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🔥 jlcodes99 / cockpit-tools - 🚀 通用 AI IDE 账号管理工具:支持 Antigravity / Codex / GitHub Copilot /

GitHub热门项目 | 🚀 通用 AI IDE 账号管理工具:支持 Antigravity / Codex / GitHub Copilot / Windsurf / Kiro / Cursor / Gemini-cli / CodeBuddy,多账号切换、配额监控、自动唤醒与多开实例管理。 🚀 Universal AI IDE account manager for Antigravity / Codex / GitHub Copilot / Windsurf / Kiro / Cursor / Gemini-cli / CodeBuddy, with multi-account switching, quota monitoring, wake-up automation, and multi-insta | Stars: 15,751 | 75 stars today | 语言: Rust

2026-08-14 原文 →
AI 资讯

Who’s Tracking You? Use This New Service to Find Out

It can be daunting to determine who's responsible for showing ads on the websites we visit, or who's harvesting data from the mobile apps we use every day. That information is already semi-public, but it is not easily parsed and traditionally much of it has remained walled away in the hands of large advertising platforms. Not anymore: A powerful and free new service called DecryptAds scrapes and correlates this adtech data and makes it simple to quickly learn a great deal about the entities that are tracking you.

2026-08-14 原文 →
AI 资讯

Help build a monument to that ‘sad little bitch’ Elon Musk

Cards Against Humanity is gearing up to build "something that will annoy Elon Musk," and it's crowdfunding the project with its usual flavor of vulgarity. The company behind the card game announced plans to build "a grand monument" to Musk on the parcel of land it owns near Starbase, Texas, with the aim to "make […]

2026-08-14 原文 →
开发者

Close the Loop Before You Open a New One

Ten things started is not progress. It's ten open tabs in your head, each one costing rent. Every unfinished task keeps a little of your attention hostage. You feel busy. You are just fragmented. Finishing one small thing returns more energy than starting three. So close the loop. Merge the PR. Send the message. Delete the branch. An empty background is where good work actually happens. Done is quiet. Chase the quiet. – Serguey Asael Shinder

2026-08-14 原文 →
AI 资讯

Suno is trying to look more like a real music production tool

Suno is releasing Studio 2.0 with significant upgrades that push it closer to an actual digital audio workstation (DAW), rather than a bare-bones audio editor with generative AI features. The biggest addition is undoubtedly MIDI support. Suno says that MIDI was its most requested feature, and it's basically a prerequisite for any modern DAW. Unfortunately, […]

2026-08-14 原文 →
AI 资讯

Anthropic's $6B Decart deal is a robotics play disguised as a compute play

Bloomberg reported this morning, August 13, that Anthropic is in talks to buy Decart AI for around $6 billion. Talks, not a signed deal. That distinction matters and I will come back to it. What caught my attention is not the number. It is where Decart came from. The Minecraft thing Decart got famous for Oasis: a playable Minecraft-looking world that no game engine was rendering. The model predicted every next frame based on what you pressed on the keyboard. 20 FPS, interactive, no scene graph, no collision system, no assets. Just a model hallucinating a consistent world fast enough that your hands believed it. In late 2024 that read as an impressive demo with no obvious business behind it. The company was founded in 2023. It has raised over $450M, was valued at $3.1B before this year's round, and its current research page describes three product lines: Oasis , a world model, now explicitly positioned for physical AI and robotics rather than gaming Lucy , a real-time video model running live at 30 FPS DOS , the Decart Optimization Stack: hardware-aware model design, custom kernels, proprietary compilers, inference optimization The demo was the marketing. DOS is the engineering. The reported reason is not robotics Read the actual reporting carefully. Fortune says a deal would bring Decart's video-simulation and chip-efficiency technology into Anthropic's inference team. Bloomberg's sources point at the same thing: the chip efficiency work could help existing infrastructure absorb more demand. So the sourced story is compute economics. Anthropic is compute constrained, spending enormously on capacity, and DOS is a margin lever that applies to every single Claude request on day one. That is a boring, completely rational reason to spend $6B. It does not need a robotics narrative at all. I still think the robotics reading is in there. Why Two things sit underneath. First, Anthropic held acquisition talks with Physical Intelligence this spring. The Information reported it

2026-08-13 原文 →
AI 资讯

Why Rust and WebAssembly Are Replacing JavaScript for Heavy AI Workloads in 2026

Why Rust and WebAssembly Are Replacing JavaScript for Heavy AI Workloads in 2026 While JavaScript remains the reigning language for web UI rendering, high-throughput client-side compute—such as local browser AI inference, video encoding, and cryptographic verification —has completely shifted to Rust compiled to WebAssembly (WASM) . In 2026, running 1B+ parameter models directly inside the browser using WebGPU and WASM SIMD has become standard practice. ⚡ Benchmarks: JS vs WASM SIMD execution Execution Time (Lower is Better) ┌────────────────────────────────────────────────────────┐ │ JavaScript (V8 Engine) : █ █ █ █ █ █ █ █ █ █ 1,420 ms │ │ Rust WASM SIMD : █ █ 210 ms │ └────────────────────────────────────────────────────────┘ Building a Rust WASM Compute Module Add the wasm-bindgen dependency in your Cargo.toml : [package] name = "wasm_ai_engine" version = "0.1.0" edition = "2021" [lib] crate-type = [ "cdylib" ] [dependencies] wasm-bindgen = "0.2" Implement high-speed array processing in src/lib.rs : use wasm_bindgen :: prelude :: * ; #[wasm_bindgen] pub fn process_tensor_data ( inputs : & [ f32 ], multiplier : f32 ) -> Vec < f32 > { inputs .iter () .map (| & x | x * multiplier ) .collect () } #[wasm_bindgen] pub fn compute_cosine_similarity ( vec_a : & [ f32 ], vec_b : & [ f32 ]) -> f32 { let dot_product : f32 = vec_a .iter () .zip ( vec_b .iter ()) .map (|( a , b )| a * b ) .sum (); let norm_a : f32 = vec_a .iter () .map (| a | a * a ) .sum :: < f32 > () .sqrt (); let norm_b : f32 = vec_b .iter () .map (| b | b * b ) .sum :: < f32 > () .sqrt (); if norm_a == 0.0 || norm_b == 0.0 { return 0.0 ; } dot_product / ( norm_a * norm_b ) } Compile directly to WebAssembly: wasm-pack build --target web Integrating into Next.js / Frontend Stack import init , { compute_cosine_similarity } from ' ./pkg/wasm_ai_engine.js ' ; async function runVectorSearch () { await init (); const vec1 = new Float32Array ([ 0.12 , 0.45 , 0.98 ]); const vec2 = new Float32Array ([ 0.15 , 0.42 ,

2026-08-13 原文 →
AI 资讯

Does Google even want to win at AI?

Today on Decoder, I’m talking with Hayden Field, The Verge’s senior AI reporter, about a question that’s been rocketing around the tech industry for the past week: Is Google losing the AI race? That’s because last week Google announced a bombshell reorganization of its AI division, Google DeepMind. Jeff Dean, the company’s chief scientist, is […]

2026-08-13 原文 →