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According to a deep analysis of Mary Meeker's latest AI trend report, the world's largest tech companies are investing in AI research and development and capital expenditure on an unprecedented scale and speed. The report points out that over the past two decades, capital expenditures in the technology industry have been continuously increasing, initially for storing and accessing data, then for distributing and scaling, and now mainly focusing on computing and intelligence. This AI trend report highlights that by 2023, AI has evolved from a research function into an important capital expenditure project. The six major U.S. companies...

On June 3rd, Mary Meeker, known as the 'Internet Queen', released her 340-page report 'Trends - Artificial Intelligence' on May 30th. The report runs throughout with the word 'unprecedented', emphasizing that the development, adoption, investment, and application speed of AI technology has far exceeded any previous technological revolution. Key points: The speed of AI transformation overturns historical understanding. In the report, Meeker pointed out that the explosive growth trend of AI user numbers, technology iteration, and capital investment presents an 'upward-right' curve.

ZhiYuan Research Institute has unveiled the new open-source bilingual model Wudao・Tianying 34 Billion Aquila2-34B, which excels in reasoning, generalization, and more. The institute has also released a comprehensive open-source toolkit to promote collaborative innovation in large model research. Aquila2-34B surpasses other open-source foundational models in overall capabilities, with the ZhiYuan team developing the NLPE method to enhance the model's extension capabilities.

Shanghai AI Lab, in collaboration with the Corpus Data Alliance, has open-sourced the 'Shusheng・Wanjuan' 1.0 multi-modal pre-trained dataset, which includes text, images, and video datasets, totaling over 2TB. The dataset has undergone fine-grained cleaning and deduplication, featuring multi-dimensional integration, meticulous processing, and ease of use. The release of this open-source dataset will help promote the application and innovation of large models and lower the technical barriers associated with large model technologies.