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During the 618 promotion in June 2025, the smart speaker market in China experienced a strong recovery. According to the latest data, online sales reached 802,000 units, an increase of 7.5% compared to last year, while sales revenue grew by 15.2% year-over-year. This significant growth was driven by the widespread application of AI large model technology, making smart speakers more powerful and offering a better user experience. Data shows that smart speakers equipped with AI large models accounted for nearly 40% of the market. Specifically, in the second quarter of 2025, the market...

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...".

Recently, the French AI laboratory Kyutai announced the official open source of its new text-to-speech model, Kyutai TTS, providing global developers and researchers with a high-performance, low-latency speech synthesis solution. This breakthrough release not only promotes the development of open-source AI technology but also opens up new possibilities for multilingual voice interaction applications. AIbase provides an exclusive analysis of this technological highlight and its potential impact. Ultra-low latency, a new experience in real-time interaction. Kyutai TTS has become an industry standout with its exceptional performance.

In the field of artificial intelligence, reward models are a critical component for aligning large language models (LLMs) with human feedback, but existing models face the issue of "reward hacking." These models often focus on superficial features, such as the length or format of responses, rather than identifying genuine quality metrics, such as factual accuracy and relevance. The root cause lies in standard training objectives failing to distinguish between spurious associations and true causal drivers present in the training data. This failure leads to fragile reward models (RMs), which generate misaligned policies.

Recently, NVIDIA and CoreWeave announced that NVIDIA's latest artificial intelligence graphics processor, Blackwell Ultra, has been commercially deployed on CoreWeave. This news undoubtedly injects new vitality into AI cloud computing services. Dell also stated that CoreWeave has received customized devices based on the NVIDIA GB300NVL72AI system, marking CoreWeave as the first to install a Blackwe

According to KPMG China's recent report, "The First 50 Health Tech Companies," China accounts for more than 70% of the global release volume of medical large models. This data not only demonstrates China's rapid development in the field of intelligent healthcare, but also reflects the wide application of large language models in the healthcare industry. The report points out that about 65% of the currently released medical large models are large language models. These models can process and generate natural language, playing a significant supporting role in the analysis of medical data, patient communication, and scientific research.

In the long-standing copyright infringement lawsuit filed by The New York Times against OpenAI, the case has made significant progress. According to Ars Technica, the federal judge presiding over the case has authorized The New York Times and its co-plaintiffs, The New York Daily News and the Investigative Reporting Center, to access OpenAI's user logs, including deleted content, to accurately determine the scope of the infringement. The New York Times believes that ChatGPT users may delete their history after bypassing the paywall, and therefore it is necessary to conduct large-scale data collection.

In the new energy vehicle market, Xiaopeng Automotive has once again drawn attention. On July 3rd, the Xiaopeng G7 Ultra was officially launched, becoming the first intelligent vehicle equipped with the local-end "VLA+VLM" large model. This innovative technology marks an important step forward for Xiaopeng in the field of intelligent driving. The Xiaopeng G7 Ultra is equipped with the VLA (active thinking and rapid decision-making capability) large model, making the driving experience more intelligent. In daily driving, the G7 Ultra can flexibly handle various complex driving scenarios, such as in traffic.

A recent report titled "Health Tech 50 - The First Edition" released by KPMG China reveals that China has taken a leading position in the field of medical large models globally. The report indicates that the number of medical large models launched in China accounts for more than 70% of the global total, far surpassing other countries and regions. In terms of model categories, large language models (LLMs) are the most numerous, accounting for nearly 65%. Moreover, the report also highlights the strong growth momentum of the intelligent medical devices market in China. It is expected that by 2025, the scale of the intelligent medical devices market in China will reach 24.23 billion yuan, and it will continue to grow.

Since July, Xiaomi App Store will gradually open AI intelligent agent distribution services to users. After opening the Xiaomi App Store APP, users can click on the newly added 【Intelligent Agent】 entry at the bottom to directly access the special zone and browse and experience various practical and interesting AI intelligent agent products. At the same time, users can also quickly locate the desired service through the search function. The entire process does not require downloading or installing, truly achieving the convenient experience of "instant use." This innovative model not only lowers the threshold for users to access AI services, but also enhances the efficiency of service delivery through scenario-based recommendations. It is worth noting that

Large Language Models (LLMs) have achieved significant progress in complex reasoning tasks by combining task prompts with large-scale reinforcement learning (RL), as demonstrated by models like Deepseek-R1-Zero, which directly apply reinforcement learning to base models, showcasing strong reasoning capabilities. However, this success is difficult to replicate across different base model families, especially within the Llama series. This raises a core question: what factors lead to inconsistent performance of different base models during reinforcement learning? How does reinforcement learning perform in

OpenAI recently announced that, despite initial testing, it will not adopt Google's TPU chips on a large scale. TPU (Tensor Processing Unit) is a custom ASIC chip developed by Google for machine learning tasks, designed to accelerate the training and inference of neural networks. TPU uses a dataflow-driven architecture, enabling efficient matrix multiplication pipeline computing and reducing memory access latency. Image source note: The image is AI-generated, provided by the licensing service Midjourney. OpenAI stated that it will continue