Top 10 Hot Artificial Intelligence Technologies十大熱門人工智能技術

文/吉爾·普雷斯 譯/申軍

By Gil Press

人工智能技術市場蓬勃發(fā)展。相關宣傳不絕于耳，媒體關注度不斷提高，創(chuàng)業(yè)公司大量涌現(xiàn)，互聯(lián)網(wǎng)巨頭爭相收購人工智能領域初創(chuàng)公司，企業(yè)對人工智能的投資和應用程度也大幅增長。自動寫作科技公司去年進行了一項調(diào)查，發(fā)現(xiàn)已有38%的企業(yè)在使用人工智能技術，到2018年這一數(shù)字會增長到62%。弗雷斯特研究公司預計2017年人工智能投資將比2016年增長300%以上。國際數(shù)據(jù)公司估計人工智能市場將會從2016年的80億美元增長到2020年的超過470億美元。

人工智能一詞最早出現(xiàn)在1955年，當時用來命名計算機科學一個新的子學科，如今它囊括了多種技術和工具，有些經(jīng)過了時間考驗，有些還相對較新。為了讓人們了解該領域的各項熱點和冷門技術，弗雷斯特公司新近在科技雷達網(wǎng)站面向應用開發(fā)人員發(fā)布了一份關于人工智能的報告，詳細分析了企業(yè)應考慮用以支持人工決策的13種技術。

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，我認為下列10種技術是人工智能的熱點：

1.自然語言生成：從計算機數(shù)據(jù)生成文本。目前用于客戶服務、報告生成和總結商業(yè)智能情報。代表供應商有：艾特維奧數(shù)據(jù)公司、自動思維科技公司、劍橋語義數(shù)據(jù)公司、數(shù)碼邏輯研究公司、路希德公司、自動寫作科技公司、統(tǒng)計分析軟件公司、易奧普公司。

2.語音識別：將人類語言轉錄，生成可用于計算機應用程序的格式。目前用于交互式語音應答系統(tǒng)和移動終端應用。代表供應商有：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亞馬遜語音助手亞歷克薩的態(tài)度變化），從簡單的聊天機器人到高級人機交流系統(tǒng)都受到廣泛關注。目前用于客戶服務和支持以及管理智能家居。代表供應商有：亞馬遜、蘋果、人工智能服務公司、人工智能助手研究公司、虛擬創(chuàng)見公司、谷歌、國際商業(yè)機器公司、愛普軟件公司、微軟、賽第斯菲科技公司。

我們對月球表面的了解勝過對地球海底的了解，這一點令人震驚，但事實的確如此。我們對海底的了解大多來自科學大洋鉆探——從深海海底系統(tǒng)采集巖芯樣本。這一革命性技術始于50年前的1968年8月11日，當時在聯(lián)邦資助的深海鉆探項目中，“格洛馬爾挑戰(zhàn)者（Glomar Challenger）”號鉆探船首次遠征，駛入墨西哥灣。

4.機器學習平臺：提供算法、應用程序接口、開發(fā)和培訓工具包、數(shù)據(jù)，及計算能力，用于設計、訓練、實施模型，并將這些模型用于應用軟件、過程和其他機器上。目前在企業(yè)各種應用程序中廣泛使用，主要涉及預測或分類。代表供應商有：亞馬遜、福萊科特數(shù)據(jù)分析公司、谷歌、H2O智能平臺、微軟、統(tǒng)計分析軟件公司、天樹信息公司。

5.人工智能優(yōu)化的硬件：專門設計和架構的圖形處理單元和設備，可有效運行面向人工智能的計算任務。目前主要在深度學習應用上發(fā)揮作用。代表供應商有：阿魯維艾特公司、克雷研究公司、谷歌、國際商業(yè)機器公司、英特爾、英偉達。

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、培訓以及后續(xù)維護和調(diào)優(yōu)。這已是一種成熟的技術，廣泛在各種企業(yè)應用程序中使用，協(xié)助或執(zhí)行自動化決策。代表性供應商有：高級系統(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.深度學習平臺：一種由具有多個抽象層的人工神經(jīng)網(wǎng)絡組成的特殊類型機器學習。目前主要用于依托大型數(shù)據(jù)集進行的模式識別和應用分類。代表供應商有：深層本能、厄薩茨實驗室、暢德人工智能公司、數(shù)學研究公司、培勒塔瑞恩軟件公司、紅花科技、感知科技公司。

8.生物計量學：實現(xiàn)更自然的人機交際，包括但不限于圖像和指紋識別、言語和肢體語言。目前主要用于市場研究。代表供應商有：三維虛擬科技公司、阿凡客科技公司、洹藝科技、菲斯面部識別科技公司、森斯語音識別公司、鑫克拉科技公司、塔祖科技公司。

9.機器人過程自動化：使用腳本和其他方法自動執(zhí)行人為操作來支持高效的業(yè)務流程。目前用于人力成本高或效率低的任務或流程領域。代表供應商有：高級系統(tǒng)概念公司、全能自動化公司、藍棱鏡公司、創(chuàng)徑公司、融合科技公司。

10.文本分析和自然語言處理：自然語言處理通過統(tǒng)計和機器學習的方法，促進對句子結構、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和安全維護，各種自動化助理，以及挖掘非結構化數(shù)據(jù)的應用程序。代表供應商有：基礎科技公司、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、語言數(shù)字公司、清風思維公司、鑫諾克公司、斯圖飛騰公司、鑫奈科技公司。

今天，人工智能技術毫無疑問帶來了許多商業(yè)利益，但根據(jù)弗雷斯特公司去年進行的調(diào)查，人工智能在應用方面也面對著一些障礙，以下是對一些在人工智能領域沒有投資計劃的公司進行的調(diào)查統(tǒng)計。

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用領域 39%缺乏相關技能 33%需要在數(shù)據(jù)管理平臺現(xiàn)代化方面先期投資 29%沒有相關預算 23%不確定人工智能系統(tǒng)應用所需的條件 19%人工智能系統(tǒng)還不成熟 14%

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