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OpenAI launches 'Stargate Norway', its first European AI data center in Narvik. Powered by renewables, it will deploy 100K NVIDIA GPUs by 2026, using liquid cooling and heat recycling. Prioritizing Norwegian startups, it supports Europe's AI innovation and Norway's sovereign AI strategy.....

The Qwen3-30B-A3B model has undergone a major update, launching the new version Qwen3-30B-A3B-Thinking-2507. This new version has achieved significant improvements in reasoning capabilities, general abilities, and context length, marking that the model is not only lighter but also has stronger thinking capabilities. Compared to the Qwen3-30-A3B model open-sourced on April 29, the new model has made progress in multiple key areas. In terms of mathematical abilities, Qwen3-30B-A3B-Thin

On July 29, a new version of the Qwen3-30B-A3B model, called Qwen3-30B-A3B-Instruct-2507, was released. This new version achieves significant improvements in multiple key areas, marking that the model can achieve performance comparable to top closed-source models such as Gemini2.5-Flash (non-thinking) and GPT-4o, by activating only 3B parameters in non-thinking mode.

Mistral AI released a large language model environmental assessment report, revealing challenges in the sustainable development of AI technology. The report shows that 85.5% of carbon emissions and 91% of water consumption are concentrated in the training and inference phases. 18 months of operation produced 20.4 tons of carbon dioxide and consumed 281,000 cubic meters of water. A single interaction of 400 tokens produces 1.14 grams of carbon emissions and 45 milliliters of water consumption. The company acknowledges the limitations of the study, such as hardware performance evaluation, but the data align with industry assessments. Mistral calls for increased industry transparency and commits to updates.

Step Star releases the next generation Step 3 large model, which will be open-sourced on July 31st. This 321B parameter multi-modal reasoning model performs outstandingly in intelligence and reasoning efficiency, supporting cross-domain knowledge understanding and visual analysis. The company has established the Model Chip Ecosystem Innovation Alliance in cooperation with chip manufacturers and reached a strategic cooperation with Shanghai State Capital, promoting the application of large models. Step 3 achieves 300% reasoning efficiency of competing products on domestic chips, with over 70% improvement in throughput, and has established a 1+N model matrix covering multiple fields. The model has achieved SOTA on multiple rankings.

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.

Hinton's first visit to China has sparked widespread discussion. At the 2025 World Artificial Intelligence Conference, this 77-year-old Turing Prize and Nobel laureate warned that AI may surpass human intelligence and called for caution against raising a tiger as a pet. He particularly emphasized that while pursuing AI technological advancement, it is essential to research how to keep AI benevolent. Although there is currently no relevant technology, this is a key area of research. Hinton's views have triggered extensive discussions in the industry.

Today, the 2025 World Artificial Intelligence Conference (WAIC) officially kicked off, and Alibaba announced the technical progress of its first self-developed AI glasses - 'Qwen AI Glasses' at this event, and showcased a real machine on site. From the current display, the Qwen AI Glasses do not have a screen, but instead use a combination of lenses and voice interaction, which is considered one of the more suitable forms of AI carriers at present.

Kuaishou opensources the KAT-V1 autonomous thinking large model, which includes two versions: 40B and 200B. The 40B version performance is close to DeepSeek-R1, and the 200B version outperforms several flagship models. The model innovatively adopts a mixed training paradigm of short and long-term thinking and the Step-SRPO reinforcement learning algorithm, which can automatically adjust the thinking mode based on the complexity of the question, solving the problem of overthinking. Based on Qwen2.5-32B, it achieves excellent performance in fields such as science and code through an heterogeneous distillation framework and pre-training with 10 million examples.

AI office company PixelBloom completes B3 funding round, led by Yizhuang Guotou, with participation from multiple renowned institutions. The funds will be used for two strategic initiatives: accelerating global expansion and consolidating the leading position of AiPPT.com in international markets; expanding the AI Venture Studio model to incubate innovative office products. This funding round reflects market recognition of its technological capabilities and development prospects. In the future, it will promote the construction of the AI office ecosystem and enhance the intelligent office experience for global users.

American tech billionaire Mark Cuban predicts that AI will become an essential skill in the workplace within five years, similar to email and Excel. He points out that using AI effectively will determine a company's competitiveness. In the future, individuals can complete team work with the help of AI, significantly lowering the barriers to entrepreneurship. Kuban suggests treating AI as a smart intern, requiring careful verification of its answers. He emphasizes that AI is a business multiplier, and entrepreneurs should use it wisely but not be controlled by it. Quick decision-making is necessary to maintain a competitive advantage. AI will break down the barriers of startup funding and change the way work is done over the next decade.

ChatGPT handles 2.5B daily queries, with 330M from the US. While smaller than Google's 14B searches, its rapid growth (doubling in 8 months) reflects surging demand for AI assistants in tasks like research and writing, signaling deeper AI integration into daily life.....

Lightricks releases open-source LTX-Video13B, a 13B-parameter video generation model with multi-scale rendering, achieving 30x faster speeds. It runs on consumer GPUs, supports 1216×704 real-time generation, and offers text/image/video-to-video modes. The model enhances coherence and detail, enabling keyframe control and style transfer. Free for SMEs, it includes training tools and optimized versions to democratize AI video creation.....

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.....

NVIDIA's Canary-Qwen-2.5B sets a 5.63% WER record on Hugging Face OpenASR. This CC-BY licensed model combines FastConformer encoder with Qwen3-1.7B LLM decoder for efficient speech-to-text and NLP. Supports multi-GPU deployment for cloud/edge applications.....

OpenAI advisory report advocates nonprofit AI governance for democratic participation, suggesting transition to a public benefit corporation to balance profit and social goals, with increased public interest funding.....

Recently, the ByteDance Seed team collaborated with the University of Hong Kong and Fudan University to introduce an innovative reinforcement learning training method called POLARIS. This method successfully enhances the mathematical reasoning capabilities of small models to levels comparable to those of large models through a carefully designed Scaling RL strategy, offering a new approach for optimizing small models in the field of artificial intelligence. Experimental results show that the 4 billion parameter open-source model Qwen3-4B trained using POLARIS achieved remarkable performance on AIME25 and AIME24 mathematical tests.