Applications of the trend
-Information gathering and searching. Knowledge workers in our data-Driven economy often spend a huge amount of time and effort gathering data. Developments in natural language processing and contextual understanding
Are finally making machines able to search information and uncover patterns
And relationships, all at superhuman speed and efficiency.
clearwell, based in silicon valley, analyzes documents for pretrial discovery-
the process of finding relevant information to use in a trial, which of the requires
combing through thousands or millions of documents. It recently analyzed
more than half a million legal documents in less than three days for a client—a
process than earlier took large teams of lawyers several weeks. Social madia
tools help enterprises with wide networks track product reviews and customer
thousands of relevant posts daily but possible with automated algorithms that
look for patterns and can distinguish between tones in posts.
-Automating communication. Many jobs that have traditionally involved humans understanding other humans and communicating with them are now getting automated as machines become better at understanding language and processing speech. The Canadian Automobile Association of Saskatchewan now uses computers to answer calls from motorists and dispatch roadside assistance, saving 60 to 80 percent in cost per call compared with an outsourced call center and cutting transaction time in half. Translation apps, integrated into smartphones and Web browsers, can instantly translate entire Web pages and could soon allow tourists to “speak” the local language by talking into their apps
-Problem-solving expertise. Advances in big data analytics and deep learning (programs that mimic how the human brain discerns patterns among objects, sounds, or other kinds of information) now make it possible for machines to process huge data sets and high-volume data feeds in near real time and see patterns the human brain cannot. IBM’s Watson computer achieved fame by beating human champions in the TV quiz program “Jeopardy!” Now, IBM has teamed up with oncologists at Memorial Sloan-Kettering Cancer Center in New York to develop a decision-support application for cancer diagnosis and treatment using Watson. The application has “trained” on 600,000 medical evidence reports and 1.5 million patient records and clinical trial reports and is continuously learning from the latest medical research and cases.
-Personal assistants. Machines are now being employed as assistants to users, sometimes even before they know they need it. Apple’s Siri digital assistant can take in voice queries and return search results, look up the weather, make calls, or offer a choice of nearby restaurants. Google Now attempts to second-guess the user based on behavior and context and preemptively provide information—flight details on reaching the airport, traffic conditions when leaving home in the morning, and even nearby photo spots.
Applications of the trend-Information gathering and searching. Knowledge workers in our data-Driven economy often spend a huge amount of time and effort gathering data. Developments in natural language processing and contextual understandingAre finally making machines able to search information and uncover patternsAnd relationships, all at superhuman speed and efficiency.clearwell, based in silicon valley, analyzes documents for pretrial discovery-the process of finding relevant information to use in a trial, which of the requirescombing through thousands or millions of documents. It recently analyzedmore than half a million legal documents in less than three days for a client—aprocess than earlier took large teams of lawyers several weeks. Social madiatools help enterprises with wide networks track product reviews and customerthousands of relevant posts daily but possible with automated algorithms thatlook for patterns and can distinguish between tones in posts.-Automating communication. Many jobs that have traditionally involved humans understanding other humans and communicating with them are now getting automated as machines become better at understanding language and processing speech. The Canadian Automobile Association of Saskatchewan now uses computers to answer calls from motorists and dispatch roadside assistance, saving 60 to 80 percent in cost per call compared with an outsourced call center and cutting transaction time in half. Translation apps, integrated into smartphones and Web browsers, can instantly translate entire Web pages and could soon allow tourists to “speak” the local language by talking into their apps-Problem-solving expertise. Advances in big data analytics and deep learning (programs that mimic how the human brain discerns patterns among objects, sounds, or other kinds of information) now make it possible for machines to process huge data sets and high-volume data feeds in near real time and see patterns the human brain cannot. IBM’s Watson computer achieved fame by beating human champions in the TV quiz program “Jeopardy!” Now, IBM has teamed up with oncologists at Memorial Sloan-Kettering Cancer Center in New York to develop a decision-support application for cancer diagnosis and treatment using Watson. The application has “trained” on 600,000 medical evidence reports and 1.5 million patient records and clinical trial reports and is continuously learning from the latest medical research and cases.-Personal assistants. Machines are now being employed as assistants to users, sometimes even before they know they need it. Apple’s Siri digital assistant can take in voice queries and return search results, look up the weather, make calls, or offer a choice of nearby restaurants. Google Now attempts to second-guess the user based on behavior and context and preemptively provide information—flight details on reaching the airport, traffic conditions when leaving home in the morning, and even nearby photo spots.
การแปล กรุณารอสักครู่..
