A Novel Deep Neural Network Architecture for Real-Time Water Demand Forecasting

President Trump has announced a significant policy shift allowing Nvidia to sell its advanced H200 AI chips to approved customers in China, effectively lifting a previous export ban imposed due to national security concerns. This decision includes a 25% surcharge on sales, which experts have criticized as illogical given the context of the deal.

The Bay Area is poised to play a crucial role in the Genesis Mission, a multibillion-dollar initiative launched by the Trump administration aimed at enhancing the United States' artificial intelligence capabilities amid growing competition from China. This mission will leverage federal scientific datasets to train AI models and develop AI agents, marking a significant government effort to boost innovation in this critical sector.

US startups, including Oakland-based Brimstone, are intensifying efforts to develop domestic sources of critical raw materials essential for technology, an area historically dominated by China. This initiative is part of a broader strategy to enhance supply chain resilience and reduce dependence on foreign sources.

DeepSeek, a Chinese AI startup, is reportedly developing its next AI model using several thousand Nvidia Blackwell chips that were smuggled into China through third-party countries. This development raises concerns regarding compliance with international trade regulations and the implications of using restricted technology.

The former chief executive of Nexperia, a Dutch semiconductor company, revealed that Dutch officials were aware for years of the company's Chinese owner’s intentions to transfer technology to China. This revelation follows the Dutch government's seizure of Nexperia in September, amid rising concerns over technology security.

A new study presents a problem generator designed to enhance data synthesis for large reasoning models, addressing challenges such as indiscriminate problem generation and lack of reasoning in problem creation. This generator adapts problem difficulty based on the solver's ability and incorporates feedback as a reward signal to improve future problem design.

A new study has introduced a method for glass surface detection that leverages the dynamics of reflections in both flash and no-flash imagery. This approach addresses the challenges posed by the transparent and featureless nature of glass, which has traditionally hindered accurate localization in computer vision tasks. The method utilizes variations in illumination intensity to enhance detection accuracy, marking a significant advancement in the field.

A recent study published on arXiv addresses the complexities of feature learning in deep learning, proposing a heuristic method to predict the scales at which different feature learning patterns emerge. This approach simplifies the analysis of high-dimensional non-linear equations that typically characterize deep learning problems, which often require extensive computational resources.