《電子技術(shù)應(yīng)用》
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從基礎(chǔ)研究淺析人工智能技術(shù)發(fā)展趨勢(shì)
2020年電子技術(shù)應(yīng)用第10期
李美桃
國(guó)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(lái),人工智能在算法、算力和數(shù)據(jù)的共同驅(qū)動(dòng)下,獲得了飛速發(fā)展,但仍處于弱人工智能階段。重點(diǎn)分析了人工智能算法和算力方面的基礎(chǔ)研究現(xiàn)狀和發(fā)展趨勢(shì),弱人工智能邁向強(qiáng)人工智能亟待基礎(chǔ)研究上的革命性突破。算法層面,深度學(xué)習(xí)算法模型缺乏可釋性和可泛化性,在基礎(chǔ)理論上遇到瓶頸,亟待基礎(chǔ)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(dǎo)致摩爾定律失效和電子芯片算力增長(zhǎng)趨緩,通用計(jì)算芯片架構(gòu)受制于馮諾依曼瓶頸,以神經(jīng)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(xì)分領(lǐng)域的高質(zhì)量數(shù)據(jù)集匱乏制約人工智能技術(shù)應(yīng)用發(fā)展,未來(lái)高質(zhì)量數(shù)據(jù)集將不斷構(gòu)建。總之,人工智能底層技術(shù)將在未來(lái)相當(dāng)長(zhǎng)時(shí)間內(nèi)緩慢前進(jìn),但產(chǎn)業(yè)化應(yīng)用正在蓬勃發(fā)展。
中圖分類號(hào): TP301
文獻(xiàn)標(biāo)識(shí)碼: A
DOI:10.16157/j.issn.0258-7998.200346
中文引用格式: 李美桃. 從基礎(chǔ)研究淺析人工智能技術(shù)發(fā)展趨勢(shì)[J].電子技術(shù)應(yīng)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(jì)算機(jī)技術(shù)發(fā)展到高級(jí)階段的復(fù)雜技術(shù)體系,綜合了計(jì)算機(jī)、數(shù)學(xué)、邏輯、信息論、控制論、認(rèn)知科學(xué)和倫理學(xué)等多種學(xué)科。人工智能于1956年在達(dá)特茅斯學(xué)院的一次學(xué)術(shù)會(huì)議上被提出,可分為三個(gè)發(fā)展階段:弱人工智能(Artificial Narrow Intelligence,ANI)、強(qiáng)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(shù)處于該階段,是沒(méi)有理解和推理的感知智能;AGI是能理解、推理和解決問(wèn)題的機(jī)器智能,有知覺(jué)和自我意識(shí),屬于認(rèn)知智能;ASI是在幾乎所有領(lǐng)域都比最聰明的人類大腦都聰明的機(jī)器智能,是人工智能技術(shù)發(fā)展的終極目標(biāo)。

    過(guò)去六十多年來(lái),三大基石即算法算力和數(shù)據(jù),共同驅(qū)動(dòng)著人工智能技術(shù)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(shí)期、知識(shí)驅(qū)動(dòng)時(shí)期和數(shù)據(jù)驅(qū)動(dòng)時(shí)期,重點(diǎn)梳理了算法和算力的前沿基礎(chǔ)研究進(jìn)展和面臨的挑戰(zhàn),闡明了大數(shù)據(jù)在數(shù)據(jù)驅(qū)動(dòng)時(shí)期對(duì)人工智能發(fā)展的巨大推動(dòng)作用,最后從算法、算力、數(shù)據(jù)集和產(chǎn)業(yè)化應(yīng)用四個(gè)方面淺析了人工智能技術(shù)的發(fā)展趨勢(shì)




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作者信息:

李美桃

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

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