标签：#home

The musician created his own line of loopers that record and layer riffs in a loop. The pricey Looper X does what it claims, but it isn’t without quirks.

Apple and Google are updating their smart home streaming devices to Thread 1.4. As first spotted by Matter Alpha and 9to5 Google, the latest spec has arrived on compatible Apple TVs in the tvOS 27 developer beta and the Google TV Streamer through a software update. This lays the groundwork for these devices, which serve […]

The Google Nest Cam with Floodlight is marked down to $179.99 ($100 off) at multiple retailers, including Amazon, Best Buy, Home Depot, and directly from Google. This weather-resistant outdoor camera captures 1080p video across a 130-degree diagonal field of view, with snappy notifications and great customization options. Even without a subscription, the camera can store […]

These bird feeders come with cameras and connected apps to let you see and learn about the birds in your neighborhood.

I've been a fan of Philips Hue smart lights since the early days. It's one of the few staples in my ever-changing smart home. However, when the Bridge Pro launched late last year, it wasn't immediately obvious why I should upgrade. The signature feature, MotionAware - which turns your lights into motion sensors - is […]

Use this WIRED-exclusive coupon code to get the best deal on this high-design machine and biodegradable pods.

Apple Intelligence is coming to cameras connected to Apple Home. At WWDC, Apple announced that with iOS27, the Home app will use Apple Intelligence to analyze footage and generate descriptions summarizing what the camera saw. You can also search footage with natural language to find clips from across connected cameras, such as when a package […]

If you have an outdoor space that needs some extra lighting, either for fun or security reasons (or a mix of the two), the Govee outdoor lamp post light is a good pick that’s 23 percent off its regular price right now. Typically retailing for $260, the Govee outdoor lamp post light is available for […]

I run a transparent OPNsense bridge between a UniFi Dream Machine Pro and the rest of my LAN. It is deliberately boring at Layer 3: the UDM keeps routing, DHCP, DNS, firewall policy, WAN handling, and VLAN definitions. OPNsense sits inline as a Layer 2 bump in the wire. The interesting part is that both sides of that bump use LACP . I already wrote the build/configuration guide for this setup here: Building a Transparent LAGG (LACP) Bridge with OPNsense, UDM, and UniFi - A Practical Guide . That article explains how the bridge was built, how the LAGG devices were configured, and why I wanted the firewall to remain transparent. This article is the other half of the story: what happens when that kind of setup fails in a non-obvious way. Not a clean outage. Not a single "the network is down" moment. Just enough instability to make everything feel wrong. 1. Topology and Failure Surface The topology looked like this: +----------------------+ | UniFi Dream Machine | | kantharos-udm-pro | +----------+-----------+ | LACP aggregate, 2 x 1G | OPNsense lagg0 "ingresslagg" igc1 + igc2, LACP | +----------v-----------+ | OPNsense bridge0 | | "laggbridge" | +----------+-----------+ | OPNsense lagg1 "egresslagg" igc4 + igc5, LACP | LACP aggregate, 2 x 1G | +----------v-----------+ | UniFi USW-Lite-16 | | downstream LAN | +----------------------+ On OPNsense, the relevant interfaces were: igc1 + igc2 -> lagg0 -> ingresslagg -> toward UDM igc4 + igc5 -> lagg1 -> egresslagg -> toward USW lagg0 + lagg1 -> bridge0 -> laggbridge The bridge is a FreeBSD bridge. The aggregates are FreeBSD lagg(4) interfaces using LACP. OPNsense exposes those through its Interfaces > Devices UI. The expected healthy OPNsense state is: laggproto lacp status: active laggport: igcX flags=<ACTIVE,COLLECTING,DISTRIBUTING> laggport: igcY flags=<ACTIVE,COLLECTING,DISTRIBUTING> Those three member states matter: ACTIVE : the member is participating in the LACP bundle. COLLECTING : the member may receive traffic. DIS

The Logitech G512 X 98 lets you swap between mechanical and analog switches in an attempt to achieve the best of both worlds. Unfortunately, its solution isn't as well thought-out as I'd hoped.

Never underestimate the power that a cheap tablet holds over a kid under six. The Skylight Buddy is a device with one job: to be a cute little guy that helps your kid track routines and chores. It's $139.99, plus an optional subscription. And to my surprise, even though it offers a pretty limited set […]

These are the cleaning robots, water monitors, and toys actually worth buying for pool season.

How I combined spaced repetition, adaptive algorithms, and clean UX to create a multi-purpose learning tool. I’ve always believed that memorisation doesn’t have to feel like a chore. After years of using (and sometimes getting frustrated with) existing tools, I decided to build my own. That’s how MemOrLearn was born in early 2026. MemOrLearn is a web-based adaptive learning platform that brings together flashcards, typing practice, math drills, and Bible memory tools — all powered by intelligent spaced repetition and performance-based adaptation. The Core Idea: Most flashcard apps follow a rigid spaced repetition schedule. I wanted something smarter — a system that actually adapts to the user in real time. If a learner is struggling with a concept, the algorithm increases review frequency and offers slight variations. If they’re crushing it, reviews are intelligently spaced out. This dynamic approach is what makes the experience feel responsive and human. Key Features: Adaptive Flashcards: The heart of the platform. Users can create decks or browse public ones. The system tracks performance per card and automatically adjusts difficulty and frequency. Clean, fast, and minimal interface — exactly how I like my tools as a developer. Typing Tutor: Built to help users improve speed and accuracy through gamified, adaptive drills. It adjusts to your current level so you’re always progressing. Math Drills: Focused practice on math facts with real-time adaptation. The system identifies weak areas quickly and targets them without wasting time on mastered content. Bible Memory Mode: A specialized tool many users love. It applies the same adaptive principles to Scripture memorization, making it effective for individuals, families, and small groups. Teacher / Parent Dashboard: A clean admin view that lets educators assign work, monitor progress, and adjust settings per student. Built with simplicity in mind. Technical Approach (For Fellow Builders): I focused on keeping the back

Looking to add a smart speaker to your house? Here’s which to choose, whether you’re an Alexa, Siri, or Google fan.

The Dreame L20 Ultra isn’t the company’s newest model, but it’s still a great robovac / mop hybrid that offers strong performance while requiring very little day-to-day maintenance thanks to its included trash bin and AI obstacle avoidance. Verge readers can get for its best-ever price right now. Originally $1,400 when it launched in 2023, […]

Smart lighting company Nanoleaf has been acquired by OneRobotics, the parent company of SwitchBot. In an exclusive interview with The Verge, Nanoleaf CEO Gimmy Chu says the company will remain independent and that he and his cofounder and COO, Christian Yan, will continue to run it. "Nothing is changing operationally," says Chu, adding that there […]

This is the technical, reproducible version of a fix I shipped on my own homelab. If you want the narrative version, that's on Medium. This one is the recipe: the measurements, the math, the Modelfile, and the exact prompt I gave Claude Code to generate it. Copy-paste friendly. Repo for the dashboard used throughout: https://github.com/SikamikanikoBG/homelab-monitor TL;DR One 24GB RTX 3090, two GPU services: WhisperX large-v3 (STT, 7.7GB peak) and a Devstral Small 24B email-triage LLM (Q4_K_M, ~18.3GB). 18.3 + 7.7 = 26GB → CUDA OOM whenever they overlapped. The LLM was loaded with a 40k context window but the triage job never needed more than ~5–8k tokens. Capped num_ctx to 8192 → KV cache drops from ~6.1GB to ~1.25GB → model footprint ~18.3GB → ~14.2GB . 14.2 + 7.7 = 21.9GB → both resident, zero OOM, no quality loss. The setup Host : openSUSE, Xeon (56 threads), 125GB RAM, 1x RTX 3090 (24GB) GPU svc : WhisperX large-v3 (speech-to-text) GPU svc : Ollama -> devstral-small-2 (24B, Q4_K_M) for background email triage Both services run all the time. The OOM only happened when I dictated to my assistant (WhisperX) while the triage loop was active. Step 1 — Make the contention measurable nvidia-smi shows instantaneous VRAM. It can't show you which service spiked or when two of them overlapped — and an intermittent OOM is a timing problem. You need per-service VRAM history. I use my own dashboard (homelab-monitor) for this. The relevant view is "AI Models", which attributes VRAM per model server and per loaded model, over a time range, with OOM markers and a capacity ceiling line. What the history showed at the overlap window: Service Peak VRAM Devstral 24B (triage) ~18.3 GB WhisperX large-v3 7.7 GB Total ~26 GB on a 24 GB card If you want to reproduce the measurement, the dashboard runs as a single container: git clone https://github.com/SikamikanikoBG/homelab-monitor cd homelab-monitor docker compose up -d --build # open http://<host>:9800 -> AI Models / GPU views (NVIDI

Switching from fossil fuels to electricity for heating is no longer covered.

Thermacell has launched Liv 2.0, the next generation of its Wi-Fi-connected smart mosquito protection system. It features new hardware and can cover a larger area, and Thermacell says its formula can now deter no-see-ums. But it's also more expensive and requires professional installation. Liv 2.0 uses the same setup as the original Liv - a […]

I’ve rounded up the best smart speakers that let you talk to Alexa, from the popular Echo Dot to the newest Echo Studio.