiness — without the legacy bloat.
At GTC 2025, Nebius and VAST shared how their collaboration delivers high-performance, scalable AI infrastructure for enterprise workloads—making cloud AI more usable and accessible.
MLPerf Inference 5.0 signals the rise of large language models, with LLAMA 2 70B surpassing ResNet-50 in submissions and driving next-gen AI performance across compute platforms.
MemryX, a provider of edge AI acceleration hardware, recently closed its latest round of funding, serving as a potential bellwether for the next growth edge in AI compute.
As AI drives power demands sky-high, hyperscale leaders share opportunities, obstacles, and the urgent path forward for immersion cooling adoption.
MLCommons launches MLPerf Automotive v0.5, the first standardized benchmark suite to measure real-world AI performance in safety-critical automotive applications.
From predicting sepsis before symptoms appear to enabling rural clinics to make specialist-level diagnoses, a privacy-first approach to AI in health care promises to transform lives.
Surveying 250 IT pros, we found 29% already run SSDs beyond performance tiers, 81% would migrate when TCO wins, and storage innovation is a top lever to free power and space across the data center.
PowerScale delivers unmatched performance and scale for AI-driven transformation, while 122TB drives reshape enterprise infrastructure, proving storage is AI’s competitive edge in today’s data era.
From Intel’s layoffs to stealth automation, AI is reshaping work at a pace that outstrips human adaptation—driving record stress, uneven gains, and a scramble to reskill before the next downturn hits.
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.