🦀 Rust 1.94.0 is out !
• array_windows iterator for fixed-size slice windows
• Cargo include support in .cargo/config.toml
• Cargo now parses TOML 1.1
• New stabilized APIs (LazyCell, LazyLock, iterator helpers)
• Expanded platform support (incl. more RISC-V features)
Google finally launched an official Rust CLI (gmail, drive, sheets, gmail, calendar, admin, keep, meet 10+ more).
#rust#rustlang#programming
https://t.co/6l7GnjJDlK
🇫🇷🤖 L'État a développé un serveur MCP pour interroger https://t.co/fkZfFM9DiO, sa plateforme open data, via les chatbots IA !
C'est encore une fois un travail très cool de la DINUM, et c'est open source.
Anthropic dropped a 33-page guide on Claude Skills...And this changes how serious teams build AI workflows
A Claude Skill is basically a reusable workflow in a folder. One https://t.co/CTRveEHjoi file teaches Claude exactly how you want tasks done consistently every time
The real insight isn’t Skills....It’s how to design them properly:
• Build micro-skills, not monoliths
• Keep instructions short and decisive
• Move heavy context into references and assets
• Always refine generated Skills manually
• Connect Skills to tools via MCP and hooks
That’s when AI stops being a chatbot… and starts becoming a system
Link - https://t.co/oUVuXLnSyf
https://t.co/pBRFjyTJgE
Kimi-K2.5 is now live on Hugging Face. Open source, multimodal, and outperforming Opus 4.5 for builders who want freedom and power.
Try it today: https://t.co/hAHzmgoHyV
You can now run 70B LLMs on a 4GB GPU.
AirLLM just made massive models usable on low-memory hardware.
𝗪𝗵𝗮𝘁 𝗷𝘂𝘀𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱
AirLLM released memory-optimized inference for large language models.
It runs 70B models on 4GB VRAM.
It can even run 405B Llama 3.1 on 8GB VRAM.
𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀
AirLLM loads models one layer at a time.
Instead of loading everything:
→ Load a layer
→ Run computation
→ Free memory
→ Load the next layer
This keeps GPU memory usage extremely low.
𝗞𝗲𝘆 𝗱𝗲𝘁𝗮𝗶𝗹𝘀
• No quantization required by default
• Optional 4-bit or 8-bit weight compression
• Same API as Hugging Face Transformers
• Supports CPU and GPU inference
• Works on Linux and macOS Apple Silicon
𝗪𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗱𝗼
• Run Llama, Qwen, Mistral, Mixtral locally
• Test large models without cloud GPUs
• Prototype agents on cheap hardware
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Reminder that my book—Rust Atomics and Locks—is freely available online: https://t.co/EgEhl3pSLO 😊
(If you read it, please leave a review on https://t.co/qNXxui85Jj)
tracel-ai / burn: Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. ★8056 https://t.co/aIFMVKia3o