标签：#X

Layup Parts co-founder Zack Eakin has drawn on a motorsports background, and his experience working for Palmer Luckey and Elon Musk, to tackle making faster, cheaper, and better composites.

Google is launching a new feature for its Phone app that aims to protect you from AI impersonation scams. Now, when you receive a call from a scammer that appears to be coming from the same number as one of your contacts, Phone by Google will flag the call as suspicious so you can hang […]

After industry objections, President Trump signed a revised AI executive order requiring only voluntary prerelease government reviews of advanced models.

The Scenario: The Help Desk Bottleneck From 2019 to 2021, while serving as Lead Backend Software Engineer at a fast-growing company, I occasionally support our Linux System Administration tasks. When the DevOps team encountered a critical bottleneck during an initiative to scale dozens of new server deployments, I stepped in to streamline the infrastructure processes. The DevOps team was being hampered by constant, fragmented requests from the help desk to manually create new Linux accounts for recruits testing the latest application. These interruptions were not only time-consuming but were directly preventing the team from focusing on the high-priority infrastructure deployments that define their core responsibilities. I realized that we weren't just struggling with a task; we were struggling with a scaling bottleneck. To regain the team's focus and ensure we hit our project deadlines, I decided to automate this workflow. The First Step: The Interactive Script My first objective was to develop a robust, automated shell script to efficiently create new Linux user accounts. I started with an interactive Bash script (create-user-interactive.sh) that prompted for input. This was a good educational exercise for learning the fundamentals of Bash—like useradd, passwd, and shell variables. However, I quickly learned that while interactive scripts are great for learning, they are rarely used in professional DevOps environments. Why Manual Scripts Don’t Scale As I transitioned into a more infrastructure-focused role, I realized that manual scripts fail for three key reasons: Lack of Automation: DevOps is about "Infrastructure as Code" (IaC). Asking an engineer to sit at a terminal and type prompts is slow, error-prone, and destroys the ability to automate. Lack of Centralization: In a real team, we aren't creating users on individual local machines. We manage identity across hundreds of servers. Security Risks: Hardcoding passwords or piping them through echo is a major red

This article was originally published on aifoss.dev --- title: 'Chroma vs Qdrant vs Weaviate 2026: RAG Database Compared' description: 'Compare Chroma, Qdrant, and Weaviate for local RAG in 2026: version snapshots, filtering tradeoffs, hybrid search, quantization, and a clear pick by use case.' pubDate: 'May 27 2026' tags: ["vectordb", "ai", "rag", "python", "opensource"] The three most commonly recommended open-source vector databases for RAG — Chroma, Qdrant, and Weaviate — are not interchangeable. Chroma is a prototyping tool that grew into a real product. Qdrant is a production workhorse written in Rust with the best filtering performance of the three. Weaviate is an enterprise-grade platform with hybrid search and the most built-in integrations. Using Weaviate when you need Chroma adds unnecessary ops overhead. Using Chroma when you need Qdrant means migrating under pressure when your collection outgrows it. Versions covered: ChromaDB v1.5.9 (May 2026), Qdrant v1.17.1 (March 2026), Weaviate v1.37 (May 2026). The quick answer Situation Best choice Local prototyping, notebooks, under 100K vectors Chroma Embedded in a Python process — no separate service Chroma Production RAG with filtering-heavy queries Qdrant Multi-user deployment, concurrent queries Qdrant Memory-constrained deployment at millions of vectors Qdrant Hybrid search (BM25 + vector in one query) Weaviate Multi-modal retrieval (text + images + audio) Weaviate Built-in re-ranking or generative AI modules Weaviate Kubernetes, team-operated, agentic MCP workflows Weaviate Getting from zero to working RAG in 10 minutes Chroma What each tool actually is ChromaDB (Apache 2.0, chroma-core/chroma ) started as a pure-Python embedded database and was rebuilt in Rust for the v1.0 release. The Rust core eliminates Python's GIL bottlenecks and delivers roughly 4× faster writes and queries compared to the pre-1.0 implementation — write throughput went from ~10K to ~40K+ vectors/second in server mode. Chroma's des

The women building these over-the-top, bedazzled cyberdecks aren’t in it for the glitter alone. This trend is reaching its peak at a time when people feel powerless against big tech.

X will now let you 'react with video' to posts.

The MacBook Neo shipped 1.1 million units in its first weeks on sale, IDC estimates, as Apple pushes deeper into the mainstream laptop market.

CEO Dave Limp said damage to the company's launchpad in Florida was not as bad as expected. But Blue Origin still hasn't shared the cause of last week's explosion.

Cómo solucionar el error "Text content does not match server-rendered HTML" en Next.js Este error ocurre cuando el HTML generado en el servidor (SSR) no coincide con el árbol de React que se construye durante la hidratación inicial en el navegador. Es un problema crítico que rompe la experiencia de usuario y puede causar comportamientos impredecibles. Causa raíz En tu caso, el error está relacionado con contenido dinámico que varía entre renderizado del servidor y renderizado del cliente , probablemente por: Uso de Date() o new Date() en el renderizado (ej. fechas de eventos como JUN 9 , JUN 11 , etc.) Uso de typeof window !== 'undefined' o APIs del navegador directamente en el render Metaetiquetas o scripts que modifican el DOM antes de la hidratación (como iOS detectando fechas como enlaces) Configuración incorrecta de librerías CSS-in-JS o Edge/CDN que modifiquen el HTML Solución definitiva (pasos) ✅ Paso 1: Aisla el contenido dinámico con suppressHydrationWarning Si el contenido que varía es intencional (como fechas de eventos), envuelve solo el elemento problemático con suppressHydrationWarning={true} : // app/page.tsx o app/events/page.tsx export default function EventsPage () { const events = [ { name : ' NEXT.JS NIGHTS ' , date : new Date ( ' 2024-06-09 ' ) }, { name : ' AMS ' , date : new Date ( ' 2024-06-11 ' ) }, { name : ' LDN ' , date : new Date ( ' 2024-06-18 ' ) }, ]; return ( < div > < h2 > VIEW EVENTS </ h2 > < ul > { events . map (( event , i ) => ( < li key = { i } > < strong > { event . name } </ strong > { /* ✅ Solo este elemento usa suppressHydrationWarning */ } < time dateTime = { event . date . toISOString () } suppressHydrationWarning > { event . date . toLocaleDateString ( ' en-US ' , { month : ' short ' , day : ' numeric ' }) } </ time > </ li > )) } </ ul > </ div > ); } ⚠️ Importante : suppressHydrationWarning solo funciona en el elemento inmediato, no en hijos. Usa span , time , div , etc., no en contenedores grandes. ✅ Paso 2: Evita Da

An anonymous security researcher called “Nightmare Eclipse” has been publishing a series of significant security exploits against Microsoft Windows—including one that breaks BitLocker. Microsoft has threatened legal action against the researcher. Lots of recriminations are being traded back and forth.

Pacific Fusion's sub-scale prototype delivered enormous amounts of power in a flash, setting the company up for its demonstration power plant.

Most people use these technologies every day. Almost nobody knows they exist. Every time you open YouTube, browse Instagram, join a Zoom meeting, or play an online game, your router is quietly performing a series of networking tricks behind the scenes. Those tricks have names: NAT SNAT DNAT PAT Port Forwarding They sound intimidating. They're actually much simpler than they appear. Let's break them down using something familiar: your home Wi-Fi. The Problem the Internet Had to Solve Imagine a family of five living in one house. Everyone owns a device: Laptop Phone Smart TV Gaming Console Tablet Each device needs internet access. The problem? Your Internet Service Provider usually gives you only one public IP address . Something has to manage all those devices sharing a single internet connection. That's where NAT comes in. NAT: The Receptionist of Your Network NAT stands for Network Address Translation . Think of NAT as a receptionist in an office building. People inside the building have room numbers: Laptop = Room 101 Phone = Room 102 TV = Room 103 But when communicating with the outside world, everyone uses the building's main address. The receptionist keeps track of who sent what. Your router does exactly the same thing. What Happens When You Visit Google? Inside your home: Laptop 192.168.1.10 Your router: Public IP 49.x.x.x When you open Google: 192.168.1.10 ↓ Router ↓ 49.x.x.x ↓ Google Google never sees your private IP. It only sees your router's public IP. That's NAT in action. SNAT: Changing the Sender's Address SNAT stands for Source Network Address Translation . The keyword is: Source It changes the sender's address. Before leaving your network: Source: 192.168.1.10 After SNAT: Source: 49.x.x.x The router replaces your private IP with its public IP. Without SNAT, websites wouldn't know how to send responses back to you. Real-Life Example Imagine mailing a letter. Instead of writing your bedroom number as the return address, you write the house address. Tha

“Did We Already Watch This?” — Building KindaSeen with FastAPI and Next.js A few months ago, my friends and I kept running into the same question whenever we talked about movies, dramas, anime, or variety shows: “Did we already watch this before?” Sometimes we remembered the title but forgot whether we had finished it. Other times, we completely forgot we had already seen it at all. That simple problem inspired me to build KindaSeen, a full-stack personal media repository designed to help users track and organize the media they’ve consumed in one centralized platform. The goal of the project was not only to create a useful application, but also to gain hands-on experience building a real-world full-stack system with modern web technologies. What KindaSeen Currently Supports User authentication with Supabase CRUD operations for personal media records TMDB-powered search functionality Watchlist system Favorites system Persistent PostgreSQL storage Dockerized backend deployment Separate frontend/backend deployment workflow Tech Stack Frontend Next.js React Tailwind CSS Shadcn/ui Vercel deployment Backend FastAPI PostgreSQL Docker Render deployment External Services Supabase Authentication TMDB API integration One of the main goals of this project was to simulate a more realistic production workflow by using a decoupled frontend/backend architecture instead of building everything inside a single monolithic application. In this article, I’ll share: Why I chose this architecture How I integrated TMDB into the application Challenges I faced during deployment What I Learned From Building KindaSeen Why I Chose This Architecture Instead of building a monolith using Next.js API routes, I decided to decouple the application into a Next.js frontend and a FastAPI backend. This decision was driven by three main factors: AI Compatibility & Future Proofing : While researching the job market, I noticed that most companies building AI products heavily rely on Python. By choosing FastA

We talk about pagination as if it's purely a backend concern – the database does the heavy lifting, the API returns pages, and the frontend just renders them. But in 2026, that mental model is outdated. The frontend now owns more of the data-fetching lifecycle than ever: server components prefetch, client caches hydrate, optimistic updates mutate, and streaming responses trickle in chunk by chunk. The choice between cursor pagination and offset pagination has real consequences for how you write your React components, how your cache behaves, how scroll feels on the phone, and what happens when a user navigates back. This post is about those tradeoffs – from the frontend seat. The Landscape Has Changed A few things are different in 2026 that make this conversation more nuanced than it was three or four years ago: React Server Components are mainstream. Data fetching happens on the server in many apps, which shifts where pagination state lives and how navigation works. TanStack Query is the de-facto standard for client-side async state, with first-class infinite query support baked in. The "infinite scroll vs pagination" debate is mostly settled — infinite scroll wins for feeds and content-heavy apps; numbered pages win for dense data tables. Your pagination strategy should serve that decision, not fight it. LLM-powered search and filtering are becoming common, and those use cases have their own quirks around pagination stability. Edge caching and CDN-level pagination mean that certain offset-paginated responses can be cached by URL – a genuine advantage offset still holds. What Frontend Engineers Actually Care About When you strip away the SQL theory, here's what the pagination choice actually affects on the frontend: 1. Cache Key Design With offset pagination, the cache key is simple and predictable: posts?page=3&limit=20 . Every page is independently cacheable by URL — your CDN loves this. TanStack Query, SWR, and Apollo all handle this naturally. // Offset — clean,

A homelab box that never sleeps runs 8,760 hours a year. So the spec that decides what it costs you is not the one on the box. It is the one nobody prints: how many watts it pulls sitting at the login prompt doing nothing. I kept hitting this while shopping for a Proxmox node, so I put the measured numbers in one place. More on that at the end. First, why the spec sheet lies to you. TDP is a thermal budget, not a power reading TDP is the heat the cooler has to handle at full tilt. It is a design target for the heatsink, not a measurement of what the chip draws, and it says almost nothing about idle. Your homelab box spends 95%+ of its life idle, so the number that runs up the meter is idle wall power, and that number is never on the product page. The arithmetic is unforgiving. One watt running continuously is 8.76 kWh a year. So the gap between a 7 W box and a 35 W box is not 28 watts, it is about 245 kWh a year, every year, for as long as the box is on. Plug in your own rate to get the dollars; the point is the gap compounds. Where TDP actively misleads you A few measured results from the dataset I'll link below, all from third-party wall-meter readings, not vendor claims: The new N100 wave is genuinely low. A Minisforum UN100C measures 5 to 7 W at idle. Beelink, GMKtec and Trigkey N100 boxes land in the 6 to 10 W range. For a Pi-hole, a few containers and some light VMs, this tier is hard to beat on running cost. AMD mini PCs idle far higher than their marketing suggests. A Minisforum UM790 Pro measures 25 to 45 W at idle. A Beelink SER6 Pro lands at 20 to 35 W. These are fast little machines, but if you picked one expecting "small box, small draw," the meter disagrees, and over a year that delta is real money. Newer and higher-TDP is not lower-idle. A Dell OptiPlex 7060 Micro idles just over 18 W on its 65 W-TDP desktop chip. The older 7070 with a six-core part sits around 13 W, and the low-power "T" SKUs lower still. The CPU's TDP class predicted idle better tha

When we started experimenting with AI translations, we assumed the biggest challenge would be accuracy. We were wrong. The harder problem was preference. Give two AI models the same sentence, and both translations can be technically correct. Yet people almost always have a favorite. One sounds more natural. One feels more human. One is the version they'd actually use. That observation eventually led us to build Parley , a simple game where players compare two translations and choose the better one. What happened next surprised us. People became highly engaged with a task that looked almost trivial. They started debating word choices, discussing tone, and noticing subtle differences between translations. Some users spent far longer interacting with translation examples than they ever would reading documentation or language-learning materials. It highlighted something interesting about AI products: evaluation can be more engaging than generation. Most AI interfaces focus on creating content. But humans are often much better at judging quality than producing it from scratch. Asking someone to choose between two outputs requires less effort while still training their intuition. The experiment also changed how I think about language learning. Traditional language apps often rely on memorization and repetition. But comparing alternatives forces you to think about meaning, context, and natural expression. You're not just learning vocabulary, you're developing taste. And in a world where AI can generate endless content, taste might become one of the most valuable skills we can build. Have you seen similar patterns in AI products where evaluation turns out to be more engaging than creation?

When managing production enterprise infrastructure, you rarely have direct root access via SFTP or SSH for security reasons. Instead, you often have to navigate multi-layered permissions—logging in as a standard user, transferring files locally, and escalating privileges via CLI to finalize configurations. In this tutorial, we will walk through the step-by-step procedure to safely renew an Apache SSL certificate under a restricted environment where WinSCP access is limited to a non-root user (sysops), requiring command-line intervention to complete the installation. Prerequisites A target Apache web server (CentOS/RHEL-based configuration using /etc/httpd/). A standard user account (sysops) with sudo privileges. The new SSL certificate (.crt) and CA bundle/chain file ready on your local machine. Step 1: Backup Existing Certificates Before making any changes to production security files, always back up the working configuration. Access the server via PuTTY using the sysops account, and switch to the root user or use sudo to create a backup of your existing keys: sudo cp /etc/httpd/server.crt /etc/httpd/server.crt.bak sudo cp /etc/httpd/server.key /etc/httpd/server.key.bak Step 2: Stage the New Certificates via WinSCP Because your WinSCP session cannot log in directly as root, you must stage the files in a directory your user owns. Open WinSCP and log in using your sysops credentials. Upload your new certificate files (nouveau_certificat.crt and nouveau_certificat_chain.pem) directly into your home directory: /home/sysops/. Step 3: Install and Replace the Certificates Now, return to your terminal session (PuTTY) to move the files from your staging directory to the protected Apache directory using elevated privileges. Copy the new primary certificate sudo cp /home/sysops/nouveau_certificat.crt /etc/httpd/server.crt Copy the new certificate chain / CA bundle sudo cp /home/sysops/nouveau_certificat_chain.pem /etc/httpd/server-ca.crt Step 4: Verify Permissions and Ownersh

We may just have gotten an early look at the Google Pixel Watch 5 - and from an unusual source. Randy Pitchford, the creator of the Borderlands game franchise, posted a pair of images of a watch on X, saying that his friend found it underwater while scuba diving near Saint Martin, as reported earlier […]

Nvidia's announcement that it's getting into the consumer laptop chip space with RTX Spark is huge. Apple has proved for years that Arm-based chips can perform incredibly well while also delivering great battery life - at least on the Mac. In the Windows world, performance hasn't fully matched up under Qualcomm chips, mostly in the […]