AI (Artificial Intelligence)

Auto Added by WPeMatico

The Kubernetes Cathedral: Why Enterprise Cloud-Native Platforms Need More Than a Cluster

ai, AI (Artificial Intelligence), Artificial Intelligence, VCF (Cloud Foundation), vCF (VMware Cloud Foundation)

TL;DR Kubernetes provides the orchestration core for containerized workloads, but an enterprise Kubernetes platform requires much more than a functioning cluster. Identity, networking, GitOps, software supply-chain controls, certificate management, observability, resilience, cost governance, and operational ownership must work as one system. AKS, EKS, and other managed Kubernetes services can reduce infrastructure management effort, but they […]

The Kubernetes Cathedral: Why Enterprise Cloud-Native Platforms Need More Than a Cluster Read More »

Pakistan joins China Moon race with Jinnah-1 rover; mission in 2029

ai, AI (Artificial Intelligence), Artificial Intelligence

Pakistan has named its first lunar rover Jinnah-1 for a 2029 mission. The rover will join China’s Chang’e-8 mission to study the Moon’s south pole. Jinnah-1 will conduct scientific research on plasma, radiation, and lunar geology. This collaboration marks a significant milestone for Pakistan’s space program. The mission aims to explore the lunar south pole’s

Pakistan joins China Moon race with Jinnah-1 rover; mission in 2029 Read More »

How to Configure GPUDirect RDMA and Prove Multi-Node GPU Performance with NCCL

ai, AI (Artificial Intelligence), AI & Machine Learning, AI & ML, AI & Society, AI 2025 trends

TL;DR A working GPU driver, an RDMA device inside a pod, and a completed NCCL test do not prove that GPUDirect RDMA is working efficiently. Production validation must prove the complete path: GPU topology, GPU-to-NIC affinity, PCIe peer access, IOMMU and ACS behavior, RDMA fabric health, container resource exposure, NCCL transport selection, and repeatable multi-node

How to Configure GPUDirect RDMA and Prove Multi-Node GPU Performance with NCCL Read More »

Meet Needle 2: An Open 45M-Parameter Tool-Calling Model That Ships as a 14MB Binary and Runs a Full Session in 28MB of RAM

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Open Source, Software engineering, Staff, Tech News, Technology, Uncategorized

Cactus Compute has released Needle 2, an open 45M-parameter model for tool calling, device use, and structured extraction. The entire model ships as a single 14MB binary that runs a full session in about 28MB of RAM. Weights are trained and deployed at CQ2-bit using Cactus Quants, and the model is sealed inside the company’s

Meet Needle 2: An Open 45M-Parameter Tool-Calling Model That Ships as a 14MB Binary and Runs a Full Session in 28MB of RAM Read More »