The article analyses the current situation of food safety supervision in China, summarizes the deep reason behind the food safety and puts forward some suggestions to strengthen the supervision by using foreign refere...The article analyses the current situation of food safety supervision in China, summarizes the deep reason behind the food safety and puts forward some suggestions to strengthen the supervision by using foreign references and advance operations from the legislation,the food safety supervision system and other aspects.展开更多
In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowled...In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowledge （common priors or implicit intuitions） can effectively lead to explainable, robust, and general AI, as follows： from shallow computation to deep neural reasoning; from merely data-driven model to data-driven with structured logic rules models; from task-oriented （domain-specific） intelligence （adherence to explicit instructions） to artificial general intelligence in a general context （the capability to learn from experience）. Motivated by such endeavors, the next generation of AI, namely AI 2.0, is positioned to reinvent computing itself, to transform big data into structured knowledge, and to enable better decision-making for our society.展开更多
文摘The article analyses the current situation of food safety supervision in China, summarizes the deep reason behind the food safety and puts forward some suggestions to strengthen the supervision by using foreign references and advance operations from the legislation,the food safety supervision system and other aspects.
文摘In this paper, we review recent emerging theoretical and technological advances of artificial intelligence （AI） in the big data settings. We conclude that integrating data-driven machine learning with human knowledge （common priors or implicit intuitions） can effectively lead to explainable, robust, and general AI, as follows： from shallow computation to deep neural reasoning; from merely data-driven model to data-driven with structured logic rules models; from task-oriented （domain-specific） intelligence （adherence to explicit instructions） to artificial general intelligence in a general context （the capability to learn from experience）. Motivated by such endeavors, the next generation of AI, namely AI 2.0, is positioned to reinvent computing itself, to transform big data into structured knowledge, and to enable better decision-making for our society.
