文/吉爾·普雷斯 譯/申軍

By Gil Press

人工智能技術(shù)市場(chǎng)蓬勃發(fā)展。相關(guān)宣傳不絕于耳，媒體關(guān)注度不斷提高，創(chuàng)業(yè)公司大量涌現(xiàn)，互聯(lián)網(wǎng)巨頭爭(zhēng)相收購(gòu)人工智能領(lǐng)域初創(chuàng)公司，企業(yè)對(duì)人工智能的投資和應(yīng)用程度也大幅增長(zhǎng)。自動(dòng)寫作科技公司去年進(jìn)行了一項(xiàng)調(diào)查，發(fā)現(xiàn)已有38%的企業(yè)在使用人工智能技術(shù)，到2018年這一數(shù)字會(huì)增長(zhǎng)到62%。弗雷斯特研究公司預(yù)計(jì)2017年人工智能投資將比2016年增長(zhǎng)300%以上。國(guó)際數(shù)據(jù)公司估計(jì)人工智能市場(chǎng)將會(huì)從2016年的80億美元增長(zhǎng)到2020年的超過(guò)470億美元。

人工智能一詞最早出現(xiàn)在1955年，當(dāng)時(shí)用來(lái)命名計(jì)算機(jī)科學(xué)一個(gè)新的子學(xué)科，如今它囊括了多種技術(shù)和工具，有些經(jīng)過(guò)了時(shí)間考驗(yàn)，有些還相對(duì)較新。為了讓人們了解該領(lǐng)域的各項(xiàng)熱點(diǎn)和冷門技術(shù)，弗雷斯特公司新近在科技雷達(dá)網(wǎng)站面向應(yīng)用開發(fā)人員發(fā)布了一份關(guān)于人工智能的報(bào)告，詳細(xì)分析了企業(yè)應(yīng)考慮用以支持人工決策的13種技術(shù)。

The market for artificial intelligence(AI) technologies is flourishing.Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises.A Narrative Science survey found last year that 38% of enterprises are already using AI, growing to 62% by 2018. Forrester Research predicted a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.

Coined in 1955 to describe a new computer science sub-discipline, “Artificial Intelligence” today includes a variety of technologies and tools, some time-tested, others relatively new. To help make sense of what’s hot and what’s not, Forrester just published a TechRadar report on Artificial Intelligence (for application development professionals), a detailed analysis of 13 technologies enterprises should consider adopting to support human decisionmaking.

1. Natural Language Generation:Producing text from computer data.Currently used in customer service,report generation, and summarizing business intelligence insights. Sample vendors: Attivio, Automated Insights,Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science,SAS, Yseop.

2. Speech Recognition: Transcribe and transform human speech into format useful for computer applications.Currently used in interactive voice response systems and mobile applications.Sample vendors: NICE, Nuance Communications, OpenText, Verint Systems.

3. Virtual Agents: “The currentdarling of the media,” says Forrester(I believe they refer to my evolving relationships with Alexa), from simple chatbots to advanced systems that can network with humans. Currently used in customer service and support and as a smart home manager. Sample vendors:Amazon, Apple, Artificial Solutions,Assist AI, Creative Virtual, Google,IBM, IPsoft, Microsoft, Satisf i.

基于弗雷斯特公司的分析，我認(rèn)為下列10種技術(shù)是人工智能的熱點(diǎn)：

1.自然語(yǔ)言生成：從計(jì)算機(jī)數(shù)據(jù)生成文本。目前用于客戶服務(wù)、報(bào)告生成和總結(jié)商業(yè)智能情報(bào)。代表供應(yīng)商有：艾特維奧數(shù)據(jù)公司、自動(dòng)思維科技公司、劍橋語(yǔ)義數(shù)據(jù)公司、數(shù)碼邏輯研究公司、路希德公司、自動(dòng)寫作科技公司、統(tǒng)計(jì)分析軟件公司、易奧普公司。

2.語(yǔ)音識(shí)別：將人類語(yǔ)言轉(zhuǎn)錄，生成可用于計(jì)算機(jī)應(yīng)用程序的格式。目前用于交互式語(yǔ)音應(yīng)答系統(tǒng)和移動(dòng)終端應(yīng)用。代表供應(yīng)商有：奈斯公司、努昂斯通信公司、歐朋文本科技公司、慧銳系統(tǒng)公司。

3.虛擬代理：弗雷斯特公司表示，虛擬代理目前是“媒體的寵兒”，（我覺得他們是指我對(duì)亞馬遜語(yǔ)音助手亞歷克薩的態(tài)度變化），從簡(jiǎn)單的聊天機(jī)器人到高級(jí)人機(jī)交流系統(tǒng)都受到廣泛關(guān)注。目前用于客戶服務(wù)和支持以及管理智能家居。代表供應(yīng)商有：亞馬遜、蘋果、人工智能服務(wù)公司、人工智能助手研究公司、虛擬創(chuàng)見公司、谷歌、國(guó)際商業(yè)機(jī)器公司、愛普軟件公司、微軟、賽第斯菲科技公司。

我們對(duì)月球表面的了解勝過(guò)對(duì)地球海底的了解，這一點(diǎn)令人震驚，但事實(shí)的確如此。我們對(duì)海底的了解大多來(lái)自科學(xué)大洋鉆探——從深海海底系統(tǒng)采集巖芯樣本。這一革命性技術(shù)始于50年前的1968年8月11日，當(dāng)時(shí)在聯(lián)邦資助的深海鉆探項(xiàng)目中，“格洛馬爾挑戰(zhàn)者（Glomar Challenger）”號(hào)鉆探船首次遠(yuǎn)征，駛?cè)肽鞲鐬场?/p>

4.機(jī)器學(xué)習(xí)平臺(tái)：提供算法、應(yīng)用程序接口、開發(fā)和培訓(xùn)工具包、數(shù)據(jù)，及計(jì)算能力，用于設(shè)計(jì)、訓(xùn)練、實(shí)施模型，并將這些模型用于應(yīng)用軟件、過(guò)程和其他機(jī)器上。目前在企業(yè)各種應(yīng)用程序中廣泛使用，主要涉及預(yù)測(cè)或分類。代表供應(yīng)商有：亞馬遜、福萊科特?cái)?shù)據(jù)分析公司、谷歌、H2O智能平臺(tái)、微軟、統(tǒng)計(jì)分析軟件公司、天樹信息公司。

5.人工智能優(yōu)化的硬件：專門設(shè)計(jì)和架構(gòu)的圖形處理單元和設(shè)備，可有效運(yùn)行面向人工智能的計(jì)算任務(wù)。目前主要在深度學(xué)習(xí)應(yīng)用上發(fā)揮作用。代表供應(yīng)商有：阿魯維艾特公司、克雷研究公司、谷歌、國(guó)際商業(yè)機(jī)器公司、英特爾、英偉達(dá)。

6.決策管理：給人工智能系統(tǒng)插入規(guī)則和邏輯的引擎，用于初始安裝、培訓(xùn)以及后續(xù)維護(hù)和調(diào)優(yōu)。這已是一種成熟的技術(shù)，廣泛在各種企業(yè)應(yīng)用程序中使用，協(xié)助或執(zhí)行自動(dòng)化決策。代表性供應(yīng)商有：高級(jí)系統(tǒng)概念公司、茵弗莫迪卡信息公司、瑪納公司、培格科技公司、創(chuàng)徑公司。

4. Machine Learning Platforms:Providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train,and deploy models into applications,processes, and other machines. Currently used in a wide range of enterprise applications, mostly involving prediction or classification. Sample vendors:Amazon, Fractal Analytics, Google,H2O.ai, Microsoft, SAS, Skytree.

5. AI-optimized Hardware: Graphics processing units (GPU) and appliances specifically designed and architected to efficiently run AI-oriented computational jobs. Currently primarily making a difference in deep learning applications. Sample vendors: Alluviate, Cray, Google, IBM, Intel, Nvidia.

6. Decision Management: Engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning.A mature technology, it is used in a wide variety of enterprise applications,assisting in or performing automated decision-making. Sample vendors: Advanced Systems Concepts, Informatica,Maana, Pegasystems, UiPath.

7. Deep Learning Platforms: A special type of machine learning consisting of artificial neural networks with multiple abstraction layers. Currently primarily used in pattern recognition and classification applications supported by very large data sets. Sample vendors:Deep Instinct, Ersatz Labs, Fluid AI,MathWorks, Peltarion, Saffron Technology, Sentient Technologies.

8. Biometrics: Enable more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Currently used primarily in market research. Sample vendors:3VR, Affectiva, Agnitio, FaceFirst,Sensory, Synqera, Tahzoo.

9. Robotic Process Automation:Using scripts and other methods to automate human action to support efficient business processes. Currently used where it’s too expensive or inefficient for humans to execute a task or a process. Sample vendors: Advanced Systems Concepts, Automation Anywhere,Blue Prism, UiPath, WorkFusion.

10. Text Analytics and NLP: Natural language processing (NLP) uses and supports text analytics by facilitating the understanding of sentence structure and meaning, sentiment, and intent through statistical and machine learning methods. Currently used in fraud detection and security, a wide range of automated assistants, and applications for mining unstructured data. Sample vendors: Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics,Linguamatics, Mindbreeze, Sinequa,Stratifyd, Synapsify.

7.深度學(xué)習(xí)平臺(tái)：一種由具有多個(gè)抽象層的人工神經(jīng)網(wǎng)絡(luò)組成的特殊類型機(jī)器學(xué)習(xí)。目前主要用于依托大型數(shù)據(jù)集進(jìn)行的模式識(shí)別和應(yīng)用分類。代表供應(yīng)商有：深層本能、厄薩茨實(shí)驗(yàn)室、暢德人工智能公司、數(shù)學(xué)研究公司、培勒塔瑞恩軟件公司、紅花科技、感知科技公司。

8.生物計(jì)量學(xué)：實(shí)現(xiàn)更自然的人機(jī)交際，包括但不限于圖像和指紋識(shí)別、言語(yǔ)和肢體語(yǔ)言。目前主要用于市場(chǎng)研究。代表供應(yīng)商有：三維虛擬科技公司、阿凡客科技公司、洹藝科技、菲斯面部識(shí)別科技公司、森斯語(yǔ)音識(shí)別公司、鑫克拉科技公司、塔祖科技公司。

9.機(jī)器人過(guò)程自動(dòng)化：使用腳本和其他方法自動(dòng)執(zhí)行人為操作來(lái)支持高效的業(yè)務(wù)流程。目前用于人力成本高或效率低的任務(wù)或流程領(lǐng)域。代表供應(yīng)商有：高級(jí)系統(tǒng)概念公司、全能自動(dòng)化公司、藍(lán)棱鏡公司、創(chuàng)徑公司、融合科技公司。

10.文本分析和自然語(yǔ)言處理：自然語(yǔ)言處理通過(guò)統(tǒng)計(jì)和機(jī)器學(xué)習(xí)的方法，促進(jìn)對(duì)句子結(jié)構(gòu)、意義、情感和意圖的理解，從而使用和支持文本分析。目前用于欺詐行為檢測(cè)和安全維護(hù)，各種自動(dòng)化助理，以及挖掘非結(jié)構(gòu)化數(shù)據(jù)的應(yīng)用程序。代表供應(yīng)商有：基礎(chǔ)科技公司、柯維傲公司、專業(yè)系統(tǒng)科技公司、茵迪克公司、奈姆公司、萊克斯分析公司、語(yǔ)言數(shù)字公司、清風(fēng)思維公司、鑫諾克公司、斯圖飛騰公司、鑫奈科技公司。

今天，人工智能技術(shù)毫無(wú)疑問(wèn)帶來(lái)了許多商業(yè)利益，但根據(jù)弗雷斯特公司去年進(jìn)行的調(diào)查，人工智能在應(yīng)用方面也面對(duì)著一些障礙，以下是對(duì)一些在人工智能領(lǐng)域沒有投資計(jì)劃的公司進(jìn)行的調(diào)查統(tǒng)計(jì)。

There are certainly many business benefits gained from AI technologies today, but according to a survey Forrester conducted last year, there are also obstacles to AI adoption as expressed by companies with no plans of investing in AI:

There is no def i ned business case 42%Not clear what AI can be used for 39%Don’t have the required skills 33%Need fi rst to invest in modernizing data mgt platform 29%Don’t have the budget 23%Not certain what is needed for implementing an AI system 19%AI systems are not proven 14%

Once enterprises overcome these obstacles, Forrester concludes, they stand to gain from AI driving accelerated transformation in customer-facing applications and developing an interconnected web of enterprise intelligence. ■

缺乏確定的商業(yè)案例 42%不了解人工智能的應(yīng)用領(lǐng)域 39%缺乏相關(guān)技能 33%需要在數(shù)據(jù)管理平臺(tái)現(xiàn)代化方面先期投資 29%沒有相關(guān)預(yù)算 23%不確定人工智能系統(tǒng)應(yīng)用所需的條件 19%人工智能系統(tǒng)還不成熟 14%

弗雷斯特公司最后表示，人工智能當(dāng)前正在推動(dòng)面向客戶應(yīng)用加速轉(zhuǎn)型以及開發(fā)互聯(lián)的企業(yè)智能網(wǎng)絡(luò)，一旦企業(yè)克服了上述種種障礙，就能在該過(guò)程中獲益。 □