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Applied AI research • SWE • local AI • privacy • selfhosting

Israel
Joined February 2025
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#Fibo2 is out today. It’s the #1 open-weights image model on @ArtificialAnlys, and the weights are yours. A few things worth knowing 🧵1/7
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Vaxry gave a keynote talk about Hyprland at our Don't Be Evil Conference this year. If you missed the event, you can watch his talk here!
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FFmpeg is moving to Rust 🦀 Our use of C and Assembly in FFmpeg has been an unacceptable violation of safety. FFmpeg will be running 10x slower - but we're doing it for your safety. All your videos will appear green - safety first, working software later.
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Free Supercharging temporarily enabled Afula, Israel tesla.com/findus?bounds=33.2… Be'er Sheva, Israel tesla.com/findus?bounds=31.8… Eilat, Israel tesla.com/findus?bounds=30.1… Eilat, Israel - BIG tesla.com/findus?bounds=30.2… Ein Bokek, Israel tesla.com/findus?bounds=31.8… Givat Shmuel, Israel tesla.com/findus?bounds=32.6… Hadera, Israel tesla.com/findus?bounds=33.0… Haifa, Israel tesla.com/findus?bounds=33.4… Holon, Israel tesla.com/findus?bounds=32.6… Jerusalem, Israel tesla.com/findus?bounds=32.3… Karmiel, Israel tesla.com/findus?bounds=33.5… Kefar Sava, Israel tesla.com/findus?bounds=32.8… Kiryat Ata, Israel tesla.com/findus?bounds=33.4… Kiryat Gat, Israel tesla.com/findus?bounds=32.2… Kiryat Shmona, Israel tesla.com/findus?bounds=33.8… Mevaseret Zion, Israel tesla.com/findus?bounds=32.4… Mitzpe Ramon, Israel tesla.com/findus?bounds=31.2… Modi’in Azrieli, Israel tesla.com/findus?bounds=32.5… Modi'in, Israel - Ishpro Center tesla.com/findus?bounds=32.5… Netanya, Israel tesla.com/findus?bounds=32.9… Petah Tikva, Israel tesla.com/findus?bounds=32.7… Ramat Hasharon, Israel - Cinema City Glilot tesla.com/findus?bounds=32.7… Tel Aviv – Azrieli Town, Israel tesla.com/findus?bounds=32.6… Tel Aviv, Israel tesla.com/findus?bounds=32.6… Yavneh, Israel tesla.com/findus?bounds=32.4…
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Valve are professionals. Nobody name themselves ";quit".
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Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: github.com/unslothai/unsloth Blog and Guide: unsloth.ai/docs/new/studio Available now on Hugging Face, NVIDIA, Docker and Colab.
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Today we launch Fish Audio S2, a new generation of expressive TTS with absurdly controllable emotion. - open-source - sub 150ms latency - multi-speaker in one pass Real freedom of speech starts now 👇
Readers added context they thought people might want to know
The "open source" claim is false. Their custom license prohibits commercial use and limits some derivative uses. A more accurate description is "source-available", meaning the source code is publicly accessible but subject to use restrictions. opensource.org/osd github.com/fishaudio/fish… fossa.com/blog/comprehen…
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Start building with Gemini Embedding 2, our most capable and first fully multimodal embedding model built on the Gemini architecture. Now available in preview via the Gemini API and in Vertex AI.
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alpaim retweeted
What I discovered by letting my normie relatives use my laptop is that if you use Linux with i3 window manager you don't need a screen locker at all.
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Introducing: Zed for Students! 🎓 Enjoy Zed's Pro plan free, for a year, if you're a current university student (or teacher!) - Zed Pro features for 12 months - $10/month in token credits - Unlimited edit predictions Apply today: zed.dev/education
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We’re teaming up with @InSilicoMed to create lightweight scientific foundation models for pharmaceutical research. Together, we are building a series of liquid foundation models with state-of-the-art performance across multiple drug discovery subdomains. 💊 Our goal is to push the frontier of drug discovery beyond single-purpose, specialized models and towards foundational generalist models that are useful and capable of ingesting proprietary molecules, assays, and target data entirely within local private instances. The first model in line is LFM2-2.6B-MMAI, a small model that achieves cloud-scale performance while operating entirely on private infrastructure: > Molecular optimization: Up to 98.8% success on MuMO-Instruct multi-parameter optimization. > Affinity prediction: Outperformed GPT-5.1, Claude Opus 4.5, and Grok-4.1 on Insilico’s 2.5M / 689-target benchmark. > Chemical reasoning: Strong functional-group reasoning (FGBench) and solid 1-step retrosynthesis (ChemCensor). By combining Liquid AI’s efficient LFM technology with Insilico’s MMAI Gym, a comprehensive training platform w/over 1,000 pharmaceutical benchmarks, we observe that on-premise deployment can deliver competitive results across the full spectrum of drug discovery tasks, all in a single system. These capabilities unlock immediately useful applications for pharmaceutical companies, particularly in high-frequency ADMET screening, medicinal chemistry-facing lead optimization, and retrosynthesis feasibility assessment that prevents wasted experimental effort.
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TIL that Linux isn't free cause I had to buy the computer to run it 😭 This is the biggest load of cope I have ever heard. I hope Opus gets smoked by DeepSeek v4 and the only people who continue to use closed source models are Windows users.
Dario Amodei just dismantled the biggest myth in the AI industry. Open source AI isn’t free. It never was. Amodei: “It’s not free. You have to run it on inference and someone has to make it fast on inference.” For decades, open source meant something real. It meant a teenager in a basement could download the same tools as a Fortune 500 company. Could read the code. Could modify it. Could build something that competed with the giants. That was genuine democratization. That actually happened. AI is different. Fundamentally. Physically. In ways the ideology hasn’t caught up to yet. Downloading the weights is the easy part. The part that actually costs something is turning the weights into a running system. Into responses. Into intelligence operating in real time at scale. That requires compute. Power. Infrastructure. The kind measured in billions of dollars and years of construction. Amodei: “These are big models. They’re hard to do inference on. Ultimately you have to host it on the cloud. The people who host it on the cloud do inference.” The open source debate was never about who owns the model. It was always about who owns the cloud. And Amodei goes further. When a competitor drops a new open model, he doesn’t ask whether it’s open or closed. He doesn’t care about the licensing. He doesn’t engage the ideology. Amodei: “I don’t think it mattered that DeepSeek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That’s the only thing that I care about.” That’s the ruthless clarity of someone actually trying to win. While the media debates licensing frameworks, Amodei is asking one question. Is it better. Everything else is a distraction. Amodei: “I don’t think open source works the same way in AI that it has worked in other areas. Here we can’t see inside the model.” This isn’t Linux. You can’t read it. You can’t fork it. You can’t understand it the way generations of developers understood the tools they inherited. You can download it. And then you need a data center to run it. The teenager in the basement who was supposed to be empowered by this revolution needs a billion dollars of infrastructure before the empowerment starts. The era of the basement coder rewriting civilization on a laptop is over. The future belongs to whoever commands the compute, owns the power grid, and can actually turn the intelligence on. Open weights without infrastructure isn’t democratization. It’s a promise the physics of the universe won’t let us keep.
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🎉 vLLM-Omni v0.14.0 is officially released — our first stable release! 180 commits from 70+ contributors (23 new!) ship the multimodal stack for production. Highlights: ⚡ Async chunk pipeline overlap 🗣️ Qwen3-TTS with online serving 🎨 Diffusion LoRA (PEFT-compatible) 🧠 DiT layerwise CPU offloading 🔌 XPU / ROCm / NPU backends New models: 🥯 Bagel (multi-stage pipeline) 🎵 Stable Audio Open 🖼️ GLM-Image, FLUX.1-dev, FLUX.2-klein APIs: 📸 /v1/images/edit endpoint 🩺 /health & /v1/models for diffusion mode Performance: ⚡ Torch compile for diffusion 🔥 SharedFusedMoE for Qwen3-Omni 🧊 TeaCache for Z-Image & Bagel 🌊 Sequence Parallelism (SP) for diffusion 🔗 github.com/vllm-project/vllm…
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Qwen3-ASR and Qwen3-ForcedAligner are now open source — production-ready speech models designed for messy, real-world audio, with competitive performance and strong robustness. ● 52 languages & dialects with auto language ID (30 languages + 22 dialects/accents) ● Robust in noisy and complex settings (yes, singing and songs too) ● Long audio support: up to 20 minutes per pass ● Word/phrase-level timestamps:  high-precision alignment for 11 languages via Qwen3-ForcedAligner, stronger than MFA/CTC/CIF-style aligners Also included: a full open-source inference & finetuning stack with vLLM batch, streaming, and async serving. GitHub:  github.com/QwenLM/Qwen3-ASR Hugging Face: huggingface.co/collections/Q… ModelScope: modelscope.cn/collections/Qw… Hugging Face Demo:  huggingface.co/spaces/Qwen/Q… ModelScope Demo: modelscope.cn/studios/Qwen/Q… Blog:  qwen.ai/blog?id=qwen3asr Paper:  github.com/QwenLM/Qwen3-ASR/…
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Introducing LM Studio 0.4.0 🎉✨ It's the next generation of LM Studio. 🪄 Deploy on servers, in CI, or anywhere 🚄 Parallel requests for high throughput use cases 🔨 New stateful REST API: use local MCPs 🎨 Complete UI revamp See what's new in this release👇🧵
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Introducing Sweep Next-Edit, an open-weights 1.5B model trained to predict your next edit. Sweep Next-Edit outperforms models 4x its size while being small enough to run locally. We're open-sourcing the weights so the community can build fast, privacy-preserving autocomplete for every IDE.
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You can now fine-tune embedding models in our free notebook! Improve retrieval and RAG with better semantic search & similarity. Unsloth trains 2x faster, 20% less VRAM, >2x context & no accuracy loss Blog: unsloth.ai/docs/new/embeddin… EmbeddingGemma (300M): colab.research.google.com/gi…
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Qwen3-TTS is officially live. We’ve open-sourced the full family—VoiceDesign, CustomVoice, and Base—bringing high quality to the open community. - 5 models (0.6B & 1.8B) - Free-form voice design & cloning - Support for 10 languages - SOTA 12Hz tokenizer for high compression - Full fine-tuning support - SOTA performance We believe this is arguably the most disruptive release in open-source TTS yet. Go ahead, break it and build something cool. 🚀 Everything is out now—weights, code, and paper. Enjoy. 🧵 Github: github.com/QwenLM/Qwen3-TTS Hugging Face: huggingface.co/collections/Q… ModelScope: modelscope.cn/collections/Qw… Blog: qwen.ai/blog?id=qwen3tts-011… Paper: github.com/QwenLM/Qwen3-TTS/… Hugging Face Demo: huggingface.co/spaces/Qwen/Q… ModelScope Demo: modelscope.cn/studios/Qwen/Q… API: alibabacloud.com/help/en/mod…
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