Announcing Olmo 3, a leading fully open LM suite built for reasoning, chat, & tool use, and an open model flow—not just the final weights, but the entire training journey. Best fully open 32B reasoning model & best 32B base model. 🧵
OPEN SOURCE
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Task Arena: Open Source AI Task Automation Framework
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Task Arena: https://
github.com/dimensionhq/ta
sk-arena
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Open Science: Foundation of Modern AI Research and Development
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Open science built modern AI: Open datasets like ImageNet, MNIST Open-source code/libraries like TensorFlow, PyTorch Shared benchmarks Read why universities must reclaim AI research for the public good: #TeamOpenScience
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Partnership with Roboflow for SAM 3 Data Annotation and Deployment
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We've partnered with @Roboflow to enable people to annotate data, fine-tune, and deploy SAM 3 for their particular needs. Try it here:
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Meta Releases SAM 3 Model with Evaluation Benchmark and Open Source Tools
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We’re sharing SAM 3 under the SAM License so others can use it to build their own experiences. Alongside the model, we’re releasing a new evaluation benchmark, model checkpoint, and open-source code for inference and fine-tuning. These resources are designed to support advanced
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Meta releases SAM 3D Body model and training data for community
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We’re sharing model checkpoints, an evaluation benchmark, human body training data, and inference code with the community to support creative applications in fields like robotics, interactive media, science, sports medicine, and beyond. SAM 3D Body:
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alphaXiv Bridges AI Research-to-Practice Divide with Integrated Platform
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alphaXiv is solving this by bridging the AI research-to-practice divide. We’re bringing together papers, benchmarks, and implementations into a single platform that makes it seamless for any AI practitioner to discover and build on top of the latest research.
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Siddharth’s Major Contributions to Flowise AI Open Source
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Thank you @aibysid for all these awesome PRs! Open source ftw 🙌 Siddharth Chauhan (@aibysid) 🚀 I’ve Been Hacking on @FlowiseAI Lately — Here’s What I’ve Built 👇 So over the last few weeks I’ve gone down a bit of a Flowise rabbit hole… in a good way 😄 I ended up opening a bunch of PRs to the project and thought I’d share what I actually did. If you haven’t used Flowise: it’s basically a super-nice visual builder for AI agents. Drag, drop, connect nodes, and boom — you’ve got a working LLM workflow. 🔧 What I’ve Been Fixing & Adding 🗑️ 1. AgentFlow list didn’t refresh after deleting Small bug, annoying experience. Fixed it so when you delete an AgentFlow, the UI instantly updates. No more manual refreshes. Tiny change, but feels way better. 🖼️ 2. Added image upload support to the ChatOpenRouter node Wanted multimodal flows inside Flowise — so now you can just drop images into the node. Opens up tons of cool use-cases. 🧾 3. Agent node can now output structured JSON Earlier, responses were mostly text. I added proper structured JSON output so people can build cleaner automations or connect flows to other tools without parsing headaches. 🚨 4. Fixed inconsistent status codes Some API calls returned weird/inconsistent errors for invalid chatflow IDs. Cleaned that up so failures are predictable and easier to handle. 🤖 5. Improved support for Hugging Face inference providers Made Flowise a bit more flexible by making model provider integrations work more smoothly with the HF inference API. 📝 6. Added image loader w/ OCR support (multiple providers!) One of my favourites — Flowise can now take in images and run OCR through different providers. Super useful for docs, receipts, screenshots, all that stuff. 🤔 Why I Did All This Honestly, I just started exploring the codebase and found small areas that could be improved. And once you make 1 PR, you kinda get hooked. Plus: Multi-modal workflows are the future JSON output makes everything easier A good user experience is basically 50% of why people love a tool Flowise is growing fast, so contributing early is fun 🎯 What I Learned Messing With Flowise OSS PRs teach you WAY more than tutorials ever will “Small things” like UI refresh bugs make a big difference Multi-modal + agent workflows get tricky behind the scenes Consistent API behavior is underrated Flowise’s architecture is actually pretty clean once you get the hang of it 🔮 What’s Next I’m planning to pick up stuff around permissions, workspaces, and maybe build some sample flows showing image-upload → OCR → agent reasoning → structured output. Also thinking of writing a guide for beginners who want to contribute. 🙌 If You’re Into AI Agents or Flowise Hit me up, or drop into the repo. There’s a lot of cool stuff happening and it’s a great project if you want to get into open-source around LLMs. Here is is list of my PRs: github.com/FlowiseAI/Flowise… — https://nitter.net/aibysid/status/1991120542594949189#m
→ View original post on X — @flowiseai, 2025-11-19 12:48 UTC
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Chinese LLMs Making GenAI Affordable and Accessible Globally
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Decent-quality LLMs from China are really helping make GenAI affordable and accessible to the world through open source. Pursuing AGI with close models might be a winner-take-all game for U.S. big techs, but making AI more open will benefit researchers, students, entrepreneurs, and hobbyists in building AI that works for them. More in this @BloombergAsia interview: bloomberg.com/news/videos/20…
