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A GitHub open-source project named "system-prompts-and-models-of-ai-tools" has gained significant traction, accumulating 30.5K stars and becoming a popular resource for AI developers and researchers. This project, according to AIbase, compiles system prompts and model configurations for 9 mainstream AI tools, encompassing over 6500 lines of content and covering v0, Cursor, Manus, Same.dev, Lovable, Devin, and Rep.

This practical guide from OpenAI provides a hands-on approach to building intelligent agents. Includes helpful resources and documentation to aid in the development process.

Today, OpenAI, a leading artificial intelligence company, quietly launched a new educational platform—OpenAI Academy—without widespread publicity. This move is seen as a significant step by OpenAI in promoting the popularization of AI education and skills training, aiming to provide free, high-quality learning resources to global users. According to the latest news, the OpenAI Academy is now live and offers a wealth of content, including video courses and events.

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.

A collaborative team from Ant Group, Zhejiang University, University of Liverpool, and East China Normal University presented ScaleOT, a novel cross-domain fine-tuning framework, at AAAI 2025. This framework achieves a 50% improvement in privacy protection and a remarkable 90% reduction in computational cost compared to knowledge distillation, without compromising model performance. ScaleOT offers a highly efficient and lightweight solution for cross-domain fine-tuning of billion-parameter models. The innovative nature of the paper secured it an oral presentation at AAAI.

The AI field is abuzz with the recent news of Moonshot's open-sourcing of its new optimizer, Muon, which boasts a computational efficiency twice that of traditional AdamW. This release coincides with DeepSeek's upcoming release of several codebases, generating significant industry attention and discussion. The Muon optimizer was initially proposed by OpenAI researchers Keller Jordan et al. in 2024 and showed excellent performance in training small-scale models. However,

A new artificial intelligence startup, Borderless AI, is focusing on making the human resources department the next major battleground for enterprise AI applications. The company recently announced the launch of its first product, HRGPT, a free AI-driven search engine designed to help businesses manage internal HR data and related employment laws and regulations more efficiently. Image source note: Image generated by AI, image licensed from service provider Midjourney. Borderless AI has been in the market since last year.

As businesses increasingly adopt large language models (LLMs), improving the accuracy of model knowledge and reducing hallucination phenomena has become a significant challenge. Researchers at Meta AI have introduced a 'Scalable Memory Layer' in a recent paper, which may provide a solution to this issue. The core idea of the scalable memory layer is to add more parameters to the LLMs without increasing computational resources during inference, thereby enhancing their learning capabilities. This architecture is suitable for storing large amounts of factual knowledge while maintaining...

For a long time, efficiently generating high-quality, wide-angle 3D scenes from a single image has been a challenge faced by researchers. Traditional methods often rely on multi-view data or require time-consuming per-scene optimization, and they struggle with background quality and reconstruction of unseen areas. Existing technologies, when dealing with single-view 3D scene generation, often produce errors or distortions in occluded areas due to insufficient information, along with blurry backgrounds and difficulties in inferring the geometric structure of unseen regions. While regression-based models can synthesize new views in a feedforward manner, they struggle with complex...

Schneider Electric recently released a report on the future power consumption of artificial intelligence (AI) data centers, urging policymakers to carefully guide the power usage of AI data centers. The study was published following last month's International Energy Agency (IEA) Global Energy and AI Conference, titled 'Artificial Intelligence and Power: A System Dynamics Approach.' The report explores various scenarios of power consumption related to AI, highlighting the potential strain on the power grid from the continuously growing AI infrastructure. Image source note: Image generated by AI, image.

On December 24, the Shanghai Municipal Government Office announced the 'Work Plan for the Development of Medical Artificial Intelligence in Shanghai (2025-2027)'. The plan clarifies the main tasks and goals for the next three years, aiming to respond to the national strategic deployment of 'AI + Action'. By promoting deep integration of medical innovation and artificial intelligence, it seeks to transform Shanghai into a globally influential hub for innovation, application demonstration, and industrial development in medical AI technology.

Recently, Rony Abovitz, the founder of Magic Leap, has once again captured public attention with his new company SynthBee, which has just completed a $20 million funding round. Located in Fort Lauderdale, Florida, the same place where Magic Leap rose to fame and sparked excitement around mixed reality computing, this funding aims primarily to expand the team and advance its unique computational intelligence platform. Image credit: Photo by AI generation.