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The TEN Agent team recently announced that its core models **TEN Voice Activity Detection (VAD)** and **TEN Turn Detection** are now open source, providing powerful technical support for building real-time, multimodal speech AI agents. This move marks a significant advancement in the TEN framework's efforts to promote the democratization and open-source collaboration of speech interaction technology. The following is the latest information compiled by AIbase, offering an in-depth analysis of these two core models.

A comprehensive analysis of the features of Humanify AI, testing its accuracy in detecting AI-generated content and the effectiveness of text rewriting for humanization. Evaluates the practical value this tool brings to students, writers, and content creators, offering professional purchasing advice.

A comprehensive review of the free AI photo editing tool, MagicEraser, revealing the true effectiveness of its one-click object removal feature. Uncover how this login-free, completely free AI tool addresses pain points such as people in the background and watermarks, along with its core differences from similar products.

Microsoft announced the release of 700 real AI agents and Copilot cases. These cases come from different fields, showcasing how artificial intelligence is deeply transforming work models. As a global leader in the AI field, Microsoft is committed to helping businesses and individuals better understand and apply AI technology. The released cases cover multiple industries such as finance, healthcare, technology, education, and automobile manufacturing, reflecting the extensive application of AI across various fields. In these cases, the intelligent agents built by Accenture for clients successfully achieved

According to the latest prediction from Gartner, by 2028, 80% of generative AI business applications will be developed on existing data management platforms. This shift is expected to reduce development complexity and cut delivery time in half. Currently, the development of generative AI business applications mainly relies on combining large language models (LLMs) with corporate internal data, as well as evolving technologies such as vector search, metadata management, prompt design, and embedding techniques. However, without a unified management approach, companies may...