Tech World

A new analysis puts a hard number on a long-standing caveat in brain imaging: roughly 40% of the fMRI BOLD signal appears to come from non-neural sources like head motion, respiration, cardiac pulsation, large-vessel dynamics, and scanner drift. Under the hood, the work partitions variance across datasets and preprocessing pipelines,

Formal verification has long been powerful but impractical for most teams-too much spec-writing, too many arcane tactics. What’s notable here is that AI is chipping away at those barriers by handling the grunt work: proposing invariants and lemmas, translating requirements into machine-checkable specs, and iterating with solvers until a

GitHub plans to start charging for self-hosted Actions runners in March 2026, a notable shift for teams that have leaned on custom runners to control environments, improve performance, or dodge per-minute fees on GitHub-hosted compute. What’s notable here is the long runway: roughly a year-plus for organizations to inventory

A new analysis estimates that a substantial share of fMRI’s BOLD fluctuations-on the order of 40%-tracks physiology rather than neuronal activity. What’s notable here isn’t that fMRI is “wrong,” but that without rigorous preprocessing, breathing, heartbeat, vascular dynamics, CO2 changes, and micro-movements can dominate the signal.

Quill OS is an open-source operating system targeting Kobo’s e‑readers, shifting these otherwise closed appliances closer to general-purpose, hackable devices. Under the hood, the hard work isn’t glamourous: stable E Ink rendering, touch input, aggressive power management, Wi‑Fi, and suspend/resume are the pillars that make

A familiar refrain in 2025: “The model sounds like me.” Under the hood, large language models don’t invent a voice so much as statistically converge on one. Feed them enough context and they’ll approximate your cadence, idioms, even regional tech slang. What’s notable here isn’t ego;

Ask HN’s monthly “What Are You Working On?” post is back, and it remains one of the web’s highest-signal snapshots of what pragmatic builders are actually shipping. What’s notable here isn’t splashy launch theater but the granular reality of roadmaps, stacks, and go-to-market experiments. Under the

SoundCloud is now blocking access from VPN endpoints, putting tighter guardrails around who can stream and upload. What’s notable here isn’t the concept-streamers have long waged war on location spoofing-but the apparent platform-wide sweep. Under the hood, this typically means IP reputation checks, ASN filtering of datacenter ranges,

Neal Stephenson’s 1999 essay reads today less like nostalgia and more like systems analysis. What’s notable here isn’t a GUI-vs-CLI flamewar; it’s the claim that narratives and packaging beat raw horsepower. Under the hood, the terminal’s superpower is composability-small tools that chain, inspect, and automate-while

Under the hood, today’s “automated” AI stacks are anything but hands-off. Agentic tool use, structured output modes, and function calling have matured into production primitives-but they arrive with state machines, retrieval layers, prompt registries, and evaluation harnesses that need constant care. What’s notable here isn’t just capability