标签：#IDE

Docking stations expand what your laptop can do, and I’ve been testing the best of the best to see which you should buy.

Your desk setup needs a monitor arm, and I’ve been testing every one I can get my hands on to find the best.

These toppers will transform your mattress into exactly what you need, whether that’s a super-plush pillow top, memory foam, or targeted back support.

I recently worked through a hands-on Amazon S3 practical series covering the features I would actually expect to use while working with AWS storage. Instead of only documenting definitions, this post focuses on what I configured, the commands I used, how I verified the behavior, and what I observed when something went wrong . For the concepts behind these practicals, I have already covered S3 in two detailed sessions: Session 1: AWS S3 Deep Dive — Objects, Encryption, Bucket Policies & Everything In Between Session 2: AWS S3 — Versioning, Static Hosting, CORS, Object Lock & More This post is the practical companion to those two sessions. The concepts are covered there; here I focus on actually building, testing, verifying, and troubleshooting the S3 features. The labs covered: S3 bucket configuration and lifecycle management Bucket policies with IAM, EC2 and HTTPS-only access SSE-KMS encryption with CloudTrail verification Pre-signed URLs AWS CLI s3 sync S3 Versioning and version recovery Static website hosting S3 CORS S3 Object Lock Note: This is a practical write-up, so I have intentionally kept the focus on implementation and verification rather than turning it into a generic S3 theory article. 1. S3 Bucket Configuration and Lifecycle Management Objective Create an S3 bucket with a secure baseline and configure a lifecycle rule that automatically transitions objects to lower-cost storage classes over time. Configuration For the lab: Block Public Access remained enabled. Bucket Versioning was enabled. Lifecycle rule: s3-lab-lifecycle The rule applied to all objects. Current objects transition to: Standard-IA after 30 days Glacier Flexible Retrieval after 90 days The lifecycle flow was: Day 0 ↓ Object uploaded ↓ Day 30 → Standard-IA ↓ Day 90 → Glacier Flexible Retrieval Result The lifecycle rule was successfully created and enabled, and the S3 console confirmed the configured transition periods. What this demonstrates Instead of manually moving old objects, S3 Life

After two years of testing, these are the electric toothbrushes that impressed WIRED staffers the most.

Microsoft has made the Azure DevOps Remote MCP Server generally available, offering a hosted endpoint into work items, repos, and pipelines with nothing to install. Claude Desktop, Claude Code, ChatGPT, and Cursor cannot connect yet because Entra lacks support for dynamic client registration and Client ID Metadata Documents. By Steef-Jan Wiggers

Investors want founders who understand the financial reality of their business. Messy data, misunderstood metrics, or waiting until you’re nearly out of cash to start fundraising can cost founders leverage, valuation, and even a term sheet. In this episode of Build Mode, host Isabelle Johannessen sits down with Sasha Orloff, founder and CEO of Puzzle […]

An effort to transform the world of sports through steroid use doesn't exactly seem to be bearing financial fruit.

OpenAI presented details of its AI’s model’s cyberattack on Hugging Face at Black Hat last week. Simon Willison details the timeline. It’s really interesting to read through—and really impressive cyberoffense work.

I put top-rated USB car chargers to the test for fast charging, value, heat, and safety. These are the best I found.

It’s been awhile since I typed some words around here. Right around the World Cup was the last time, from what I can see. I really didn’t want to like the World Cup, but there’s something about watching it I family that makes it about more than just a game. But I digress - this post has nothing to do with football (fortunately). This is about a pet project I’ve been kicking around for some time, and finally got around to fleshing it out and making it live. A Chinese and Western Zodiac calculator. I’m not a hard-core zodiac horoscope person. I just find the topic interesting. From time to time people would say, “Hey what sign am I?”. I’d spin up the ol’ internet and look for a good Chinese Zodiac calculator (Western Zodiac is much simpler to calculate). But the calculators were usually either deeply embedded in larger sites that were not dedicated to the topic, or ugly as hell and ridden with ads (and who knows what else). I really wished to just find a nice-to-look-at calculator that worked. And one day I realized - hey, I could just make one. I make nice looking websites. I can code enough to set up a Chinese Zodiac calculator that can accurately calculate lunar cycles and your Chinese zodiac animal, without blindly saying, “Oh, you were born in 2026? You’re a horse, of course!” (Which would only be true if you were born on February 17th of 2026 or later). You know, a simple tool that does one thing, and one thing well - show you your sign! (So you can stop asking people in bars…) Zodiacl is Born If you want to know more about the technical side of the new site, you can check it out in my portfolio. So I was probably about halfway through coding the project when the name dawned on me. Unless a client or project needs otherwise, I code and publish for an English- and Spanish-speaking audience. I deeply favor names that work in both languages; the closer to a perfect cognate (word spelled exactly the same in both languages and with the same meaning) the better. I fou

Live video looks simple until you build it. Then you discover that "low latency" means five different things, that your CDN and your latency target are fighting each other, and that the box which handled ten viewers falls over at ten thousand for reasons nobody warned you about. This is the guide I wish existed when I started. No vendor talk, just how the pieces fit. 1. Ingest and delivery are separate decisions The single most common mistake is treating "streaming protocol" as one choice. It is two. Ingest is getting video from a camera, encoder or browser into your server. Delivery is getting it from your server to viewers. They have different constraints and you almost never use the same protocol for both. A typical stack ingests over RTMP or SRT and delivers over HLS. Another ingests WebRTC and delivers WebRTC. Mixing is normal and expected. Once you separate them, most of the confusion disappears. 2. The ingest protocols RTMP is old, TCP-based, and still everywhere. Every encoder speaks it, OBS defaults to it, and it just works. Latency is typically 2 to 5 seconds. Classic RTMP is limited to H.264 and AAC, though the Enhanced RTMP spec has added HEVC and AV1. Being TCP, it degrades badly on lossy networks: packet loss becomes head-of-line blocking, and your stream stalls instead of gracefully dropping quality. SRT is the answer to that. UDP-based with its own retransmission layer (ARQ), a configurable latency buffer, and built-in AES encryption. It is designed for pushing broadcast-quality video across the public internet, which is exactly where RTMP struggles. If your source is on a flaky connection, a 4G link, or a different continent, SRT is usually the right call. # Publishing over SRT with ffmpeg ffmpeg -re -i input.mp4 -c copy -f mpegts \ "srt://your-server:4200?streamid=live/stream1" RTSP is what IP cameras speak. If you are pulling from surveillance hardware, you are pulling RTSP whether you like it or not. WHIP (WebRTC-HTTP Ingestion Protocol) is the n

What tok/s really measures, how concurrency changes it, and why a single-user benchmark is not the whole story for local LLM performance. A Few Moments Later… How Fast Is "Fast"? Every interface in the world of local AI eventually shows you that dreaded spinner, and on the wrong setup it sits there long enough that your brain supplies the meme: "A few moments later…" That pause is a number wearing a disguise. Somewhere inside your machine, the model is grinding out tokens — fragments of words — and the only question that matters is how many of them it produces per second. Tokens per second (tok/s) is the universal speedometer of local LLMs, quoted in every benchmark and every GPU review. But it is also one of the most misleading numbers in the field, because the same model can measure 45 tok/s or 793 tok/s depending on how you test it. This guide explains what the number actually means, why it moves so dramatically, and how to read a benchmark without fooling yourself. What a Token Actually Is Before speed makes sense, the unit has to. Models do not read words; they read tokens, which are chunks of text roughly three-quarters of a character on average in English. The word "calculator" might be one token or three, depending on the tokenizer, and this is not idle trivia — it is the reason the same prompt can cost a different amount across providers, as the Token Counter Calculator shows in practice. Because tokens are the unit of both billing and speed, "tokens per second" is the single number that connects all three corners of the local AI decision: how fast the model answers (tok/s), how big the model is (parameters), and what it costs to run (hardware amortized over time). A model doing 50 tok/s reads roughly 100-150 words per second — comfortably faster than you can read. A model stuck at 5 tok/s feels like a slow internet connection in 1998. The Single-User Number Is Not the Whole Story Here is the trap: most consumer benchmarks report tok/s at one user, one requ

I wanted to build a real-world application with RocketRide rather than just a simple AI demo, so I created ClaimDesk, an AI-assisted insurance claim intake and analysis application. ClaimDesk allows claims adjusters to upload vehicle damage photos and provide a description of an accident. The application then uses a RocketRide pipeline to: Analyze the vehicle damage Analyze the written accident description Compare the image and text analysis Generate a structured claim report I also integrated Ollama for local model execution and created a local startup workflow that launches the required dependencies, models, RocketRide pipeline, webhook connection, and web application together. What I Learned Building ClaimDesk showed me that AI applications require many of the same software engineering practices as traditional applications. I had to think about architecture, debugging, integrations, and creating structured outputs and environments for my application to be reproducible. Overall, working with RocketRide gave me a better understanding of how agentic AI can be integrated into real software applications rather than being used as a standalone model.

I built Suzi Chat to bring back the nostalgic feel of late-90s/early-2000s browser chat rooms. Key Features: Create and customize your own public or private chat rooms instantly from the browser. Built-in multiplayer casual board games (Chess, Checkers, Gomoku). No complicated setup—straightforward web-based access. Built using a NestJS backend and running on a dedicated Linux VPS. Live Platform: https://suzichat.com Looking for feedback from other developers on the UI layout, room creation flow, and multiplayer lobby stability.

Every video card on our category grids was hotlinking a 1280x720 JPEG from a third-party CDN and then letting CSS scale it down to about 320 device-independent pixels. That is roughly 90 KB of wasted transfer per card, 24 cards per page, across eight regional page variants that each carry their own cache key. Mobile LCP on the busiest category pages sat at 4.1s, and the largest single contributor was an image we did not host, could not resize, and could not re-encode to WebP. The fix was not clever CSS. It was owning the frame. We built a small Go service that takes a source video (a partner preview MP4, or a poster frame that arrives at the wrong dimensions), pulls a representative frame with FFmpeg, encodes it at three widths in WebP, and writes the result to a content-addressed path the front end links directly. That service now feeds the same multi-region cron that runs TrendVidStream , and the generated files ride the same FTP mirror as the rest of the deploy. What follows is the part that actually mattered: the FFmpeg invocations, the Go concurrency model that keeps a 2-core build box from melting, and how a stateless Go daemon hands work to a PHP 8.4 + SQLite front end that cannot run a daemon at all. Why this is not a PHP job Our front end is PHP 8.4 on LiteSpeed shared hosting with SQLite (FTS5 for search) as the only datastore. It is a genuinely good fit for a read-heavy discovery site: no database server to babysit, page cache on disk, cron jobs pulling regional feeds every 2-7 hours depending on the site. It is a terrible fit for thumbnail extraction: Shared hosting caps max_execution_time at 180s. A cold FFmpeg decode of a 4-minute 1080p preview can burn 20-40s. Do 200 of them in one cron tick and you are wearing a hard timeout. shell_exec is frequently disabled, and when it is not, you get one process per request with no way to bound total concurrency. There is no shared memory between PHP requests, so two cron ticks racing on the same video ID will ha

The universe may never tell you if your choices mattered. Owlcat’s Osiris Reborn might not either.

Einride will buy the Tesla Semis, which will be made to Amazon and other customers.

Merino is one of the best fabrics you can wear. We explain the different blends, what “GSM” means, and how to care for your clothes.

Higgsfield, founded by former Snap exec Alex Mashrabov, lets users create AI images and videos.