@seclink: This project is interesting. It open-sources some datasets that can be used for algorithm training and research.
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This project open-sources datasets that can be used for algorithm training and research.
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Cached at: 07/11/26, 03:26 PM
This project is quite interesting. It open-sources some datasets that can be used for algorithm training and research. https://t.co/QQgvIqjgBg
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@seclink: Share "Developer Ecosystem Information Gap Report (2026-06-05)", interested friends can read. - Now some people are beginning to migrate openclaw-type projects to AI glasses, AI rings, and other wearable devices ... - Robotics and embodied AI open source: many open source datasets and open source models ...
Shared an information gap report on the developer ecosystem, covering topics such as migrating openclaw-type projects to wearable devices like AI glasses and rings, open-source data and models for robotics and embodied AI, and niche open-source applications for AI API relay stations and routing.
@seclink: gstack is also quite powerful, with 121k stars, and the project creator is a major IP themselves, so the possibility of star-farming is low. It's definitely worth downloading to study. Another similar project is gbrain, which is essentially the toolbox needed for FDE positions.
gstack is an open-source project with 121k stars, created by a well-known figure, and worth studying; another similar project, gbrain, is a toolbox for FDE positions.
@yaojingang: With the consent of our friend Ba Dao Liu, we are open-sourcing the dataset recently collected from major domestic AI platforms. The cleaned dataset, preprint paper, and first analysis report have been pushed to the GitHub repository (see comments for the link). This should be the latest and most comprehensive public GEO raw dataset for major domestic AI platforms, including Doubao, Dee...
Friend Ba Dao Liu open-sourced search result datasets from 8 domestic AI platforms, containing 620 standard questions and 210,000 citation records, along with cleaned data, a preprint paper, and an analysis report.
@seclink: 有点意思 ....
TileRT is a tile-based runtime achieving ultra-low-latency LLM inference, with recent milestones including 1000+ tokens/s on a 1-trillion-parameter model. It supports models like DeepSeek-V3.2 and GLM-5, and is available as open-source on GitHub.
@seclink: https://x.com/seclink/status/2069238720155484221
This article reviews the latest world model algorithms in the field of embodied intelligence, including Fast-WAM and its low-latency decoupling mechanism, and introduces several open-source projects such as GeoSem-WAM, CLAW, WALL-X, etc., providing technical features and code links.