The deal marks a strategic move to bolster Qualcomm’s AI and custom silicon capabilities amid challenging competition and the potential start of a wave of AI silicon acquisitions.
A new partnership combines WEKA’s AI-native storage with Nebius’ GPUaaS platform to accelerate model training, inference, and innovation with microsecond latency and extreme scalability.
As the battle for AI market share continues, AMD’s recent acquisitions signal a strategic move toward optimizing both software and hardware for inference workloads and real-world AI deployment.
The HPE-owned platform combines unified observability, smart alert correlation, and automation to tackle hybrid IT complexity while also working with existing monitoring tools.
AIStor’s stateless, gateway-free design solves legacy storage issues, enabling high-performance object-native infrastructure for exabyte-scale AI and analytics workloads.
Amber Huffman and Jeff Andersen of Google join Allyson Klein to discuss the roadmap for OCP LOCK, post-quantum security, and how open ecosystems accelerate hardware trust and vendor adoption.
Enterprise AI doesn’t create fragility; it reveals undocumented assumptions, missing ownership, and invisible pipeline debt. Fix the foundations and AI gets cheaper, faster, and more trusted.
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.
In this podcast, MLCommons President Peter Mattson discusses their just-released AILuminate benchmark, AI safety, and how global collaboration is driving trust and innovation in AI deployment.
In this episode, Eric Kavanagh anticipates AI's evolving role in enterprise for 2025. He explores practical applications, the challenges of generative AI, future advancements in co-pilots and agents, and more.
Peter Dueben of European Centre for Medium-Range Weather Forecasts explores the role of HPC and AI in advancing weather modeling, tackling climate challenges, and scaling predictions to the kilometer level.
David Kanter discusses MLCommons' role in setting benchmarks for AI performance, fostering industry-wide collaboration, and driving advancements in machine learning capabilities.
Join Allyson Klein and Jeniece Wnorowski in this episode of Data Insights as they discuss key takeaways from the 2024 OCP Summit with Scott Shadley, focusing on AI advancements and storage innovations.
Jonathan Koomey of Koomey Analytics shares insights on AI’s role in energy efficiency, sustainability, and the tech sector’s potential to address climate challenges in this must-listen episode.