标签：#AR

Ars analysis suggests the 9-year-old console could keep selling for years.

While the auto industry wrings its hands over the electric vehicle market, sweating details like aerodynamic efficiency and range anxiety, a new EV startup based in Lisbon, Portugal, is zagging in a different direction. Amble's new electric buggy won't impress anyone with its 0-60 time or its self-driving features (it has none). Instead, it takes […]

The T70S can be eligible for racing events or built to be road-legal.

Claude Cowork now keeps working on tasks even after you close your laptop. It’s part of a larger push toward smartphone-controlled agents.

HA dashboard cho Postgres replication: vì sao "có replica" không đồng nghĩa "đang HA", và cách để replica chết không âm thầm Streaming replication trong Postgres là một tunnel WAL từ primary sang standby: primary chạy một walsender cho mỗi standby, standby chạy một walreceiver nhận WAL và một startup process replay. Đau nhất trong vận hành không phải setup — mà là replica đã ngắt nhiều giờ mà không ai biết, tới lúc primary chết mới phát hiện HA thực ra là single-node từ tuần trước. HA dashboard là tập metric + alert được rút ra từ pg_stat_replication , pg_stat_wal_receiver , và pg_replication_slots để ép mọi trạng thái xấu — replica disconnect, replay đứng, slot pin WAL, sync standby biến mất — thành tín hiệu nhìn thấy được trước khi biến thành sự cố. Cơ chế hoạt động Trên primary, mỗi standby đang kết nối tạo ra một backend loại walsender — Postgres đọc WAL từ pg_wal/ (hoặc từ WAL buffers khi còn nóng) và stream qua replication connection. Trên standby, walreceiver nhận từng WAL record, ghi vào pg_wal/ local, fsync (tùy synchronous_commit ), rồi startup process apply record lên shared buffers — đây chính là replay. Bốn LSN xuất hiện trong luồng này và tương ứng với bốn cột trong pg_stat_replication : sent_lsn — byte cuối cùng primary đã gửi qua socket. write_lsn — byte cuối cùng standby đã write() vào OS page cache. flush_lsn — byte cuối cùng standby đã fsync xuống đĩa. replay_lsn — byte cuối cùng standby đã replay vào shared buffers (dữ liệu đã "thấy được" trên standby). Postgres docs quy định replay_lsn <= flush_lsn <= write_lsn <= sent_lsn <= pg_current_wal_lsn() — bốn "vạch" này chính là bốn nhịp của lag. Ba cột write_lag , flush_lag , replay_lag (kiểu interval ) là thời gian mà standby chậm hơn primary tương ứng với ba mốc write/flush/replay — được đo qua feedback message định kỳ từ standby. -- Trên primary: bức tranh đầy đủ cho một HA dashboard SELECT application_name , client_addr , state , -- streaming | catchup | startup | backup | stopping sync_state , --

There's a lot of info packed in the top area of an Android phone's screen

We recently got the shape() function and corner-shape property. What else could we possibly need as far as making shapes in CSS? Let me tell you: the border-shape property! Get Ready For the Powerful CSS border-shape Property! originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

AI law startup Norm has raised a $120 million Series C round led by Khosla Ventures, valuing the startup at $1.2 billion.

Bidbus, which lets dealerships bid on used cars, has raised $15 million in a Series A round that was led by early-stage mobility fund Ibex Investors.

iRobot just announced its first-ever non-robotic floor cleaner. The $399 Roomba Electro Plus is a 5-in-1 hard-floor cleaner that combines vacuuming, mopping, and disinfecting, but you have to operate it yourself. The company also announced updates to its line of Roomba robot vacuums, launching five new models with higher suction power, smaller footprints, and lower […]

The data can help predict what a future pandemic virus might look like.

You can clip a cover over the cameras, which could be a double-edged sword.

Solos announced a new version of its AirGo smart glasses, one that forgoes cameras for a sleeker design and an AI assistant that relies on voice interactions. Last year's AirGo A5 weighed 36 to 40 grams depending on the frame style, but the new AirGo A6 weigh around 19 grams. Part of the weight savings […]

Part 1: Solving GOP Structure and Compatibility Issues Operating a digital television network isn't just about keeping channels on air—it's about maintaining quality that viewers expect and troubleshooting issues before they escalate. When something goes wrong in live broadcasting, every second counts. But how do you quickly pinpoint whether the problem lies in encoder settings, transport stream structure, or temporal metadata? This is where specialized stream analysis tools become essential. In this series of articles, we'll walk through real-world scenarios that broadcast engineers face daily and show practical approaches to diagnosing and resolving them. When File Analysis Becomes Critical While live monitoring catches issues as they happen, file-based analysis is your diagnostic microscope. Here's the typical workflow: something breaks in production, engineers capture a few minutes of the problematic stream, and now they need to understand exactly what went wrong. File analyzers serve three primary purposes: Troubleshooting: Identifying the root cause of broadcast issues Encoder optimization: Fine-tuning compression settings Quality control: Validating compliance with standards and specifications Let's explore how this works in practice with actual tools and techniques. The GOP Structure Problem Here's a scenario every broadcast engineer has encountered: legacy set-top boxes or older TV models suddenly can't play your stream. The audio works, video starts and stops, or you see freezing. The culprit? Often, it's the GOP (Group of Pictures) structure. H.264 has been around since 2003—over 20 years. Almost everything supports it, yet you'll still find legacy equipment that struggles with certain configurations. Specifically, the number of B-frames can make or break compatibility. Why B-frames matter: They enable lower bitrates while maintaining quality by increasing encoding complexity through bidirectional prediction. But this comes at a cost—a more complex refere

TL;DR — Angular 22 promoted Signal Forms from experimental to stable. This is not "Reactive Forms are dead." It's a real architectural trade-off, and this post walks through both APIs in full, with production-realistic code, so you can decide feature-by-feature instead of framework-war-by-framework-war. Table of Contents Why This Matters Now The Core Question Reactive Forms: Why It Became the Standard Full Example: Reactive Forms Login Where Reactive Forms Still Excel Signal Forms: What Actually Changed in Angular 22 Full Example: Signal Forms Login Where Signal Forms Shine Side-by-Side: Core Concepts Mapped Deep Dive: Validation Synchronous Validation Cross-Field Validation Conditional Validation with when() Async Validation Deep Dive: Dynamic and Nested Forms Nested Form Groups Dynamic Collections (FormArray-style) Deep Dive: Form State — Dirty, Touched, Errors, Submission Developer Experience and Testing Performance Considerations Interop: Migrating Without a Big-Bang Rewrite Migration Strategy for Enterprise Teams When NOT to Migrate Decision Framework FAQ Closing Thoughts Why This Matters Now With Angular 22 (released June 3, 2026), Signal Forms left experimental status and became part of the stable, supported API — alongside resource() and httpResource() . That's a meaningful milestone: it means the Angular team ran extensive internal case studies across real form-heavy applications at Google before committing to stability, and the interop story with Reactive Forms has matured enough that a big-bang rewrite is no longer the only migration path. At the same time, Angular 22 also flips two important defaults: components now use OnPush change detection by default, and zoneless change detection continues its push toward becoming the standard. Signal Forms is part of that same story — Angular's reactivity model finally speaking one dialect end-to-end, from component state to form state to async data. None of this makes Reactive Forms obsolete. It changes what "the

I came into this as a graphic designer, not a software engineer. I didn't have a computer science background, and a lot of what BrandStack needed — authentication, databases, payments, deployment — was new territory for me when I started. What made it possible wasn't some shortcut. It was breaking the problem down into pieces I could actually learn: how user accounts work, how a database should be structured so one person's data never leaks into another's, how to move from test payments to real ones without breaking checkout for actual customers. I made real mistakes along the way. Early on, every user shared the same underlying brand data because I hadn't scoped the database correctly to each account — a serious bug that I only caught by testing with two separate accounts myself. Finding and fixing that taught me more about proper application architecture than any tutorial could have. I don't think being a designer first is a disadvantage for building product. If anything, it means the interface and the experience get real attention, not just the backend logic. But it does mean being honest about what you don't know yet, and being willing to slow down and actually understand a problem instead of copying a fix you don't understand. BrandStack is still a work in progress. But it's a real, working product — built by someone who had to learn most of this from scratch, in public, one bug at a time.

I hesitated to write this. Not because I don’t have an opinion about AI in software engineering, but...

The company just raised $7 million in seed funding, and is launching its app for iPhone and Android on Tuesday.

Amazon Web Services (AWS) has announced a major expansion of its AWS DevOps Agent, introducing new release management capabilities designed to assess code changes and autonomously test software before it reaches production. By Craig Risi

Protect your expensive iPhone 17, iPhone Air, iPhone Pro, or iPhone 17e with our favorite cases and screen protectors.