From the early use of mathematical tools to explore the mechanism of neural activity, to the use of artificial neural network models to simulate human intelligence, to the solution of specific problems based on deep networks, AI has developed over the past 80 years and has now entered the era of foundation intelligence (FI), which is characterized by its foothold in large models, serving the broad social groups. The development of large models faces a series of challenges. First, the quality and quantity of data necessary for large models training need to be improved. Second, high-end computing resource is limited, and model training has high power consumption and high carbon emissions, which brings environmental problems. Third, it is the socialization of large models that brings about social development problems such as discrimination and prejudice, the spread of false information, invasion of privacy, and impact on employment. In order to overcome the aforementioned challenges, it is essential to build a federal ecosystem (including federal data, federal control, federal management and federal services) with support of block chain and decentralized autonomous organizations (TRUE+DAO, TAO), and provide solutions for the development of artificial intelligence in the new era.
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