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Zhipu AI officially open-sources its latest general vision model, GLM-4.1V-Thinking, based on the GLM-4V architecture, which introduces a chain-of-thought reasoning mechanism, significantly enhancing its capabilities for complex cognitive tasks. The model supports multimodal inputs such as images, videos, and documents, and excels in diverse scenarios including long video understanding, image question answering, subject problem-solving, text recognition, document interpretation, grounding, GUI Agent, and code generation, covering a wide range of industry application needs. GLM-4.1V-9B-Thinking

On June 30th, the world's first trillion-parameter large model for the power generation industry, Qinyuan, developed independently by the State Energy Group, was officially released. This innovative large model, with its unique full-stack independent and controllable characteristics, marks an important step forward for the power generation industry into a new era of intelligent decision-making. The Qinyuan large model aims to integrate the diverse scenarios, high complexity, and strong professionalism of the power generation industry, fully utilizing the State Energy Group's globally largest installed capacity and massive data resources. The launch of this model not only creates a new engine for multi-energy coordination and dynamic optimization, but also establishes an electricity

Recently, OpenAI announced that it will refactor its Codex CLI tool, completely abandoning TypeScript in favor of the Rust language. This decision aims to provide developers with a more efficient and stable AI terminal interaction experience. Codex CLI was originally designed to simplify developers' interaction with AI in the terminal, using TypeScript and the React-based Ink framework. However, as Codex CLI continues to develop,

This morning, Microsoft officially announced its latest innovative small-parameter model, Mu. This model has only 330 million parameters, yet it can match the performance of Microsoft's previously released Phi-3.5-mini, while being just one-tenth the size of Phi-3.5-mini. More notably, Mu can achieve a response speed of over 100 tokens per second on offline NPU laptops, which is a rare breakthrough in the field of small-parameter models. A major highlight of the Mu model is its support for setting intelligent features in Windows.

A deep dive into the features and effects of Flux Context, an AI image enhancement tool, including core features like photo cartoonization, watermark removal, and old photo restoration, to analyze whether it can truly enhance the efficiency and quality of image processing.

Google's DeepMind announced a major breakthrough in hurricane forecasting on Thursday, launching an innovative artificial intelligence system capable of unprecedented precision in predicting the path and intensity of tropical cyclones. This achievement solves long-standing challenges faced by traditional meteorological models for decades. At the same time, DeepMind also launched "Weather Lab", an interactive platform to showcase its experimental cyclone prediction model. The model can generate up to 50 possible storm scenarios 15 days in advance. More notably, De

Apple has released the latest update to its artificial intelligence model, which primarily supports the Apple Intelligence feature for systems like iOS and macOS. According to Apple's official data, the newly launched model performs comparably with similar products from Google and Alibaba, but compared to OpenAI's GPT-4o released a year ago, Apple's server-side model performance is notably weaker. In the update, Apple emphasized the capabilities of its 'device-side model'.

In the rapidly developing field of artificial intelligence today, Alibaba officially open-sourced its new Qwen3 Embedding model series on June 6th. Based on the Qwen3 foundation model, this model is optimized for tasks such as text representation, retrieval, and ranking, marking another significant breakthrough for Alibaba in the AI field. Compared to the previous version, Qwen3 Embedding has achieved over a 40% performance improvement in core tasks such as text retrieval, clustering, and classification. This progress not only makes it more competitive