Infrastructure

AI21 trumpets zero manual GPU negotiations after adopting Kueue on GKE, but the real story is a mix of genuine gains, vendor‑specific dependencies, and unresolved fragmentation that SaaS operators should scrutinize before copying the playbook.

Google promises persistent, cross-device AI memory that stays private by keeping decryption keys on user devices. We break down the tech, the trade-offs, and what it means for enterprise AI budgets.

NVIDIA's new qualification program certifies power and cooling gear for its AI factory reference designs — if you build exactly their way, with their blessed vendors.

NVIDIA bets its Halos stack is the only way to deploy physical AI without regulatory annihilation. The vendors lining up suggest they're right.

Samsung plans to more than double HBM4 and HBM4E output next year, pushing 12-layer stacks to 80% of shipments. Your AI infrastructure bill just found a new reason to cry.

Google's open-agentic orchestrator AX promises to tame runaway agent costs and state management with declarative primitives. But does it solve real ops pain or just add another YAML layer?

Classic benchmarks measure throughput on empty disks. This project tests what actually kills production: snapshot aging, ENOSPC behavior, corruption self-healing, and fsync tail latency.

Vendor SLAs promise uptime; OONI's crowdsourced probes show you which governments actually flipped the kill switch. Run it or guess.

OpenAI says its first AI accelerator, Jalapeño, was cooked up with its own LLMs in under 20 months. We peel back the performance claims, the design shortcuts, and what it really means for your inference budget.

DDR5’s on‑die ECC promises relief but falls short of true server‑grade protection, leaving cost and risk trade‑offs for IT teams.

The latest MCP roadmap promises stateless scalability and agent‑centric features, but many of its headline items recycle past work while leaving real‑world security and operational gaps unaddressed.

Explanation of everything you can see in htop/top on Linux, including load averages, process states, and memory usage.

The author delves into the complexities of reporting free or used memory in modern operating systems, specifically FreeBSD, and discovers issues with the `btop` tool. A fix is proposed and implemented, providing a more accurate representation of memory usage.

Exploring alternatives to run CUDA on non-Nvidia hardware, including HIP, SYCL, and ROCm.

A new MPMC queue design ensures bounded waiting times, preventing starvation and ensuring efficient data transfer between producers and consumers. The queue's performance has been benchmarked, showing promising results.