《電子技術應用》
您所在的位置:首頁 > 人工智能 > 設計應用 > 從基礎研究淺析人工智能技術發(fā)展趨勢
從基礎研究淺析人工智能技術發(fā)展趨勢
2020年電子技術應用第10期
李美桃
國家工業(yè)信息安全發(fā)展研究中心人工智能所,北京100040
摘要: 近六十多年來,人工智能在算法、算力和數(shù)據(jù)的共同驅動下,獲得了飛速發(fā)展,但仍處于弱人工智能階段。重點分析了人工智能算法和算力方面的基礎研究現(xiàn)狀和發(fā)展趨勢,弱人工智能邁向強人工智能亟待基礎研究上的革命性突破。算法層面,深度學習算法模型缺乏可釋性和可泛化性,在基礎理論上遇到瓶頸,亟待基礎理論上的突破;算力層面,因集成電路工藝制程逼近微觀物理極限導致摩爾定律失效和電子芯片算力增長趨緩,通用計算芯片架構受制于馮諾依曼瓶頸,以神經形態(tài)芯片為代表的人工智能芯片方興未艾;數(shù)據(jù)層面,細分領域的高質量數(shù)據(jù)集匱乏制約人工智能技術應用發(fā)展,未來高質量數(shù)據(jù)集將不斷構建。總之,人工智能底層技術將在未來相當長時間內緩慢前進,但產業(yè)化應用正在蓬勃發(fā)展。
中圖分類號: TP301
文獻標識碼: A
DOI:10.16157/j.issn.0258-7998.200346
中文引用格式: 李美桃. 從基礎研究淺析人工智能技術發(fā)展趨勢[J].電子技術應用,2020,46(10):29-33,38.
英文引用格式: Li Meitao. Analysis of the trend of artificial intelligence technology on basic research[J]. Application of Electronic Technique,2020,46(10):29-33,38.
Analysis of the trend of artificial intelligence technology on basic research
Li Meitao
National Industrial Information Security Development Research Center,Beijing 100040,China
Abstract: During the past sixty years, artificial intelligence(AI) has achieved rapid development jointly promoted by algorithms, computing power, and big data, but it is still in the stage of artificial narrow intelligence. The status and trends of basic research in AI algorithms and computing power are analyzed. The evolution of artificial narrow intelligence to artificial general intelligence will depend on breakthrough in AI basic theory research. On the aspect of AI algorithms, the deep learning algorithm model lacks interpretive reasoning and generalizability. AI encounters bottlenecks in basic theory and urgently needs a breakthrough. On the aspect of computing power, due to the CMOS physical limits the Moore′s law is approaching failure and the growth of computing power is slowing down, the general computing chip architecture is limited by Feng Neumann′s bottleneck and AI chips represented by neuromorphic chips are in the ascendant. On the aspect of data, the lack of high-quality data sets in specific area restricts AI technology application and more high-quality data sets will be continuously constructed in the short future. In short, the basic AI technology will slowly advance for a long time in the future, but the AI applications are booming from right now.
Key words : artificial intelligence;basic research;development trend;algorithm;computing power

0 引言

    人工智能(Artificial Intelligence,AI)是計算機技術發(fā)展到高級階段的復雜技術體系,綜合了計算機、數(shù)學、邏輯、信息論、控制論、認知科學和倫理學等多種學科。人工智能于1956年在達特茅斯學院的一次學術會議上被提出,可分為三個發(fā)展階段:弱人工智能(Artificial Narrow Intelligence,ANI)、強人工智能(Artificial General Intelligence,AGI)和超人工智能(Artificial Super Intelligence,ASI)。ANI是在限定條件下的人工智能,目前掌握的人工智能技術處于該階段,是沒有理解和推理的感知智能;AGI是能理解、推理和解決問題的機器智能,有知覺和自我意識,屬于認知智能;ASI是在幾乎所有領域都比最聰明的人類大腦都聰明的機器智能,是人工智能技術發(fā)展的終極目標。

    過去六十多年來,三大基石即算法算力和數(shù)據(jù),共同驅動著人工智能技術快速發(fā)展。本文概述了弱人工智能的發(fā)展歷程,即初始時期、知識驅動時期和數(shù)據(jù)驅動時期,重點梳理了算法和算力的前沿基礎研究進展和面臨的挑戰(zhàn),闡明了大數(shù)據(jù)在數(shù)據(jù)驅動時期對人工智能發(fā)展的巨大推動作用,最后從算法、算力、數(shù)據(jù)集和產業(yè)化應用四個方面淺析了人工智能技術的發(fā)展趨勢。




本文詳細內容請下載:http://theprogrammingfactory.com/resource/share/2000003015




作者信息:

李美桃

(國家工業(yè)信息安全發(fā)展研究中心人工智能所,北京100040)

此內容為AET網站原創(chuàng),未經授權禁止轉載。