【深度好奇DeeplyCurious是哪个国家的品牌？】

英文翻译：Deep curiosity (Beijing) Technology Co., Ltd. was established in Beijing in 2016. At the beginning of its establishment, it was invested by two domestic investment institutions in angel rounds of ten million level. Focus on becoming a competitive innovative technology company in the field of Chinese language intelligence. Deep curiosity has cutting-edge technology reserves in deep learning, natural language processing and other directions, and provides cutting-edge language intelligent technology products and services in the vertical fields of law, security, finance and so on. As an important direction of artificial intelligence, deep learning has become an important cornerstone of language intelligence. The team of the company has made pioneering contributions in the field of in-depth learning for natural language processing, and has important work in the fields of dialogue, machine translation, question answering, reasoning, natural language generation, etc. Four of the ten work in Greater China cited in Professor kyunghyuncho's summary of language intelligence at New York University came from members of the deep curiosity team. At present, the company is exploring several cutting-edge directions, such as introducing brain like mechanisms into deep learning and combining deep learning with symbolic intelligence, and applying these technologies to text understanding, text generation and dialogue. The company believes that semantic analysis and representation is one of the core tasks of natural language understanding and even artificial intelligence, as well as an important technology developed by the company. The company not only focuses on sentence parsing, but also attempts to extend this parsing to the document level, mapping articles or paragraphs into machine understandable formats. The company focuses on a new method that combines neural networks and symbolic artificial intelligence, which will be compatible with the learnability and flexibility of neural models and the interpretability and strictness of symbolic methods. As the basic technology of automatic writing and dialogue, natural language generation, especially the generation of long text, has always been one of the important technologies that companies pay attention to and invest in. The company's cutting-edge work in this area includes a text generation model based on convolutional neural network (CNN) in the world, adding ultra short term memory to the RNN generated by text to increase the effect of decoder, and embedding logic modules and human knowledge into the text depth generation model, etc.

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