🚀 SpaceX signed a massive $920 million monthly deal with Google for 110,000 Nvidia chips — this is a huge infrastructure play ahead of their monster $1.7 trillion IPO. 🏛️ The Trump administration is discussing taking equity stakes in top AI firms — this would make the public official partners in the upside of AI-driven economic growth. 🔓 Meta's automated AI support was hacked to take over high-profile accounts — it proves that offloading critical security tasks to AI can create dangerous, easily exploited vulnerabilities. 🧠 Tech workers are trading hours of manual labor for high-level strategy thanks to AI — while tasks now take minutes, humans are still needed for crucial, complex decision-making. submitted by /u/Ok_Muffin_7347 [link] [留言]

Sigma’s new entry is both a bold design experiment and a pretty decent camera.

These 5- to 6-inch blades are the secret workhorses of the kitchen, whether you’re a smaller person, have smaller hands, or just desire a smaller but still high-functioning knife.

Tired of uploading your private files to sketchy ad-filled website for conversion and OCR? Meet EasyConvert, a serverless media tool that uses FFmpeg WASM to convert, compress and OCR media files 100% locally. Link: easy-convert.pages.dev Github: https://github.com/nihid7/easyconvert submitted by /u/Fun-Time9529 [link] [留言]

A CAD design tool for coding agents (free + open source) Discussion | Link

Hey everyone!! sharing something I've been building for the past 2 months. Leafy lets you and your team annotate any webpage. You click an element (or highlight text), leave a comment, @ mention teammates, and they get notified. Comments are anchored to specific parts of the page and sync across devices. Use cases I've seen people use it for: → Product teams reviewing features on their products → Designers leaving feedback on live prototypes → Researchers annotating sources together → QA marking bugs on staging environments → Sales teams using it on salesforce → Students using it for marking interesting things on any page, to study You can organise teams into "Gardens" (I know, quirky naming). Free tier supports up to 3 gardens with 5 members each. I'd love any feedback! especially on what feels broken or missing. Chrome Web Store: https://chromewebstore.google.com/detail/leafy-annotate-the-web-to/doohbmfpjanoimbigjbjocanpenbfkkh https://preview.redd.it/4riy4haubu5h1.png?width=908&format=png&auto=webp&s=69ecac6f3bef7a4843c58095c3d8a5972ff2ceaa Product page: https://get-leafy.com submitted by /u/maxisrichtofen [link] [留言]

Just shipped this project and wanted to share the full technical breakdown because hotel/hospitality AI doesn't get much attention compared to the usual chatbot and SaaS use cases. The client manages 500 hotel properties. Their support team was manually handling around 15,000 guest emails per day. Same questions over and over across hundreds of hotels but each one still needed a human to read it, understand it, find the answer, and reply. Here's how the system works end to end: Layer 1: Email ingestion and question extraction This was the hardest part. Guest emails are messy. A typical one looks like: "Hi there, we're coming for our anniversary on the 20th and I was wondering if you have any room upgrades available. Also is the spa open to guests or do we need to book separately? We're driving so need to know about parking too. Last time we stayed the wifi was a bit slow in our room, has that been fixed? Thanks!" That's four separate questions plus a complaint wrapped in one email. If you just embed the whole thing and search the FAQ database you get a blended result that partially answers one or two questions and misses the rest. So I built an extraction layer that reads the full email and breaks it into individual questions. It handles directly stated questions ("is the spa open?"), implied questions ("we're driving" implies they need parking info), complaints that need acknowledgment but aren't FAQ-searchable ("wifi was slow"), and informational context that shouldn't be treated as a question at all ("coming on the 20th"). Getting this extraction reliable was probably 40% of the total development time. Layer 2: FAQ knowledge base with vector search All hotel FAQs get embedded and stored in a vector database. Different properties have different amenities, policies, and details so the search is scoped per hotel. When a guest emails the Berlin property asking about breakfast, it searches the Berlin FAQ, not the Munich one. Each extracted question from Layer 1 gets s

Lauf’s sleek new entry feels closer to a traditional mountain bike than anything I’ve ridden before.

After 16 weeks of daily use, our WIRED testers saw visible hair regrowth with these red-light therapy devices.

This post is a continuation of part 1 During my childhood, I was obsessed with mazes. I would spend hours drawing mazes with increasingly complex rules and I would force my parents and friends to solve them. I wanted to translate this to the computer. Every so often, I would return to the challenge. Most of my mazes were built in Minecraft. Soon though, my mind started to connect the dots. Minecraft had convinced me that computers could be bent to my will. If I could understand how the game worked, maybe I could make my own world. I was convinced understanding the .bat script was the key. Initially, I experimented. I vividly remember trying to rename the script, after which windows would yell out a scary warning about how changing an extension might make the file unusable. I quickly pressed cancel, hoping I did not break my game. The first time I tried opening the minecraft.bat file in notepad, I was overwhelmed. A bunch of nonsensical garbage filled my screen. I did not know it at the time, but the people who shipped the cracked version obfuscated the script. It was not meant to be understood. I borrowed more and more books on programming and computers from the library, slowly building an understanding of how mysterious lines of text made the computer do stuff. I attempted many times to apply my knowledge. Most of my "programming" was copying code from books in notepad, trying to run it but not having the compilers or knowledge to execute my code. My computer was littered with hundreds of little files. maze.py , maze.php , maze.java . Each an attempt to achieve my dream of creating a maze. Each time, I faced disappointment when I double-clicked, and the computer told me that the file I just worked on was unrecognised. However, there was one piece of code I wrote that actually worked. A small little batch script - welcoming me to a new world. echo "Hello World" A short while later the computer I was working on died. Being locked out of a world I had only just starte

The idea is to make it straightforward to find any ffmpeg version and configuration you require, and to have the binaries available for production CI/CD flows without worrying they will expire. submitted by /u/pinter69 [link] [留言]

Data analysis is at the heart of how we spot patterns and improve systems today. Tools like Python, SQL, Power BI, and Tableau are everywhere in the data world, but Excel has held its ground as the starting point for anyone getting into data work, and there is a reason for that. What is Excel? Excel is a spreadsheet built on a grid of rows and columns. You use it to organize, format, and calculate data. For analysts it is where messy raw data gets sorted out, numbers get worked through, and everything gets turned into something that actually makes sense to look at. Ways Excel is Used in Real-World Data Analysis 1. Data Cleaning Raw data is almost never clean. Names are misspelled, IDs get duplicated, spacing is off, values go missing. None of that is unusual, it is just the reality of working with real data. Before any analysis happens the data has to be honest, because if the data is wrong the results will be too. Functions like PROPER() and TRIM() are some of the basic tools that help get data into a state where you can actually work with it. 2. Financial Reporting Every business, big or small, needs to know where the money is going. Excel makes that straightforward. SUM() adds up a range of numbers, AVERAGE() finds the mean, and once the calculations are done the data can be turned into charts and dashboards that tell the story of the business clearly. Not everyone in the room is an analyst, but everyone can read a chart. 3. Business Decision Making Clean data presented well becomes a decision making tool. What do customers want? What is working? What needs to change? Sorting figures from highest to lowest or filtering by region can take thousands of rows and turn them into something focused and answerable. That is really what data is for, helping people make better calls. Excel Features I Have Learned and How They Apply Three features that have stood out to me are conditional formatting, data validation, and cell referencing. Conditional formatting highlights ce

A bit of context first. I run a service that caches images from paywalled sites so users don't have to load them fresh on every visit. The overwhelming majority of what we cache is PNG - huge, bloated, uncompressed PNG. Naturally, I started looking into smarter storage and serving strategies, and JPEG XL kept coming up as the obvious answer. The compression gains on PNGs especially are remarkable: you can cut file sizes by 50–60% compared to JPEG with minimal perceptible quality loss at equivalent settings. So the plan seemed straightforward: Convert everything to JXL Detect browser support via the Accept header Serve JPEG as a fallback on the fly for unsupported browsers Here's what the numbers actually looked like: Strategy Total Size Savings Do nothing ~51 GB - WebP Q85 (universal) ~12 GB −39 GB JPEG Q92 (universal) ~21 GB −30 GB JXL d=1 + JPEG fallback ~16 GB / ~5 GB −46 GB (85% of users get 76 KB avg) The JXL route has the best savings on paper - but it means storing two versions of everything, or doing on-the-fly conversion, which adds latency. WebP Q85 just wins. Universally supported (~97–98% of browsers globally), −39 GB in savings, no fallback needed. I hate that this is the conclusion, because JXL is better across most technical dimensions that matter Chrome removed JXL support in Chrome 110 in October 2022 - and that removal was the real killer, given Chrome's ~65% global market share. The stated reasons were actually fourfold: experimental flags shouldn't remain indefinitely; insufficient ecosystem interest; insufficient incremental benefits over existing formats; and maintenance burden reduction. Critics, including engineers from Intel, Adobe, Cloudinary, Meta, and Shopify, disputed all of these claims vigorously in what became one of the most contentious threads in Chromium history. In 2026: Google has reversed course. Chrome 145 (released February 2026) ships with a JPEG XL decoder - currently behind a flag, but back in the codebase for the first tim

As the title says, creating and sharing short videos on macOS or Windows has never been a smooth flow for me. I used to screen cap with QuickTime or the NVIDIA. The result were huge .mov or .mp4 file. Then I either need to upload a 600 MB file to an online compressor, open Handbrake, or use ffmpeg from the command line. Ffmpeg is great, but for quick everyday use, but I found myself loosing the text file where I keep the most useful commands to adjust parameters, and it's anying when there are silly error because I forgot a parameter. And if I wanted to trim the video, I usually had to open a separate video editor that take time to open and are sort of overkill for a simple trimming. So I built Compress.mov . The basic flow is simple: drag and drop a video, choose whether you want to trim it, compress it, or both, and get the result automatically saved in your computer. Over time I added more features: audio removal, video rotation, codec selection, video rescaling, multiple languages (german, farsi, japanese...), and a small counter that shows how many lifetime megabytes you’ve saved by using the Compress app. The latest feature I’m testing is video recording, so I don’t have to use QuickTime anymore! This started as a side project on my spare time, and I built it without an AI assistant, so it’s fully handmade 😃 You can try it at compress.mov for FREE and if you become a fun please purchase it at the windows store or App Store to help me stay motivated. submitted by /u/tino-latino [link] [留言]