标签：#X

Ambrosia Energy wants to build power plants in less than 12 months while undercutting natural gas. It hopes to build gigawatts worth by 2030.

The RAMageddon crisis has got Microsoft rethinking its Xbox console hardware business. Xbox CEO Asha Sharma and Xbox strategy chief Matthew Ball have both revealed this week that Microsoft is reevaluating plans for its next-generation Project Helix console and exploring "radically different" console business models in the meantime. "We are working very hard to rethink […]

Redis is fast. But self-hosting Redis on a serverless stack is a nightmare — cold starts, connection pool exhaustion, and managing a persistent server that your serverless functions keep hammering. Upstash solves this with an HTTP-based Redis API that scales to zero, charges per request, and works natively with Next.js App Router. This guide covers the patterns that actually matter in production: cache-aside with proper TTLs, SWR (stale-while-revalidate), session storage, and pub/sub. Real code, real trade-offs. Read the full article with all code examples at stacknotice.com Why Upstash Over a Traditional Redis Instance Standard Redis uses persistent TCP connections. Serverless functions don't maintain persistent connections — every invocation potentially opens a new one. At scale, you hit ECONNREFUSED or max connection errors that are annoying to debug and expensive to fix. Upstash's @upstash/redis client talks over HTTP/REST. No connection pool, no connection limit headaches. Each request is stateless. This is exactly what Next.js Server Components and Route Handlers need. Other advantages: Pay per request — a cache that never gets hit costs $0 Global replication — low latency from any Vercel edge region Native Edge Runtime support — works in Next.js middleware Free tier — 10,000 commands/day, no credit card needed Setup npm install @upstash/redis // lib/redis.ts import { Redis } from ' @upstash/redis ' export const redis = new Redis ({ url : process . env . UPSTASH_REDIS_REST_URL ! , token : process . env . UPSTASH_REDIS_REST_TOKEN ! , }) Pattern 1: Cache-Aside // lib/cache.ts import { redis } from ' ./redis ' export async function withCache < T > ( key : string , fetcher : () => Promise < T > , options : { ttl ?: number ; prefix ?: string } = {} ): Promise < T > { const { ttl = 300 , prefix = ' cache ' } = options const cacheKey = ` ${ prefix } : ${ key } ` const cached = await redis . get < T > ( cacheKey ) if ( cached !== null ) return cached const data = awai

I recently built GeoPrizm , a free and open-source dashboard for tracking bilateral relations through global news event signals. The idea is simple: instead of reading dozens of headlines every day and trying to guess whether a relationship is improving or worsening, can we turn public news event data into a readable trend signal? GeoPrizm is my attempt at that. Website: https://www.geoprizm.com/en GitHub: https://github.com/Haullk/relationship-temperature The problem International relations are usually discussed through headlines, speeches, official statements, and expert commentary. That is valuable, but it creates a few practical problems: It is hard to compare country pairs on the same scale. A single headline can feel more important than it really is. Readers often see conclusions before they see the underlying signals. Most non-specialists do not have time to follow every event in detail. I wanted a lightweight way to answer one question: Based on public news event signals, is this bilateral relationship trending more cooperative, neutral, or tense? Data source: GDELT GeoPrizm uses the GDELT global news event database. GDELT monitors global news coverage and converts news reports into structured event records. These records include fields such as: actor countries event date CAMEO event category GoldsteinScale value number of mentions number of articles source information For GeoPrizm, the key idea is to focus on events where two countries appear as actors, then aggregate the cooperation or conflict signals over time. From event signals to an index Each bilateral pair is converted into a 0-100 relationship index. The midpoint is 50. Above 50 means the recent signal is more cooperative or favorable. Around 50 means the signal is relatively neutral or mixed. Below 50 means the recent signal is more tense or conflict-heavy. The rough process is: Select recent GDELT events for a country pair. Keep events where both actors are present and the GoldsteinScale value is

The exec, Emad Dlala, has left just a few months after being promoted to SVP of engineering and digital, TechCrunch has learned.

This is an updated rewrite of my 2021 article on protected routes . A lot has changed in the React ecosystem since then. React Router moved from v5 to v7, class components have faded out, and the patterns we use for authentication state have matured. This version reflects how protected routes are built in modern React applications. Almost every web application requires some form of authentication to prevent unauthorized users from accessing parts of the application meant for signed-in users only. In this tutorial, I'll show how to set up an authentication flow and protect routes from unauthorized access using modern React patterns: function components, hooks, React Router v6+, and the Context API. First things first Install the dependency: npm i react-router-dom That's it. React Router v6 and above ships as a single package, so you no longer need to install react-router and react-router-dom separately. It is worthy of note that we will not be using Redux for authentication state in this version. For something as simple as "is the user logged in?", React's built-in Context API is the standard approach today. Redux still has its place, but it is overkill here. The Auth Context Instead of writing to localStorage directly from components and reading it in random places, we centralize authentication state in a context. This gives us a single source of truth and a clean useAuth() hook we can call anywhere in the app. Create ./src/auth/AuthContext.jsx : import { createContext , useContext , useState } from " react " ; const AuthContext = createContext ( null ); export function AuthProvider ({ children }) { const [ user , setUser ] = useState (() => { // Rehydrate on page refresh const saved = localStorage . getItem ( " user " ); return saved ? JSON . parse ( saved ) : null ; }); const login = async ( username , password ) => { // In a real app, this is an API call to your backend. // We simulate it here with hardcoded credentials. if ( username . toLowerCase () === " admin

A few months ago I was doing a final pre-release review on a client project before handing it...

If you build agents on Base, two things landed recently that are worth connecting. First: Base shipped its own Agent Skills. There's now a base/skills repo with consolidated skills that teach an AI agent to connect to Base, deploy contracts, authenticate wallets, and run nodes — installed with one command via Vercel's npx skills CLI. Second: that CLI is part of a fast-growing, cross-agent ecosystem most crypto devs haven't clocked yet. So this post does two things — explains how npx skills and skills.sh actually work, and shows where the payment layer in Base's skills stops and how to extend it with x402 pay-per-call and batch disbursement . What npx skills actually is npx skills is an open CLI from Vercel Labs for installing "skills" — modular SKILL.md files that teach an agent a specific capability without stuffing everything into its context window. A few things make it different from what crypto devs usually expect: GitHub is the registry. There's no central package server. Any public GitHub repo with a SKILL.md at its root is a valid, installable skill. Install with npx skills add owner/repo . It's cross-agent. The same skill installs into Claude Code, Cursor, Codex, GitHub Copilot, Goose, Windsurf, Gemini, and dozens more. You write once; it works across the agent you (or your users) actually run. skills.sh is the directory + leaderboard. It ranks skills by real install counts pulled from telemetry, with all-time, trending, and hot lists. There's no editorial submission step — you publish by putting a skill in a repo, and installs surface it. The format underneath — SKILL.md — is an open spec, which is why Base, Vercel, Anthropic, and a long tail of independent devs all use the same files. Here's Base's install, for reference: # Base's official agent skills npx skills add base/skills --skill build-on-base npx skills add base/skills --skill base-mcp build-on-base is a consolidated Base dev playbook; base-mcp wires up a Base MCP server that gives an agent a wall

Netflix's response: "Absurd."

Exactly one year ago, my terminal was a blank slate. I started where almost everyone does , wrestling with HTML, CSS, and JavaScript, trying to understand the web pixel by pixel. What began as curiosity quickly turned into a full obsession. I went from building simple static pages to diving deep into full-stack development. Here’s what that intense first year of constant building, breaking things, and shipping real projects has looked like. The Leap into Modern Frameworks Once vanilla JavaScript started feeling limiting, I jumped into React . Component-based thinking completely changed how I approached interfaces. Then came Next.js — it bridged client-side beauty with server-side power and pushed me into a true full-stack mindset. The Ultimate Test: Lynvista Safaris The biggest challenge was building lynvistasafaris.com , a live travel booking platform for a real client. This project forced me far beyond tutorials and into real engineering problems. I had to implement: Payment infrastructure from scratch with Daraja API (M-Pesa STK pushes) and Paystack for international transactions. A robust database layer using Drizzle ORM + MySQL. Custom business logic , including a multi-currency pricing system with special validation rules for currencies like GBP. It was messy , many late nights debugging webhooks, schema mismatches, and edge cases , but shipping it taught me more than any course ever could. What One Year Taught Me Syntax is just a tool. The real skill is learning how to break down complex problems, debug effectively, and keep iterating even when things break in production. I’m incredibly proud of the progress I’ve made in 365 days (402 contributions later), but I know I’m still at the very beginning. For the next phase, I’m focused on shipping more projects, writing about the crazy bugs I encounter, and deepening my architectural and full-stack skills. If you want to see what I’m building right now, check out my GitHub .

How KlineVision does AI technical analysis with Next.js + Gemini, draws it on the real candles, and verifies every call it makes after the fact — misses included. Most "AI stock analysis" tools confidently tell you a chart looks bullish and then never look back. I wanted the opposite: a tool that records every call it makes and later checks whether the market actually agreed — and publishes the hit rate, misses included. That one constraint — keep yourself honest — ended up shaping most of the interesting engineering. Here's how KlineVision is put together. What it does Type a ticker ( AAPL , 600519.SH , 0700.HK ) — or drop a chart screenshot. You get a structured read : trend, support/resistance, candlestick + chart patterns, and 缠论 (Chan theory) structure — drawn directly onto the real candles , not hand-waved in prose. Works across US, A-shares, and Hong Kong markets. The stack Next.js (App Router) on Vercel Supabase (Postgres + RLS) for data & auth Gemini 3 Flash for the analysis itself EODHD + Yahoo Finance for market data GitHub Actions + Vercel Cron for the background jobs PostHog for product analytics Now the parts that were actually interesting to build. 1. "Never analyze fake data" The market-data layer had a silent fallback: when a provider rate-limited, it returned synthetic candles so the UI never broke. Great for a demo, terrible for a product whose entire value is trust — the model would write a beautiful, confident analysis of a chart that never existed . The fix was to make the data layer fail honestly : Yahoo (primary) → EODHD (fallback) → if only demo data is available → 503, no analysis If we can't get real candles, the user gets "live market data temporarily unavailable" — not a hallucinated read. For a trust tool, a silent fallback to fake data is the worst bug on the board. 2. Make the AI show its work A text blob saying "there's a double bottom" isn't credible. You have to see it on the chart. So the model returns structured overlays keyed to

Use-after-free bug can be exploited to evade sandbox defenses.

Orbital founder Euwyn Poon built 250,000 scooters at Spin. Now he wants to launch 10,000 space data centers.

A decade ago, commuter buses attracted big protests in San Francisco. Years later, the city is still feeling the repercussions.

The startup is one of many entering the RV space, but it's banking on a hybrid power system that can go far beyond campsites.

Imagine speaking in English, and having listeners from all over the world hear you translated into...

This article was originally published on aicoderscope.com TL;DR : Cursor Tab (the inline ghost-text autocomplete) breaks in 8 distinct ways. Roughly 70% of cases are fixed in under a minute by checking three things: the toggle in Settings, your extension list for Copilot, and your usage quota. The remaining 30% need a corporate proxy fix or a toggle-restart cycle. After this guide you will: Know which of the 8 root causes matches your specific symptom Have the exact settings path and command for each fix Understand the 2,000-completion monthly cap on the Hobby plan that silently kills suggestions at month-end Honest take : Every "Cursor Tab is broken" thread in 2026 falls into one of these eight buckets. Go through the three-step quick check first — most readers fix it there. The 60-second triage: three checks before anything else Open Cursor and verify these in order. They resolve 70% of cases. 1. Is Cursor Tab actually enabled? Press Ctrl+Shift+J (Windows/Linux) or Cmd+Shift+J (Mac) to open Cursor Settings, then go to Features > Cursor Tab . The toggle should be on. If it's off — and this happens more than it should after updates — flip it, restart Cursor, done. You can also check from the status bar at the bottom right of the editor. A small "Tab" indicator shows whether inline completions are active. If it shows disabled, click it to re-enable. 2. Have you hit the free quota? On the Hobby plan, Cursor gives you 2,000 tab completions per month . During active coding at a normal acceptance rate, you can burn through 50–100 per hour. If you're late in the billing cycle, open Settings > Usage & Limits and check the completions counter. Completions reset on your account anniversary date, not the calendar month. When you hit 2,000/2,000, tab completion stops silently — no error, no banner, just nothing appearing. Upgrade to Pro ($20/mo) or wait for the reset. 3. Is GitHub Copilot or Tabnine installed? If you migrated from VS Code with extensions intact, you may have G

The interpreter's variable lookup is now blazing through arithmetic loops at a 57% faster pace. But this isn't just about raw speed — four tracker items were checked off the list, culminating in a more robust system. All rolled out on submain, a direct result of a thorough four-pillar audit. BindingId replaces string hashing at runtime The heavyweight change came from tracker #009. Previously, our interpreter was busy hashing variable names every time they were accessed. That was a repeat offender in wasted cycles. Now, by using a pre-assigned numeric BindingId, we seize efficiency. The semantic phase was already handing out these IDs, but the runtime kept adding the overhead back. It doesn’t anymore. ScopeFrame.vars has transitioned to a HashMap equipped with a zero-cost identity hasher keyed by u32 binding IDs. Name-based lookups are still around but tucked away for less frequent operations like string interpolation. Fixes were necessary upstream: ConstDecl and semantic_impls now hold onto their BindingId, making sure our semantic phase pipelines gracefully into the interpreter's primary key system — narrowing the gap with JIT's variable handling. Here's how the numbers shine on a Windows release build: arith_loop (5M iterations): from 5744ms down to 2481ms (56.8% boost) nested_loops (4M iterations): from 2675ms down to 1796ms (32.8% boost) fib_recursive: from 6835ms down to 6488ms (merely 5.1% faster due to call-frame constraints) Our findings align with expectations: recursive functions aren't bogged down by variable lookups as much as by setting up call frames. Array bounds errors stop lying Misleading diagnostic labels are on their way out, thanks to tracker #002 and #032. Attempts to access out-of-bounds array indices once triggered an error as unhelpful as variable 'index 5' has not been declared . Not anymore. Changes came in two waves. First, we introduced a new error variant: RuntimeError::IndexOutOfBounds { pos, index, length } . Then, three runtime.rs c

Waymo has acquired a massive 5,500-acre proving ground in Arizona owned by Route 14 Investment Partners LLC, a Delaware shell company associated with Apple, according to documents filed with Maricopa County.

Amazon is expanding its print-on-demand features to AI-generated designs created using Alexa for Shopping for products like T-shirts, water bottles, and hoodies. Shoppers can use text prompts to generate images that are then printed on to blanks for sale on Amazon. They can then share the link to the design so other people can buy […]