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Google Research Unveils TimesFM: A Pre-trained Foundation Model for Advanced Time Series Forecasting

Google Research has introduced TimesFM (Time Series Foundation Model), a new pre-trained foundation model specifically designed for time series forecasting. Developed by Google's research division, TimesFM aims to enhance the accuracy and efficiency of predictions across various time-dependent data sets.

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TimesFM (Time Series Foundation Model) is a pre-trained foundation model developed by Google's research division. This model is specifically designed for the task of time series forecasting. The development by Google Research indicates a focus on advancing capabilities in predicting future values based on historical time-ordered data.

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FreeMoCap: Democratizing Motion Capture for Everyone – A New Open-Source Project Trending on GitHub

FreeMoCap, an innovative project, is making waves on GitHub Trending, aiming to democratize motion capture technology. The project's core mission is to enable "everyone to freely motion capture," suggesting an accessible and user-friendly approach to a technology traditionally requiring specialized equipment and expertise. Launched by 'freemocap' and published on February 22, 2026, this initiative promises to open up new possibilities for creators, developers, and enthusiasts by making motion capture widely available.

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Trivy: Comprehensive Vulnerability, Misconfiguration, Secret, and SBOM Scanner for Containers, Kubernetes, Code Repositories, and Cloud Environments

Trivy, developed by aquasecurity, is a powerful and versatile security scanner designed to identify vulnerabilities, misconfigurations, secrets, and Software Bill of Materials (SBOMs) across various components of the modern software development lifecycle. It supports scanning containers, Kubernetes clusters, code repositories, and cloud environments, providing a unified solution for enhancing security posture. The tool aims to help developers and security teams proactively detect and address potential security risks.

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Hugging Face Introduces 'Skills' for AI/ML Task Definition and Interoperability with Major Coding Agents

Hugging Face has unveiled 'Skills,' a new framework designed to define tasks within the AI/ML domain, encompassing activities like dataset creation, model training, and evaluation. These skills are built for seamless interoperability with leading coding agent tools, including OpenAI Codex, Anthropic's Claude Code, and Google De, aiming to streamline AI/ML workflows.