The Dark Side of the Moon Company proudly launches its brand new SOTA (state-of-the-art) model—k1.5 Multimodal Thinking Model, marking a significant breakthrough in multimodal reasoning and general reasoning fields. This model not only possesses outstanding multimodal processing capabilities but also demonstrates exceptional general reasoning abilities, effectively addressing various complex tasks. The standout feature of the k1.5 model is its multimodal reasoning capability. It can process information from different modalities including text, images, and sounds simultaneously, providing more comprehensive and accurate results.

Recently, Beijing Dark Side of the Moon Technology Co., Ltd. announced a significant technological upgrade for its intelligent assistant Kimi, introducing the brand new k1.5 Multimodal Thinking Model. This model has reached industry-leading levels in multimodal reasoning and general reasoning capabilities, marking another breakthrough for Kimi in the field of artificial intelligence.

Recently, Zhejiang University and Alibaba DAMO Academy jointly released a remarkable study aimed at creating high-quality multimodal textbooks from educational videos. This innovative research not only provides new ideas for training large-scale language models (VLMs) but may also change the way educational resources are utilized. With the rapid development of artificial intelligence technology, the pre-training corpus of VLMs mainly relies on visual-text pairs and visually intertwined data. However, much of this current data comes from the web, where the correlation between text and images is weak, and the knowledge density is relatively low.

On January 15, 2025, Beijing Dark Side of the Moon Technology Co., Ltd. announced the official release of the new multimodal image understanding model moonshot-v1-vision-preview. This model enhances the multimodal capabilities of the moonshot-v1 model series, helping Kimi better understand the world. The Vision model boasts powerful image recognition capabilities, accurately identifying complex details and subtle differences in images, distinguishing similar yet different objects, whether they are food or animals.

On January 14, 2025, Shanghai Step-Star Intelligent Technology Co., Ltd. announced an in-depth cooperation with the well-known domestic tea brand Cha Bai Dao. This collaboration aims to leverage Step-Star's large model technology to jointly explore new models for intelligent inspection and AIGC marketing, with the goal of creating a new digital store production and operation model that provides consumers with a safer, smarter, and more enjoyable milk tea consumption experience.

Driven by multimodal large language models (MLLMs), significant advancements have been made in tasks related to images and videos, including visual question answering, narrative generation, and interactive editing. However, achieving fine-grained understanding of video content still poses major challenges. These challenges involve tasks such as pixel-level segmentation, tracking with language descriptions, and visual question answering based on specific video prompts. Although current state-of-the-art video perception models excel in segmentation and tracking tasks, they still fall short in open language understanding and conversational capabilities.

Recently, Hu Han, former chief researcher of the visual computing group at Microsoft Research Asia, officially joined Tencent, where he will be responsible for the development of the Hunyuan multimodal large model. This news has attracted widespread attention in the industry, and Hu Han's addition is believed to inject new vitality into Tencent's artificial intelligence initiatives. Hu Han obtained his bachelor's degree from Tsinghua University in 2008 and his Ph.D. in 2014, studying under the renowned professor Zhou Jie. His doctoral thesis was awarded the Excellent Doctoral Dissertation Award by the Chinese Association for Artificial Intelligence in 2016, showcasing his academic achievements.

Recently, the VITA-MLLM team announced the launch of VITA-1.5, an upgraded version based on VITA-1.0, aimed at enhancing the real-time and accuracy of multimodal interaction. VITA-1.5 not only supports English and Chinese but also achieves significant improvements in multiple performance metrics, providing users with a smoother interaction experience. In VITA-1.5, the interaction delay has been greatly reduced from 4 seconds to just 1.5 seconds, making it almost imperceptible for users during voice interactions.

On December 30th, Alipay launched its next-generation AI visual search product 'Explore', based on self-developed multimodal large model technology, enabling users to 'explore everything with the eye of AI' and providing faster, more useful, and fun generative search services. Users can let AI recognize plants, pets, and trendy products through the camera when encountering interesting items, get on-the-go travel explanations, check product and medication details, and even enjoy fun interpretations of pet and baby photos, eliminating worries about captions when sharing pictures. The product is now available on Alipay; simply swipe left after clicking 'Scan' on the homepage to find it.

The Qwen team recently announced the open-source release of their latest multimodal reasoning model, QVQ, marking an important step forward in the capabilities of artificial intelligence in visual understanding and complex problem-solving. This model is based on Qwen2-VL-72B and aims to enhance AI reasoning capabilities by combining language and visual information. In the MMMU evaluation, QVQ achieved a high score of 70.3, demonstrating significant performance improvements over Qwen2-VL-72B-Instruct in several math-related benchmark tests.