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US Solar Power Surpasses Hydro on Grid After 35% Growth, According to Final 2025 Data

The latest energy data for 2025 reveals a significant shift in the US power landscape, with solar energy generation now exceeding hydropower. This milestone follows a remarkable 35% growth in solar capacity. The report indicates an overall increase in US energy consumption. This development highlights the accelerating transition towards renewable energy sources in the United States.

Hacker News

The final energy data for 2025 has been released, indicating a notable change in the composition of the US power grid. Solar power has officially surpassed hydropower in terms of electricity generation. This achievement is attributed to a substantial 35% growth in solar capacity over the period. Concurrently, the data also shows an increase in overall energy use across the United States. This shift underscores the growing prominence of solar energy as a key contributor to the nation's power supply and its role in the broader renewable energy transition.

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Meituan AI Research Milestone: 32 Papers Accepted at Top 2026 Conferences Including ACL Outstanding Award
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Meituan AI Research Milestone: 32 Papers Accepted at Top 2026 Conferences Including ACL Outstanding Award

In a significant display of academic and technical prowess, Meituan's technical team has announced the acceptance of dozens of research papers at premier AI conferences in 2026, including ACL, SIGIR, ICML, and KDD. The team has curated 32 of these high-impact papers for a specialized five-session livestream series designed to share their findings with the broader AI community. A standout achievement in this year's cohort is the receipt of an 'Outstanding Paper' award at ACL 2026, highlighting Meituan's contribution to cutting-edge Natural Language Processing. This comprehensive collection of research underscores Meituan's commitment to advancing AI across multiple domains, from machine learning to information retrieval and data mining, bridging the gap between industrial application and academic excellence.

Meituan Unveils LongCat-2.0: A 1.6-Trillion Parameter Model Trained on 50,000 Domestic GPUs
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Meituan's technology team has officially announced the release of LongCat-2.0, a pioneering large-scale model featuring 1.6 trillion parameters. This model distinguishes itself as the first in the industry to complete its entire training and inference lifecycle on a domestic computing cluster comprising 50,000 cards. LongCat-2.0 is designed with a dynamic architecture, maintaining an average activation of 48 billion parameters and native support for a 1-million-token ultra-long context window. Developed from scratch, the model's core objective is to revolutionize 'Agentic Coding' by providing a stable and efficient platform for complex code understanding, generation, and execution tasks. This release marks a significant milestone in the development of high-capacity AI models using localized hardware infrastructure.

Meituan Technical Team Showcases Machine Learning Research at ICML 2026: Bridging Theory and Practice
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Meituan Technical Team Showcases Machine Learning Research at ICML 2026: Bridging Theory and Practice

The Meituan Technical Team has announced its selection of academic papers for the 2026 International Conference on Machine Learning (ICML), one of the most prestigious global forums in the field. ICML serves as a primary venue for exploring the critical challenges and core issues defining the future of machine learning. By contributing research that emphasizes both theoretical value and practical impact, Meituan aims to drive the industry forward and help set the direction for future academic and industrial inquiries. This participation underscores the company's commitment to evaluating and disseminating frontier research results that address complex problems within the machine learning landscape. The selection highlights Meituan's ongoing efforts to integrate high-level academic research with real-world technological applications, reinforcing its position as a significant contributor to the global machine learning community.