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热词推荐: 能源基础设施

人工智能基础资源建设和开放共享发展现状及建议

文章摘要

随着人工智能技术快速迭代与深入融合发展,人工智能基础资源建设与开放共享水平愈来愈成为影响人工智能产业发展的重要因素。人工智能基础资源开放平台具备统筹配置算力、数据、算法资源和产业服务能力的优势,逐渐成为人工智能基础资源供给的重要载体。近年来,我国人工智能基础资源需求快速增长,国家大力推进开放平台建设以打造人工智能产业底座。北京、上海、深圳等人工智能先行先试地区围绕当地产业布局基础资源建设,科技企业也依托各自技术和产业优势建设开放平台以培育自身产业生态。云计算和智算中心等算力基础设施建设加快推进,高质量数据集和开源框架、大模型等不断发展,人工智能基础资源开放共享能力不断提高。然而,目前我国人工智能基础资源建设仍存在算力缺口大、公共数据集建设与开放共享滞后、开源算法生态尚未构建、安全风险叠加放大等问题,仍需从强化统筹规划、加大政策扶持、强化风险管理等方面加强系统谋划和有效应对。

Abstract

With the rapid iteration and deep integration of artificial intelligence technology,the construction and open sharing level of artificial intelligence basic resources have increasingly become important factors affecting the development of the artificial intelligence industry. The open platform of basic AI resources has the advantages of overall allocation of computing power,data,algorithm resources and industrial service capabilities,and has gradually become an important carrier for the supply of basic AI resources. In recent years,the demand for basic AI resources in China has grown rapidly,and the country has vigorously promoted the construction of open platform to build an AI industry base. Artificial intelligence pilot areas such as Beijing,Shanghai and Shenzhen focus on the construction of basic resources for local industrial layout,and technology enterprises also rely on their own technology and industrial advantages to build open platform to cultivate their own industrial ecology. The construction of computing infrastructure such as cloud computing and intelligent computing center has been accelerated,high-quality data sets,open source frameworks,large models,etc. have been continuously developed,and the ability to open and share AI infrastructure resources has been constantly improved. However,there are still problems in the construction of artificial intelligence basic resources in China,such as a large computing power gap,lagging behind in the construction and open sharing of public datasets,the lack of an open source algorithm ecosystem,and the amplification of security risks. It is still necessary to strengthen systematic planning and effective response by strengthening overall planning,increasing policy support,and strengthening risk management.

作者简介
宋琦:宋琦,博士,国家工业信息安全发展研究中心工程师,主要从事国内外人工智能、数据安全等领域政策与产业研究工作。