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The Kimi Open Platform launched the Kimi K2 High-Speed Version (kimi-k2-turbo-preview), increasing the output speed from 10 Tokens per second to 40 Tokens per second while maintaining the original parameter scale, significantly improving response efficiency. This upgrade is mainly targeted at applications requiring higher real-time performance, aiming to optimize user experience.

kimi-k2-turbo-preview, the high-speed version of Kimi K2, is officially released. According to the information, this high-speed version model maintains the same parameter settings as the original kimi-k2, but achieves significant performance improvements. The output speed has jumped from 10 Tokens per second to 40 Tokens per second, providing users with a smoother and more efficient experience.

San Francisco AI startup Deep Cogito launches the Cogito v2 series of open-source large models, focusing on machine intuition and self-improvement capabilities. The series includes four dense and mixture-of-experts models with 70B to 671B parameters. The flagship 671B MoE model has a reasoning efficiency that is 60% higher than DeepSeek R1, and its performance is close to Claude4Opus. Its core technology involves internalizing reasoning paths into model weights through introspective reasoning, enabling continuous evolution while in use. Tests show that the model can

Singapore's SixSense raised $8.5M led by Peak XV, totaling $12M. Founded by female engineers, its no-code AI platform for semiconductor manufacturing improves efficiency by 30%, yield by 1-2%, and reduces manual checks by 90%. Expanding to US amid global chip investment boom.....

Arm considers launching self-designed chips, potentially affecting partnerships with Nvidia. Dominant in smartphones and AI data centers, Arm faces market competition, expanding upstream. Q3 revenue missed forecasts, causing an 8% stock drop. Quarterly revenue rose 12% to $1.05B, with licensing up 25%. SoftBank positions Arm at the core of AI strategy.....

Pudong New Area launched a seed fund with a total scale of 2 billion yuan for artificial intelligence. The first phase is 500 million yuan, making it the first state-owned capital venture capital fund in China focusing on the pre-seed stage. It has signed 18 projects. The AI industry scale in Pudong exceeds 160 billion yuan, accounting for 40% of the city, and has gathered more than 200 specialized model enterprises. In the future, five major measures will be implemented: releasing over 30 application scenarios, building a heterogeneous robot training field, establishing a full-cycle fund matrix, optimizing industrial policies, and providing talent services. The goal is to add 1,000 AI companies within three years, and the core output value will exceed 200 billion yuan, aiming to build a comprehensive AI ecosystem.

VLM2Vec-V2, a multimodal embedding framework developed by Salesforce Research and other institutions, breaks through the limitations of traditional models. Based on the Qwen2-VL architecture, this framework innovatively unifies image, video, and visual document retrieval tasks. It adds five new evaluation tasks to expand the MMEB dataset. With key technologies such as dynamic resolution and M-RoPE, it achieved an average score of 58.0 across 78 datasets, leading in performance, especially in video tasks. Although its document retrieval is slightly behind ColPali, it

Zhiyuan Robotics announced the open-source plan for the Zhiyuan Lingqu OS, an embodied intelligence operating system, at the 2025 World Artificial Intelligence Conference. The humanoid robot Lingxi X2 demonstrated intelligent interaction capabilities through natural dialogue. The system adopts a layered open-source model, including underlying middleware, agent framework, and toolchain, with plans to launch in the fourth quarter. Zhiyuan Robotics has already achieved application in fields such as industrial logistics, and its Qiyuan general embodied large model won the SAIL Star Award. The company will continue to improve the operating system and promote the development of embodied intelligence industry.

The Kimi team released the Kimi K2 technical report. This trillion-parameter large model, with 32 billion activated parameters, won the global open-source model competition, with performance comparable to top closed-source models such as GPT4.5. Its innovations include: using the MuonClip optimizer to process 15.5 trillion token data without loss; developing a multi-domain tool data synthesis pipeline; pioneering the restatement method to improve training efficiency, achieving the effect of ten rounds of original data in one round of rewritten data; optimizing model performance through supervised fine-tuning and reinforcement learning. The model is based on N

In 2025, open-source large models will show three major trends: 1) MoE architecture becomes mainstream, with DeepSeek-V3 (67.1 billion parameters) and Qwen3-235B (235 billion parameters) each having unique designs in their expert systems; 2) small models break through performance bottlenecks, with SmolLM3-3B adopting position-encoding-free technology, and Qwen3-4B achieving lightweight efficiency; 3) models show significant differentiation, with Llama3.2 focusing on general tasks, while Kimi-K2 (1 trillion parameters) excels in complex reasoning.

Tesla has released its new Dojo 2 chip, with performance 10 times that of the first generation, and computing power close to NVIDIA B200. The chip is manufactured by TSMC and uses advanced packaging technology, solving power consumption issues. Dojo 2 will assist Tesla's FSD autonomous driving system training, processing 16 billion video frames per day, achieving technological self-sufficiency. Musk revealed that next year a more powerful Dojo 3 will be launched, and he joked that Dojo 2 can run 'Crysis' at one billion frames per second. This breakthrough will reduce Tesla's reliance on NVIDIA and may be offered externally.

Moonshot AI's open-source model Kimi K2 excels in programming, matching Qwen3-235B-A22B and nearing o3-mini-high & Claude-3.7-Sonnet. With 1T MoE, 128k context, 65.8% accuracy on SWE-bench, and $0.14/M tokens, it's ideal for coding. Supports web generation, workflows, vLLM/Hugging Face deployment, MIT-licensed.....

Cursor's regional restrictions drive developers to adopt Chinese AI Kimi K2, hitting 10B daily tokens. Its API is 5-25x cheaper than Claude, gaining global traction in coding and content creation.....

Kimi-2, an open-source 32B MoE AI model, excels in code generation and outperforms Claude Opus4/GPT-4.1. Priced at $0.15/million tokens, it ranks 3rd globally and is now available via API and Kimi app.....

OpenAI ex-CTO's AI firm Thinking Machines Lab raises $2B seed at $12B valuation, focusing on multimodal AI for public benefit, with plans for open-source components and human-aligned AGI.....

Moon's Dark Side addresses Kimi K2API slowdowns, citing high traffic and large model size. Optimization and hardware upgrades underway, with improvements expected soon. Kimi K2 is fully open-source, allowing alternative deployments. The company, founded in 2023, focuses on AI tools like Kimi Assistant for translation and legal analysis, aiming to enhance user experience.....

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...

Kimi K2 excels in creative writing, outperforming o3-Pro in short story creation. This open-source model by Moonshot (Ali-backed) shows strengths in literary compression and metaphor innovation, with some works near publishable quality. Its low cost ($0.15/M tokens) and precise instruction-following attract developers, though emotional depth and multilingual performance need improvement. This breakthrough sets new AI writing standards.....