Interesting HuggingFace post. What if the easiest way to make long-context Local AI faster is to simply STOP feeding it everything? A new HF forum experiment tested 600 distractor-heavy long-context prompts with Qwen2.5-7B 4-bit. Instead of sending the entire ~14K-token context, a MiniLM semantic selector kept only the most relevant ~60%. The result ... 📚 Input tokens 13,124 → 7,702 ➡️ -41% ⚡ Prefill 871 ms → 463 ms ➡️ -47% 🚀 End-to-end latency 944 ms → 519 ms ➡️ -45% 💾 Peak VRAM 11.71 GiB → 9.16 GiB And here's the weird part... 🎯 Token F1 actually IMPROVED: 0.534 → 0.581 So the model got: ✅ less context ✅ lower VRAM use ✅ almost 2× faster prefill ✅ lower total latency ✅ BETTER answers Why? Because more context isn't always better context. Coding agents and RAG systems often drag around enormous histories filled with irrelevant junk. ⚠️ This was a controlled distractor-heavy HotpotQA stress test, not proof that deleting 40% of every real-world context will improve accuracy. 🔗 Link in ALT.

Ever since NVIDIA acquired @HuggingFace, we have been looking into migrating some of our work off of HuggingFace and to alternative solutions like ModelScope. Even though NVIDIA's announcement claims they will continue allowing HuggingFace to be accelerator-agnostic, NVIDIA does not have a good track record of developing hardware-agnostic software. We love HuggingFace and hope we are wrong, but at the same time, we are also finding the UX of ModelScope to be great!

Great to welcome the @huggingface team to our Shanghai office! 🤗 We had inspiring conversations about LongCat’s future model development and open-source plans, as well as some of the latest features and technical details of Hugging Face Transformers. Hope you enjoy the LongCat keychains! Looking forward to exploring more ways to collaborate across the open-source ecosystem 🐱🚀

Chip giant @nvidia buys @huggingface for $12.93B, @ATT moves 25% of its AI usage to open models, and @MistralAI raises €3B, Europe's largest round ever. The money is moving to open-source AI ↓

is the HuggingFace attack something that should be taken seriously? yes. is it the first warning shot of a machine takeover? no. will issues of this type look like a tractable / mostly solved problem with proper precautions in 6 months? yes. will that happen automatically? no. as always, will require work from smart people and their agents.

Can you teach the @HuggingFace Amazing Hand to mimic human movements — in real-time and entirely on-device? @knaveen put it to the test using an NPU-accelerated MediaPipe Gesture Recognizer model running on the @Qualcomm Dragonwing IQ-9075.