开发者
A new way of coding!
Welcome to ForkMesh World Most developer tools start with another dashboard. We started with a beach. Not because developers desperately needed virtual sand, but because software is built by people, and people spend way too much time staring at rectangular windows. We're building ForkMesh World , a place where developers, open-source communities, and companies can actually hang out while building software. Not another Slack clone. Not another Zoom call. Something that's actually fun. You finish reviewing a pull request. Instead of closing your laptop, you walk outside your team's office. Someone is flying a drone over the island. Another team is racing cars down the road. A few contributors are hanging out on the beach after finishing a release. Someone jumps off the roof because... honestly, why not? (Don't try that in real life. Gravity has terrible UX.) This isn't replacing Git. It's making the community around Git feel alive. Your own office Every company and open-source project can have its own space inside ForkMesh World. Think of it as your team's home. A place for: Team meetings Community events Contributor onboarding Product demos Hackathons Launch parties Casual conversations Instead of sending someone a Discord invite and six documentation links, imagine saying: "Come by our office." Built for developers ForkMesh World is part of the larger ForkMesh ecosystem. ForkMesh is our open-source federated Git platform that lets developers own and preserve their repositories across a network instead of depending on a single hosting provider. We're trying to make developer infrastructure more resilient, while also making it a little more fun. Because open source shouldn't feel like filling out tax forms. More is coming We're only getting started. Some of the things we're working on include: 🏢 Company offices 🏖️ Beaches 🚗 Cars 🚁 Drones 🪂 Rooftop jumps (because games should be fun) 🎉 Community events 💬 Developer meetups 🛠️ Interactive spaces for open-source projects
AI 资讯
Gaming and IRL worlds collide in Jumanji: Open World trailer
"I'm beginning to suspect we are not in Jumanji."
AI 资讯
Remarkable’s refurbished bundle is an awesome deal that’s over $350 off
A lot of us here at The Verge are fans of Remarkable’s digital note-taking tablets, and right now one of its higher-end options is much cheaper than usual. The Remarkable Paper Pro normally sells for $629 on its own, but Woot is currently offering a refurbished bundle for $449.99 through July 31st. It includes the […]
AI 资讯
Why We Built Bitweave: Sub-Millisecond Hybrid Retrieval in <1.1 MB RSS Memory
When building local RAG (Retrieval-Augmented Generation) applications, edge agents, or serverless AI pipelines, developers usually hit a wall with standard vector stores: memory overhead. Running a dedicated vector database locally often demands hundreds of megabytes—or gigabytes—of RAM just to keep indices warm. On the flip side, lightweight local options like scanning raw JSON files or querying SQLite don't scale well when vector dimensions climb into the thousands (1536d+). We built Bitweave to solve this exact trade-off: a zero-copy, SIMD-accelerated hybrid retrieval engine in Rust (with Python bindings) that handles categorical filtering and vector search while locking its active heap footprint under 1.1 MB RSS. The Architecture: How Bitweave Achieves Sub-Millisecond Speed at <1.1 MB RAM Bitweave relies on a 3-part design to maximize search speed while keeping memory consumption negligible: [ Categorical Filters ] ---> Bit-Sliced Bitmaps │ ▼ [ Query Vector (1536d) ] --> 1-Bit SIMD Pre-Filtering (Hamming Distance) │ (Top K Candidates) ▼ [ Raw Embeddings Buffer ] -> Zero-Copy Float32 Rescoring (exact_rescore=True) │ ▼ Top-K Results Array (NumPy) Zero-Copy Memory Mapping (memmap2) Instead of deserializing index files into Python RAM or Rust heap space, Bitweave uses memory-mapped files (.bweave). The operating system's page cache handles lazy loading of index segments directly from disk into virtual address space. As a result, the active RSS memory footprint remains static around 1.1 MB, whether your index holds 5,000 or 200,000 records. 1-Bit Vector Quantization & SIMD Hamming Distance High-dimensional float32 vectors (1536d) are quantized down to 1-bit sign masks (where values > 0 map to 1 and <= 0 map to 0). During pre-ranking, Bitweave uses SIMD bitwise XOR and POPCNT operations to compute Hamming distances across candidate vectors in microseconds. Zero-Copy 2-Pass Float32 Rescoring (exact_rescore=True) Quantization speeds up initial candidate selection, but f
AI 资讯
Perplexity employee who worked on Comet launches an AI browser aimed at knowledge work
Polar has come out with an AI-first browser aimed at knowledge workers, and it has now raised a $5.7 million seed round led by Madrona.
AI 资讯
TraceLLM
OpenTelemetry for production AI applications Discussion | Link
AI 资讯
Encore AI raises $30M to build AI agents that learn from customer calls
The startup analyzes calls, messages, and CRM data to identify effective sales techniques and turn them into playbooks for AI agents.
AI 资讯
‘No one’s making a phone like this’: Light’s co-founders on building for the anti-smartphone generation
With the Light Phone, Kaiwei Tang and Joe Hollier have spent over a decade exploring the value of simplicity in our relationship to technology, partnering along the way with players like Andrew Yang, Kendrick Lamar, and Pete Davidson. Now, with a new flip phone and a growing wave of “attention activists” pushing back against Big Tech, they think the rest of […]
开源项目
PRNotch
GitHub pull requests in your Mac's notch Discussion | Link
科技前沿
Are remote car starters still worth it in 2026?
Some newer vehicles include the feature, but to keep it, you'll have to pay monthly. You can also buy remote starters outright.
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🔥 nolabs-ai / nono - Sandbox any AI agent in seconds - zero setup, zero latency.
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🔥 shaka-project / shaka-player - JavaScript player library / DASH & HLS client / MSE-EME play
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🔥 fspecii / ace-step-ui - 🎵 The Ultimate Open Source Suno Alternative - Professional U
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🔥 lightseekorg / tokenspeed - TokenSpeed is a speed-of-light LLM inference engine.
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