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AI startup Thinking Machines Lab has completed a $2 billion seed round funding, valuing the company at $12 billion, setting a new record for seed funding in Silicon Valley. Founded by Miral Kotb, former CTO of OpenAI, the company has attracted well-known investors such as NVIDIA within less than a year. The company is about to launch its first product, which includes important open-source projects aimed at supporting AI researchers and startups. Despite Meta's failed attempt to acquire the company, it is still seen as a potential challenger to industry giants. This funding reflects...

Tencent open-sourced 'Hunyuan-A13B', an 80B-parameter MoE model with dynamic inference (130B active params). Supports 256K context, trained on 20T tokens. Achieves 87.3% on AIME2024 math, but comparisons show version disparities.....

Recently, a research team from Renmin University, Shanghai Artificial Intelligence Laboratory, University College London, and Dalian University of Technology revealed an important finding in the reasoning process of large models: when the model is thinking, the 'thinking words' it uses actually reflect a significant increase in its internal information. This research result provides a new perspective for better understanding the reasoning mechanisms of artificial intelligence through methods of information theory. You may have seen large models output some language that seems human-like when answering questions, such as "Hmm..." or "Let me think...".

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

At the theme speech of Huawei Developer Conference HDC2025 held this afternoon, Zhang Ping'an, Executive Director of Huawei and CEO of Huawei Cloud Computing, officially announced the release of PanGu 5.5, marking the comprehensive upgrade of five basic models in natural language processing (NLP), computer vision (CV), multimodal, prediction, and scientific computing.

Recently, a new general intelligent agent called MiniMax Agent has been officially launched, aiming to provide efficient solutions for complex long-term tasks and has attracted widespread attention in the industry. MiniMax Agent: A breakthrough work of general intelligent agents - MiniMax Agent is an intelligent agent designed specifically to solve long-term complex tasks, featuring expert-level multi-step planning capabilities, flexible task decomposition mechanisms, and end-to-end execution efficiency. Its design concept is to make AI a reliable teammate.

A new study led by Apple researchers has poured cold water on the current large reasoning models (LRMs) that are highly anticipated. The research found that when solving complex tasks, reasoning models designed to simulate thinking processes, such as Claude3.7Thinking and Deepseek-R1, not only failed to show advantages but also exhibited serious problems like insufficient reasoning and performance collapse. This study tested four classic logical puzzles: the Tower of Hanoi, Checkers, River Crossing, and Block World. These puzzles allow precise control over the tasks.

In the recent Fiction.Live benchmark test, Gemini2.5Pro performed excellently in understanding and reproducing complex stories and backgrounds, leading ahead of OpenAI's o3 model. This test goes far beyond traditional "needle-in-a-haystack" tasks, focusing on a model's ability to handle deep semantics and context-dependent information within large contexts. According to the test data, when the context window length reaches 192,000 tokens (approximately 144,000 words), the performance of the o3 model drops sharply, while

Recently, the Beijing Academy of Artificial Intelligence (BAEI), in collaboration with Shanghai Jiao Tong University and other institutions, officially released a new generation of ultra-long video understanding model - Video-XL-2. The introduction of this model represents a significant breakthrough in the field of open-source ultra-long video understanding technology, injecting new vitality into the development of multimodal large models for understanding long video content. In terms of technical architecture, Video-XL-2 mainly consists of three core components: a visual encoder, the Dynamic Token Synthesis (DTS) module, and a large language model (LLM). The model adopts

Recently, the Windows version of Sogou Input Method has undergone a major upgrade with the launch of the new AI Wanzai Quick Search function, providing users with a more efficient and convenient office and study experience. The AI Wanzai Quick Search function is characterized by its one-click trigger and fast response. Users no longer need to follow the traditional three-step search process of opening a browser👉🏻search engine👉🏻input content. They can directly type on any spot on the desktop or use the shortcut key Ctrl+Shift+Space”, which can summon the All-Purpose Quick Search” function within 0.5 seconds, allowing for faster information retrieval.

Alibaba officially released QwenLong-L1-32B today, a large language model specially designed for long context reasoning, marking a significant breakthrough in AI's ability to handle long text processing. The model outperforms o3-mini and Qwen3-235B-A22B, performing at a level comparable to Claude-3.7-Sonnet-Thinking. The biggest technical breakthrough of QwenLong-L1-32B is that it is the first in the world to be trained via reinforcement learning.