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深度好奇DeeplyCurious在人工智能AI行业中的票数：200 更新时间：2025-04-27

深度好奇DeeplyCurious是哪个国家的品牌？「深度好奇DeeplyCurious」是深度好奇(北京)科技有限公司旗下著名品牌。该品牌发源于北京市，由创始人李祥生在2016-08-19期间创立，经过多年的不懈努力和高速发展，现已成为行业的标杆品牌。

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深度好奇（北京）科技有限公司，2016年设立于北京，成立初期即获国内两家投资机构千万级天使轮投资。专注于成为中国语言智能领域具竞争力的创新技术公司。

深度好奇在深度学习、自然语言处理等方向拥有前沿的技术储备，并面向法律、安全、金融等垂直领域，提供前沿的语言智能技术产品和服务。

作为人工智能重要的方向，深度学习已经成为语言智能重要的基石。公司的团队在深度学习用于自然语言处理方向做出了开创性贡献，在对话、机器翻译、问答、推理、自然语言生成等领域均有重要工作。在纽约大学Kyunghyun Cho教授对语言智能的总结所引用的十篇大中华区的工作中，有四篇来自深度好奇团队成员。目前，公司正探索若干个前沿方向，如将类脑的机制引入深度学习以及将深度学习和符号智能进行结合等，并将这些技术应用于文本理解、文本生成和对话等领域。

公司认为语义的解析和表示是自然语言理解乃至人工智能的核心任务之一，也是公司研发的重要技术。公司不但关注对句子的解析，而且试图将这种解析延拓至文档级别，将文章或段落映射成为机器可“理解”的格式。公司聚焦一类将神经网络和符号人工智能结合的新方法，它将兼容神经模型的可学习性和灵活性与符号方法的可解释性和严格性。

作为自动写作、对话等的基础技术，自然语言生成，尤其是长文本的生成，一直是公司关注和投入的重要技术之一。公司在这方面的前沿工作包括世界上一个基于卷积神经网络（CNN）的文本生成模型、对文本生成的RNN加入超短期记忆来增加解码器的效果、以及将逻辑模块和人类知识嵌入文本深度生成模型等。

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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