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DeepSeek AI, a prominent Chinese artificial intelligence research lab, following its powerful open-source language model DeepSeek-R1, has achieved another significant breakthrough in the field of Large Language Models (LLMs). Recently, DeepSeek AI officially launched an innovative technology called Self-Principled Critique Tuning (SPCT), aimed at building more general-purpose and scalable AI reward models.

Meituan CEO Wang Xing detailed the company's strategic plan for artificial intelligence (AI). Wang revealed that over the past year, Meituan prioritized securing GPU resources, investing heavily in AI infrastructure. He further stated that Meituan plans to further increase investment in key AI infrastructure in 2025 to strengthen its position in this field.

AMD recently announced GAIA, an open-source application designed to provide a highly efficient and localized method for running Large Language Models (LLMs). Currently supporting Windows and optimized for Ryzen AI 300 series processors, GAIA leverages the strengths of these processors for AI tasks. GAIA is a generative AI application enabling private LLM execution on personal computers, ensuring data privacy. Furthermore, GAIA utilizes...

According to the Science and Technology Innovation Board Daily, Alibaba Cloud has launched a new initiative called "Project T" to accelerate the development of next-generation AI technologies. The project will focus on several cutting-edge areas, including AI engines, large language models (LLMs), and multi-modal technologies. The goal is to meet the growing market demand through breakthroughs in these technologies. The launch of "Project T" signifies Alibaba Cloud's further deepening of its AI strategy. Insiders reveal that this project will not only speed up AI R&D but also attract more top talent.

Large Language Models (LLMs) are constantly evolving in the field of artificial intelligence. Researchers from Carnegie Mellon University (CMU) and HuggingFace recently introduced a new method called Meta Reinforcement Fine-Tuning (MRT). This method aims to optimize the computational efficiency of LLMs during testing, particularly excelling in solving complex reasoning problems. Studies show that existing LLMs struggle with...

Alibaba has open-sourced a new inference large language model, QwQ-32B. Benchmarks show performance comparable to DeepSeek-R1, but with significantly reduced VRAM requirements.

Are you still struggling with handling various formats of unstructured documents? Fireworks AI has recently launched an innovative feature called 'Document Inlining' that can convert unstructured documents such as PDFs, screenshots, and images into structured text that large language models (LLMs) can understand. This provides chatbots and AI models with usable text content, significantly enhancing the efficiency and accuracy of AI document processing. The core of Document Inlining lies in its powerful composite capabilities.

Booz Allen Hamilton has successfully deployed and operated the first generative AI large language model (LLM) on the International Space Station, marking a significant breakthrough for artificial intelligence in the field of space. This model operates using HPE's Spaceborne Computer-2 at the ISS National Laboratory, enabling the use of a powerful AI assistant to tackle complex problems and retrieve information in space without reliance on Earth's internet. The development process took only eight weeks, demonstrating the potential of AI in extreme environments.

NASA's Interagency Implementation and Advanced Concepts Team (IMPACT) is jointly developing INDUS, a suite of large language models (LLM) aimed at fields such as Earth science, biological and physical sciences, heliophysics, planetary science, and astrophysics, through signing Space Act agreements with private, non-federal partners. The model is trained using curated scientific literature from diverse data sources.

Google's Gemini model, born only six months ago, has already demonstrated remarkable capabilities in safety, coding, debugging, and more. However, it also shows serious limitations. Nonetheless, this large language model (LLM) surpasses humans in providing sleep and fitness recommendations.