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What happens when you stop picking a stack and let each protocol pick one for you. Every engineering team has a stack. Ours has seven, and we did not decide on any of them. Nevai is a self-hosted, end-to-end encrypted workspace built on Matrix. Part of it is a set of bridges — 25 of them — connecting Discord, Telegram, WhatsApp, Signal, iMessage, Messenger, Instagram, Slack, Google Chat, LINE, WeChat, KakaoTalk, Skype, GroupMe, SMS, email, IRC, XMPP, Zulip, Mattermost, Revolt, Mumble, QQ, X and LinkedIn into one place. We started out intending to standardise. We ended up with this: Language Bridges Go 12 TypeScript 5 Python 4 JavaScript 1 Kotlin 1 PLpgSQL 1 Slice 1 Nobody sat in a room and chose that distribution. It is what you get when the protocol decides. Go wins where the protocol was reverse-engineered WhatsApp, Signal, iMessage, Messenger, Instagram, Telegram, X, WeChat, QQ, Skype, LinkedIn, email. Twelve bridges, and the reason is the same every time: the mature libraries for those protocols are written in Go. That is not a claim about Go being a better language. It is a claim about where a decade of reverse-engineering effort happens to live. If you want to speak WhatsApp's protocol without running a browser session, you use what exists, and what exists is Go. Look at what leaks in around the edges and the picture gets sharper: Signal is 86% Go and 13% C — the C is libsignal, and you do not reimplement libsignal. iMessage is 96% Go and 3% Objective-C — because iMessage runs on macOS, and at some point you have to talk to the operating system in its own language. Those percentages are the honest part. A bridge is mostly your code and a small amount of somebody else's, and the small amount is usually the part that matters most. Python wins where the API is boring Google Chat, Zulip, KakaoTalk, LINE. Documented HTTP APIs, JSON in and JSON out, no protocol archaeology required. There is no performance argument here. These bridges are not throughput-bound; they

Arguably the coolest new photo feature for the Pixel 11 lineup is Google's new Camera Looks, which process image data differently at the sensor level to produce photos that don't have that "smartphone" look. The result is new styles like "Digi," which mimics the style of photos taken by older digital cameras. But to use […]

Natural gas prices could triple in some parts of the U.S., which could saddle hyperscalers with massive bills to power their AI data centers.

The Administrative Office of the U.S. Courts told TechCrunch that it will start disclosing how many times judges authorized the use of spyware to wiretap suspected criminals.

High-Speed eBPF/XDP Packet Filtering for Linux Server DDoS Mitigation Executive Summary Executive Summary & Key Security Takeaways ← Back to Articles Linux Kernel • XDP DDoS Defense High-Speed eBPF/XDP Packet Filtering for Linux Server DDoS Mitigation By Zyekh Abdul Qadir Jailani Published: 2026-08-04 15 min read (1750+ Words) Share Download .md Download .pdf eBPF/XDP Driver-Level Packet Ingestion & Ultra Fast Packet Dropping Executive Summary & Key Security Takeaways XDP_DROP Early Decision: Drop malicious UDP/SYN floods before allocating sk_buff memory. Kernel Map Invalidation: Dynamic IP blocklists via eBPF BPF_MAP_TYPE_HASH maps. Zero-Copy Performance: Process 10M+ packets per second on commodity server hardware. Clang/LLVM BPF Compilation: Build C programs directly into BPF bytecode targets. Table of Contents Understanding XDP Architecture vs Traditional Linux SKB Allocation XDP Packet Processing Actions (XDP_DROP vs XDP_PASS) Writing a Production XDP Packet Filter in C Compiling & Loading Bytecode Targets via Clang/LLVM Dynamic Blocklist Management via BPF Maps High-Throughput Packet Benchmark Verification Frequently Asked Questions (FAQ) 1. Understanding XDP Architecture vs Traditional Linux SKB Allocation Standard Linux network processing allocates a complex kernel socket buffer data structure (sk_buff) for every incoming packet before firewall rules (iptables/nftables) can evaluate the packet. Under volumetric DDoS attacks (such as 10 Million Packets Per Second UDP floods), the CPU time spent allocating and freeing sk_buff structures exhausts kernel memory and CPU cache lines, causing severe packet drops and server unresponsiveness. eXpress Data Path (XDP) provides a high-performance bare-metal packet processing framework. XDP programs execute eBPF bytecode directly inside the network driver's RX ring buffer before sk_buff memory allocation occurs. # Inspect network interface driver XDP support ip link show eth0 2. XDP Packet Processing Actions (XDP_DROP vs

Joi AI hired 10 people to masturbate using AI companions as part of a monthlong “wellness” study. The company claims the practice could help “solve male loneliness.”

The partnership is expanding beyond the initial market of Zagreb, Croatia to four additional European cities.

Can electrifying your workout offer a shortcut to a stronger, fitter you? I sweated in a skintight EMS suit for two months to find out.

Expedia Group has open-sourced mockql-rs, a Rust CLI that fills @mock-annotated GraphQL fields with LLM-generated data at request time. It follows Airbnb's @generateMock in April and a GraphQL Foundation RFC opened in February. All three solve the same problem with different architectures, and two use the same directive name with incompatible semantics. By Steef-Jan Wiggers

From the multibrained octopus to the bitty brain organoid, we’re all just inference engines making flawed bets on the future. Here are the five insights your brain will need to survive.

One woman’s meth addiction was so bad, the only option left might have been brain surgery. Then a single session of noninvasive, focused ultrasound seemed to do what years of treatment could not.

Rx.NET 7.0 has been released with a narrowly focused change aimed at reducing deployment size for Windows applications. The new version separates WPF, Windows Forms, UWP, and Windows Runtime integration from the main System.Reactive package, avoiding cases where self-contained applications could acquire tens of megabytes of unused framework dependencies. By Edin Kapić

Zero-Trust SSH Access Blueprint: FIDO2 Hardware Keys & SSH Certificate Authority Executive Summary Executive Summary & Key Security Takeaways ← Back to Articles Cyber Security • Zero Trust SSH Zero-Trust SSH Access Blueprint: FIDO2 Hardware Keys & SSH Certificate Authority By Zyekh Abdul Qadir Jailani Published: August 3, 2026 8 min read (1,250+ Words) Share Download .md Download .pdf Zero-Trust Infrastructure Blueprint for FIDO2 Hardware Tokens & SSH Certificate Authority Executive Summary & Key Security Takeaways Eliminate Static Keys: Migrate from static authorized_keys deployment to short-lived SSH Certificates. FIDO2 Hardware Bound: Enforce ed25519-sk key pairs tied to physical security tokens (YubiKey/FIDO2). Centralized Authority: Use an offline SSH Certificate Authority (CA) to sign user access requests with automatic 8-hour expiration. Zero Administrative Sprawl: Adding or revoking user permissions requires zero modifications on target servers. Table of Contents The Problem with Static SSH Public Keys Hardware Security Keys: OpenSSH FIDO2 / U2F Setting Up a Centralized SSH Certificate Authority Related Privacy & Security Tools Verification & Security Audit Checklist Frequently Asked Questions (FAQ) Traditional SSH key management across growing server fleets suffers from a critical flaw: static public key sprawl. Managing thousands of ~/.ssh/authorized_keys files across production instances creates massive administrative overhead, increases the blast radius of compromised developer workstations, and makes offboarding security audits nearly impossible. A true Zero-Trust SSH Access Model replaces static SSH keys with two cryptographic pillars: FIDO2 / Security Key Hardware Tokens ( ed25519-sk ): Private key material never leaves the physical YubiKey token and requires physical touch plus user PIN. SSH Certificate Authority (SSH CA): Short-lived SSH certificates (e.g., valid for 8 hours) signed by a centralized CA key, eliminating manual authorized_keys deploym

Netflix plans to shut down two of its gaming studios, as reported by Game File and Variety, as it makes a bigger shift toward party games and titles streamed to TVs. One of the studios being shut down is Night School Studio, creators of the Oxenfree series. Netflix bought Night School in 2021, and it […]

Support SMS inboxes are usually a routing problem before they are an AI problem. Someone asks about billing. Someone else needs technical support. A third person wants to talk to sales. The app has to understand the message, pick the right destination, reply to the customer, and remember what happened. This TypeScript example does that on Telnyx Edge Compute with the Agent SDK. Code: https://github.com/team-telnyx/telnyx-code-examples/tree/main/agent-sms-triage-bot What it builds agent-sms-triage-bot receives inbound SMS webhooks, classifies each message into one of four topics, looks up the route for that topic, replies by SMS, and stores triage history in durable actor state. The topics are: billing support sales general The default route table maps those topics to queue names: billing -> billing-queue support -> support-queue sales -> sales-queue general -> general-queue The request flow Inbound SMS -> POST /webhooks/sms -> TriageAgent.triage(from, text) -> Telnyx AI Inference classifies topic -> durable route table lookup -> SMS reply -> triage history update The app uses one TriageAgent actor per inbound number. That actor stores route rules, recent history, total messages, and topic counts. The main routes POST /webhooks/sms receives Telnyx message.received events POST /debug/triage simulates inbound SMS POST /routes updates the route table GET /routes lists route rules GET /history returns recent triage history GET /debug/state inspects actor state GET /health/liveness and GET /health/readiness provide health checks The Agent SDK piece The core class is TriageAgent . It extends the Agent SDK Agent class and uses durable state for: route table triage history total message count topic counts The AI classification call uses the Telnyx binding: const completion = await this . env . TELNYX . ai . openai . chat . createCompletion ({ model : this . env . AI_MODEL || " moonshotai/Kimi-K2.6 " , messages : [ { role : " system " , content : CLASSIFY_SYSTEM_PROMPT }, { r

X is expanding the open source code behind its 'For You' feed and launching new transparency tools that show users when its ranking systems have affected their accounts or posts.

I kept hitting the same small friction: I'd want to quickly rewrite an email, clean up some text, or summarize a long thread — and every tool wanted me to sign up, pick a plan, or watch an ad first. For a ten-second task, that's absurd. So I built the thing I wanted: a set of free, no-signup AI text tools , each doing one job well. This is a quick write-up of the stack and the decisions behind it. 👉 Live: https://www.texttoolsai.app The core idea: one tool, one job, zero friction Instead of a single mega-app, it's a collection of single-purpose tools — rewrite, tone change, summarize, prompt generation — each on its own page. You land, paste, get output. No account, no modal, no paywall. The "no signup" rule forced good constraints: everything has to work instantly and statelessly, which kept the whole thing simple. The stack Next.js (App Router) — server components for the content/SEO pages, client components only where the tool actually needs interactivity. Vercel for hosting — the deploy story is boringly good, which is what you want. An LLM API on the backend — the browser never sees a key; requests go through a Next.js route handler that owns the prompt and the provider call. Tailwind for styling — fast to iterate, easy to keep consistent across dozens of tool pages. One decision that paid off: data-driven pages Every tool is defined as a config object (label, placeholder, system prompt, endpoint) rather than a hand-built page. Adding a new tool is mostly adding data, not wiring up new routing. That's what made it realistic to ship a lot of tools without the codebase turning into spaghetti. // simplified shape { slug: 'rewrite', label: 'Paste your text', endpoint: '/api/tools/rewriter', systemPrompt: '...' } The route handler resolves the endpoint key against a map of system prompts, so the API surface stays tiny even as the tool count grows. What I'd tell anyone building something similar Keep the API key server-side. Obvious, but easy to leak through a miscon

People with schizophrenia face a perfect storm of dangers on a hotter planet.

How We Built a 160-Article AI Education Platform with Next.js and Static HTML Three months ago, I launched IAcademy — an AI education platform in Spanish with 160+ free guides covering everything from prompting basics to autonomous agents, LLM deployment, and MCP servers. Here's what worked, what didn't, and the architecture behind it. Why Spanish AI Education is Underserved The AI education space is dominated by English content. Coursera, Udemy, DeepLearning.AI — all English-first. Spanish-speaking professionals (500M+ people) get translated scraps or nothing. The opportunity: 0% competition on keywords like "agentes ia" (400 monthly searches), "herramientas ia" (400), "formación ia" (250). In English, these keywords have 30-50% competition. In Spanish, nobody's writing quality content. Architecture: Why Static HTML, Not a CMS Each blog post is a standalone index.html file. No WordPress, no Gatsby, no MDX compilation step. site/blog/ ├── agentes-ia-que-son/ │ └── index.html ├── herramientas-ia-guia/ │ └── index.html ├── formacion-ia/ │ └── index.html └── ... (160+ directories) Why this approach: Zero build time. Adding an article = creating a directory + file. No compilation, no hydration errors, no framework upgrades breaking 160 pages. Perfect SEO control. Every <title> , <meta> , JSON-LD schema, internal link, and heading hierarchy is hand-crafted per page. No CMS template imposing its structure. Instant deploy. Push to GitHub → Cloudflare Pages deploys in ~30 seconds. No build queue. No JavaScript required for content. Google indexes immediately. Core Web Vitals are perfect — there's nothing to load. The dynamic parts (auth, course portal, labs) use Supabase + vanilla JS. But the blog — which is the SEO engine — is pure static HTML. Content Strategy: Niche Prompts Beat Head Terms After 3 months, here's what ranks and what doesn't: What ranks (top 10 in Google): prompts-ia-facturacion — prompts for accountants (position 8.4) prompts-ia-logistica — prompts for lo

If you've ever run a Linux VM in VirtualBox and had copy-paste between your host and guest just... stop working, this post is for you. What started as a simple "my clipboard isn't syncing" turned into a proper detective story involving conflicting installations, a kernel module stuck "in use," and a systemd service quietly failing on every single boot. Here's the full walkthrough — what broke, how we figured out why, and how we fixed it for good. The Setup I run a Kali Linux VM inside VirtualBox on my host machine, mainly as a home lab for practicing infrastructure and security tooling. One day, shared clipboard between my host and the guest just stopped working. My first instinct was to run apt update && apt upgrade — but nothing changed. That's actually an important clue we'll come back to: apt upgrades regular packages, but it does not automatically rebuild or reinstall VirtualBox Guest Additions , which is the component actually responsible for clipboard sharing. What Actually Makes Clipboard Sharing Work Before diving into the fix, it helps to understand the moving parts, since "clipboard sync" isn't one single thing — it's three things working together: The vboxguest kernel module — a driver inside the guest OS that lets it talk to VirtualBox itself. VBoxService — a background daemon (runs as root) that handles ongoing communication with the hypervisor: time sync, clipboard, shared folders, and more. VBoxClient — a per-user process that specifically handles the clipboard and display integration, and talks to VBoxService through the kernel module. If any one of these three breaks, clipboard sharing breaks — and the error messages don't always make it obvious which one is the culprit. First Round: The Standard Checklist We started with the usual suspects for VirtualBox clipboard issues: Enable Bidirectional clipboard : In the VM window, under Devices > Shared Clipboard , this needs to be set to Bidirectional (or the direction you want). It resets sometimes after