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The fast-growing startup Cluely in Silicon Valley recently announced that its annual recurring revenue (ARR) has rapidly surged to about $7 million after launching a new enterprise product. This growth rate has excited the founder Roy Lee, who told TechCrunch: "Everyone who has a meeting or interview is testing this product." Cluely is dedicated to using artificial intelligence to analyze online conversations, providing real-time meeting notes, background information, and question suggestions, all seamlessly displayed on the user's screen.

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 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.

The TEN Agent team recently announced that its core models **TEN Voice Activity Detection (VAD)** and **TEN Turn Detection** are now open source, providing powerful technical support for building real-time, multimodal speech AI agents. This move marks a significant advancement in the TEN framework's efforts to promote the democratization and open-source collaboration of speech interaction technology. The following is the latest information compiled by AIbase, offering an in-depth analysis of these two core models.

On June 30, Huawei officially announced the open sourcing of the Pangu dense model with 7 billion parameters, the PanguPro MoE model with 72 billion parameters, and the model inference technology based on Ascend. This open-source initiative is a key step in Huawei's strategy to build an Ascend ecosystem, aiming to promote research and innovation in large model technology, accelerate the application of artificial intelligence across industries, and create value.

A professional review that thoroughly analyzes how the AI call assistant from ChurchCalls.ai helps churches solve management challenges such as answering calls around the clock, collecting information, and intelligently transferring calls, thereby enhancing the communication efficiency of modern religious institutions.

On the evening of June 11, XPeng Motor officially released its latest model - XPeng G7. This car is known as the world's first AI car with L3-level computing power. Its biggest highlight lies in the installation of XPeng’s self-developed Turing AI chip, which has a computational capability equivalent to three Orin-X chips, showcasing XPeng's technical advantages in the intelligent vehicle field. The XPeng G7 is equipped with a powerful 40-core processor that can run up to 30B simulation parameters and features two self-developed neural network processors.

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 MiMo-VL multi-modal model developed by Xiaomi Company has taken over the baton from MiMo-7B, showcasing powerful capabilities in multiple fields. The model significantly outperforms the same-size benchmark multi-modal model Qwen2.5-VL-7B in tasks such as general question answering and understanding inference for images, videos, and language, and its performance in GUI Grounding tasks is comparable to that of specialized models, preparing for the arrival of the Agent era.

MegaT AI Search has launched a brand new Ultra-fast model, marking a significant breakthrough in its artificial intelligence search technology. Through innovative technical means, the response speed of MegaT AI Search has reached an amazing 400 tokens/second, ensuring that most questions can be answered within 2 seconds. This advancement not only enhances user experience but also significantly improves information retrieval efficiency. The realization of the Ultra-fast model is thanks to the application of multiple advanced technologies. The MegaT AI team has optimized on GPUs using ker

Recently, MiTA AI Search officially launched the new ultra-fast model, bringing users a more efficient and accurate search experience. The MiTA AI Search team successfully achieved a maximum response speed of 400 tokens/second on a single H800 GPU through kernel fusion technology on GPUs and dynamic compilation optimization strategies on CPUs, with most responses provided within 2 seconds.