从Siri看下一代智能系统的变革与商机

上网时间: 2011年11月10日? 作者:R. Colin Johnson? 我来评论 【字号: ? ?小】

关键字:iPhone-4S Siri? 智能系统?

In a smart-system world, data’s ‘the new currency’

R. Colin Johnson

We give them human names—Watson, Siri—that suggest how much “like us” they are. Today’s smart systems can intuitively handle tasks that until now have been impossible to automate in real-time. And by mining the resultant sea of real-time data coming in from billions of streams worldwide, analytics science is creating services that have even more value than the smart systems themselves.

IBM’s Watson supercomputer captured the public’s attention earlier this year when it beat human champions at Jeopardy. Siri, the intelligent agent on the Apple iPhone-4s, answers users’ ad hoc questions about almost anything in natural, conversational English, putting a scary-smart system in the pocket of anyone who can afford the phone.

While those systems get the glory, there’s a seething mass of smart systems already at work in virtually every electronics sector: automotive, industrial, communications, computing, transportation, energy, medical and personal health maintenance. In fact, according to the U.S. President’s Council of Advisors on Science and Technology, such “cyber-physical systems” will eventually constitute 50 percent of all electronics worldwide, making them a U.S. strategic asset.

In response, the National Institute of Standards and Technology recently announced a standardization effort to define interfaces for interoperability, as well as metrics and methods for measuring and comparing performance among smart systems. Such efforts set the stage for U.S. entrepreneurs to build successful smart systems from homegrown designs, but to realize those designs with electronics that are manufactured at low cost overseas (see sidebar, final page).

The stakes are huge. Market watcher International Data Corp. (Framingham, Mass.) recently reported that nearly 2 billion smart systems per year are already being sold, making for a $1 trillion market that IDC predicts will grow to 4 billion units and $2 trillion by 2015.

The most valuable services performed by smart systems, according to IDC, result from the application of analytics to real-time data streams.

“Data is the new currency,” said Mario Morales, vice president of semiconductor research at IDC. “And the companies that understand this are the ones already developing the analytics and infrastructure to extract that value—companies like IBM, HP, Intel, Microsoft, TI, Freescale and Oracle.

“Over the last three years, we have seen a transformation not merely in computing, but also in networking, and even in the way users are interacting with smart devices. Enterprises have yet to figure out exactly how to monetize all this data, but there is a tremendous amount of opportunity there, which is prompting visionaries to make huge investments in the analytics software and services that will couple to their intelligent hardware.”

IDC has been covering embedded computers for over a decade but only recently started delineating “intelligent systems” as the successor to the embedded space. And IDC is not the only market forecaster claiming that smart systems are the future. Applied Business Intelligence Inc. (New York), for one, recently started a “smart cities and grids” research service.

IBM ahead of curve

IBM probably has the deepest understanding of smart systems today. Dozens of its so-called smarter-planet systems are already solving widespread infrastructure problems worldwide, including a smart transportation system in Stockholm, Sweden; a national smart grid—the world’s first—in Malta; and a smart wireless sensor network that protects paintings at the New York Metropolitan Museum of Art.

“Smart systems are generating eight times more data every day than there is in all the U.S. libraries combined—85 percent of which is unstructured,” said Jai Menon, IBM fellow, chief technology officer and vice president of technical strategy for the company’s systems group. “Business intelligence has the problem of using analytics to derive value from all that unstructured data, and Watson is a good example of how to answer questions about unstructured data very quickly.”

Traditional IT analytics were run on structured data that was carefully tailored by database experts into neat, isomorphic containers that could be easily searched, sorted and analyzed using well-known mathematical formulas. But Watson proved that messy, unstructured data can also be easily searched, by virtue of cleverly crafted analytics designed to run on optimized system architectures that preposition the technological capabilities needed to address specific unstructured problem domains.

“Analytics for the financial markets—such as predicting commodity prices—is a cyclical phenomenon driven by well-known patterns. But predicting the risk of failure in infrastructure—say, how long a water pipe will last—is what we call an unstructured problem,” said Arun Hampapur, distinguished engineer and director of business analytics at IBM Research. “And analytics for unstructured problems is best done by instrumenting a strategy that custom-tailors the analytics and architecture for a particular problem domain.”

IBM’s latest foray into addressing unstructured problem domains with smart systems is aimed at using Watson to create automated advisers for apps in health care, banking and finance, retailing, law and governmental regulation. “We get calls every day from industry leaders who want to repurpose Watson for new applications, such as helping to make airline reservations faster, better, easier,” said Hampapur.

For instance, Wellpoint Inc. (Indianapolis), the nation’s largest health-care provider, recently announced that it would use a Watson-derived smart system to simplify and speed medical diagnoses by matching patients’ symptom sets with data from millions of medical records, journal articles and late-breaking medical-research results.

Watson is based on technologies that IBM created to solve unstructured problems in smart-city projects. IBM started its quest for such smart systems by leveraging its strengths in the data center, where traditional analytics are run. But it has been steadily working out toward the edge of the connectivity network, where analytics can be run on the embedded processors themselves. Menon noted that Chicago police “use smart analytics at the edge to automatically turn surveillance cameras toward a gunshot, so that by the time the 911 call comes in they already have a readout of the caliber of gun that was used and a camera pointing at the location from which it was fired.”

IBM has spent more than $15 billion in the past few years acquiring companies with specialized analytics expertise, and it is building a new generation of cognitive-computer chips for smarter systems that can fuse the inputs from multiple sensors.

HP sees 'the same opportunities'

Hewlett-Packard, meanwhile, is transforming its business model to deliver smart systems that harness wireless sensor networks in order to communicate vast streams of real-time data to HP’s cloud-based servers, where analytics can be run to predict everything from public power outages to personal heart attacks.

“We are not explicitly trying to emulate IBM, but we are finding the same type of opportunities as they are, because it’s clear that more and more of the value is in the system as a whole,” said senior HP fellow Stanley Williams. “The money will be in the analytics, because analytics is what turns ones and zeros into something meaningful; it creates the knowledge and awareness that allows people to quickly react to situations, and to prevent undesirable outcomes.”

In creating its first generation of smart systems, HP is focusing on just two sectors—energy and health—for which it is building systems from scratch, from the sensor chips to the analytics software running in the cloud.

“Smart systems represent a huge development effort, involving every aspect of information technology, but we have consciously decided to only enter two sectors with our first vertically integrated platform,” said Williams. “We wanted to enter at least two so that we could compare and contrast the different applications in order to understand what

is common and what needs to be different. Then, once we have those two under our belt, we’ll look to the other vertical market segments.”

HP is prototyping its first widescale applications in cooperation with customers such as Shell Oil, which has contracted for a wireless sensor network that can perform smart seismic imaging. Analytics run on HP servers will turn data streams from thousands of HP seismic sensors into practical intelligence indicating where to drill.

HP manufactures both a specialized MEMS accelerometer for seismic sensing and a wireless sensor node that streams the sensor data back to its servers, where analytics are run.

Intel takes the local

Intel Corp., for its part, is pursuing a smart-systems business that adds local analytics as the natural evolution from the embedded model, focusing on software that lets OEMs perform analytics on Intel X86 and Atom processors instead of diverting raw data streams up to the cloud.

“As sensors become more pervasive, embedded systems have begun creating large volumes of data that today flow straight into the cloud,” said Ton Steenman, vice president and general manager of Intel’s Embedded Communications Group. “We believe that it is unreasonable to think that everything should move to the cloud; in fact, we advise that any problems needing real-time analytics should be run on the embedded processor itself.”

Intel last year acquired CognoVision Solutions Inc. (Toronto) for that company’s anonymous video analytics (AVA) technology, which runs on X86 processors, and branded the technology the Intel Audience Impression Metrics Suite. AIM runs locally on digital signage and changes the ads displayed depending on who is viewing them.

“Digital signs in the past were just media players with a low-end processor that passed through a media stream to the sign,” said Steenman. “But now that cameras have been added, smart analytics running locally can recognize gender and age, then change the advertisement on the sign to match the viewer.”

Intel also recently acquired security powerhouse McAfee and embedded OS specialist Wind River. Those acquisitions now are collaborating to use Intel’s remote management tools to extend PC-like security strategies down to smart embedded systems.

Intel's digital signs offer consumers interactive displays—here of Adidas shoes—while using local analytics to ascertain and send data about users’ gender, age and interests to cloud servers.


[ 投票数:? ] 收藏 ??? 打印版 ??? 推荐给同仁 ??? 发送查询 ??? ?订阅杂志

评论
免费订阅资讯速递
信息速递-请选择您感兴趣的技术领域:
  • 安防监控
  • 便携设备
  • 消费电子
  • 通信与网络
  • 分销与服务
  • 制造与测试
  • 工业与医疗
  • 汽车电子
  • 计算机与OA
  • 电源管理
  • 无源器件与模组
  • 新能源
  • 供应链管理
论坛速递
相关信息
  • 什么是iPhone-4S Siri?
  • 国际电子商情提供相关iPhone-4S Siri技术文章及相关iPhone-4S Siri新闻趋势,及更新最新相关iPhone-4S Siri电子产品技术

  • 什么是智能系统?
  • 国际电子商情提供相关智能系统技术文章及相关智能系统新闻趋势,及更新最新相关智能系统电子产品技术

?新浪微博推荐
Global Sources


编辑推荐
?大家正在说


打开微信“扫一扫”,打开网页后点击屏幕右上角分享按钮

1.扫描左侧二维码
2.点击右上角的分享按钮
3.选择分享给朋友
电子元器件数据手册下载
数据手册搜索

Datasheets China.com

《汽车电子特刊》

汽车电子系统在现代的汽车中占有的比重越来越高,对产品设计的工程师来说,产品的设计和验证面临着很多的挑战。本期《汽车电子特刊》将会向您呈现ADI技术对于汽车电子行业的应用等,还有IIC汽车电子论坛的精彩回顾哦!

扫一扫,关注最新资讯

esmc