He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

Leading provider of aerial imagery and data analytics expands data extraction capabilities for local government, insurance and infrastructure sectors. Bothell, WA (April 26, 2017) – EagleView, the leading provider of aerial imagery and data analytics for government and commercial industries, is proud to announce the acquisition of OmniEarth, developer of machine learning technologies and decision-making tools for the water resource management, energy and insurance markets. With this acquisition, EagleView gains OmniEarth's machine learning capabilities, resulting in higher accuracy and precision of existing automated datasets. OmniEarth's ability to extract data from geospatial imagery will enhance EagleView's property reports and Pictometry imagery classification of land areas such as impervious surfaces or irrigated farmland. It will also better identify roof shape and condition, tree overhang, decks, pools and other notable property features.

IBM's Watson may be most famous for winning at the game show "Jeopardy!" In a room at IBM offices, software developers and business customers can query the famous computer and see a demonstration of its work as a research partner in fields ranging from land use to medicine. The room itself has a display wall on one side and a touch screen in the center and near the window. In a recent demonstration of how the machine approaches search queries, Rachel Liddell, a "Watson Experience Leader," used the central touch screen to search through a series of TED talks. As she touched the screen to look up lectures on human psychology, Watson created a set of associated topics, such as "education," and touching one of those words generated more specific topics that appeared in the talk.

He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

Using that information, water authorities or companies can target areas or homes where people are wasting water, and send specialized educational materials to let people know how they can cut down on water waste. Some of OmniEarth's customers have already started seeing results, with some reporting a 15 percent reduction in water use, just by using the conservation messages. Many people, Fentzke said, may not even realize that they're wasting water. There could be bad meters, leaks, or bad settings on automatic sprinkling systems that are contributing to the problem. "We've found it to be very effective in targeting people who may not even know that they're inefficient," Fentzke said.

It's a lightning-fast learner, speaks eight languages and is considered an expert in multiple fields. It's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, it's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was created back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

To get information about water use, Watson uses "visual recognition" to scan images of land parcels for valuable information, according to Pesenti. But unlike less-powerful image detection software, Watson doesn't just identify a specific object -- say, a crop field -- in an image. Instead, it combs through lots and lots of information about the image -- like the objects it contains and the colors of those objects -- and uses that information to "understand" the image as a whole. In the case of OmniEarth, researchers can use Watson not just to determine if a given parcel of land contains a crop field, but also to calculate the exact amount of water used by that parcel based on all of the information contained in the photo. What's more, Watson doesn't need to know much about water consumption to tell OmniEarth if people are using too much water.