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关于“大立科技”的报告

本报告研究涉及企业/品牌/案例:华为,大立科技,云测数据,京东众智,百度数据众包,阿里云,百度智能云,深海科技,商汤,云从科技,依图,阅面科技,出门问问,科大讯飞,云知声,普强信息,阿里巴巴,百度,腾讯,京东,松鼠AI,小i机器人,图灵机器人,海康威视,学堂在线,知鸟,蚂蚁金服,第四范式,京东数科,百度医疗大脑,阿里健康,平安智慧城市,一汽,大众,启辰,东风日产

中国人工智能产业增长快速,预计2030年中国人工智能核心产业规模将突破10000亿元。数据的沉积、算法的优化和算力的提升为人工智能技术的商业化应用奠定了坚实基础。越来越多传统行业借助人工智能技术进行转型升级,并受到大众的广泛关注。iiMedia Research(艾媒咨询)数据显示,人工智能与金融、安防、医疗、教育等领域的融合发展成为大众的重点关注领域,37.8%的受访者表示最了解人工智能在金融领域的应用;39.3%的受访者最期待人工智能在医疗领域的应用;66.8%的受访者对人工智能未来发展表示看好。艾媒咨询分析师认为,随着人工智能领域细分化和专业化程度的不断提升,人工智能商业化进程将会提速,但快速发展携带而来的信息安全风险以及道德伦理问题不容忽视。
China's artificial intelligence industry is growing rapidly. It is expected that the scale of China's artificial intelligence core industry will exceed 100 billion yuan in 2030. The deposition of data, the optimization of algorithms, and the enhancement of computing power have laid a solid foundation for the commercial application of artificial intelligence technology. More and more traditional industries rely on artificial intelligence technology for transformation and upgrading, and they have attracted widespread attention. According to iiMedia Research data, the integrated development of artificial intelligence and finance, security, medical care, education and other fields has become the focus of attention of the public. 37.8% of the respondents said they knew the application of artificial intelligence in the financial field best; 39.3 % Of the respondents are most looking forward to the application of artificial intelligence in the medical field; 66.8% of the respondents are optimistic about the future development of artificial intelligence. iiMedia Consulting analysts believe that with the continuous improvement of the segmentation and specialization of the artificial intelligence field, the commercialization of artificial intelligence will accelerate, but the information security risks and ethical issues brought about by rapid development cannot be ignored.

本报告研究涉及企业/品牌/案例:百度,小马智行,深兰科技,深兰科技,商汤科技,地平线机器人,大立科技,数多多,Cambricon, 数据堂,IBM, Magic Data,海深科技,阿里巴巴,华为,京东,滴滴出行,小i机器人,图灵机器人,科大讯飞,普强信息,云知声,出门问问,依图,海鑫科金,腾讯云

随着政策的推动以及资本的关注,人工智能产业仍将保持迅猛发展态势,2020年中国人工智能核心产业规模将超1500亿元。当前人工智能的商业化主要是基于计算机视觉、智能语音、自然语言处理等技术,技术应用面广泛,涉及智能医疗、智能驾驶、智能家居等多场景。2018年中国人工智能领域共融资1311亿元,增长率超过100%,投资者看好人工智能行业的发展前景,资本将助力行业更好地发展。在人工智能与出行结合领域,路径规划、网络约车、交通管理、自动驾驶等技术的研发解决了传统出行不便的痛点,其中深兰科技深耕智能交通、智能环境、智能城市等细分领域,已实现人工智能产品落地。其深兰科技熊猫智能公交车已实现在广州、天津等国内多个城市试运行。而人工智能与安防、医疗、零售等产业的结合,均解决了一定行业痛点,利用机器学习算法、深度学习和NLP促进行业发展。随着5G商用时代的逐渐来临,人工智能技术连接效率也将进一步提升,深度学习、数据挖掘、自动程序设计等领域也将在更多的应用领域得到实现。

With the promotion of policy and the attention of capital, the AI industry will continue to develop rapidly, and the scale of China's AI core industry will exceed 150 billion yuan by 2020. At present, the commercialization of AI is mainly based on computer vision, intelligent voice, natural language processing and other technologies. It has a wide range of applications, including intelligent medical, intelligent driving, intelligent home and other scenarios. In 2018, China's AI sector raised 131.1 billion yuan, with a growth rate of more than 100%. Investors are optimistic about the prospects of AI industry, and capital will help the industry develop better. In the field of combination of artificial intelligence and travel, the research and development of technologies such as path planning, network car appointment, traffic management and automatic driving have solved the pain points of traditional travel inconvenience. Among them, Shenlan Science and Technology has realized the landing of artificial intelligence products in the sub-fields of intelligent transportation, intelligent environment, intelligent city and so on. Its Shenlan Panda Intelligent Bus has been put into trial operation in Guangzhou, Tianjin and other domestic cities. The combination of AI and security, medical, retail and other industries has solved some industry pain points, using machine learning algorithm, in-depth learning and NLP to promote the development of the industry. With the gradual advent of 5G commercial era, the efficiency of artificial intelligence technology connection will be further improved. In-depth learning, data mining, automatic programming and other fields will also be realized in more application areas.

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