The Artificial Intelligence (AI) market is booming, with nearly every major player in the enterprise space vying for a foothold. IBM, Amazon, GE, Microsoft, Google, Cisco, SAP, HPE, Verizon--you name it, anybody and everybody, even folks who used to sell hardware--are actively working on and/or want to stake a claim in a piece of the AI pie. What encompasses the AI market? Machine learning, natural language processing (NLP), voice recognition and image processing, application and geography are what we're looking at, with mobile devices and cloud being the enablers. And just what will the AI market be?

Natural disasters are out of the reach and influence of human beings. However, a lot can be done to minimize loss of lives. Artificial intelligence is one viable option that can potentially prevent massive loss of lives while at the same time make rescue efforts easy and efficient. To learn more, checkout the infographic below created by Eastern Kentucky University's Online Masters in Safety degree program. In the period between 2005 and 2015, a total of 242 natural disasters occurred in the United States of America.

Machine Learning is a subfield of computer science by which computers have the ability to learn without being explicitly programmed. Machine learning is a method used to develop complex models and algorithms that lend themselves to prediction. Machine learning is deployed where the system deals with large scale of data. Deployments of machine learning leads to improved speed and accuracy of the functions performed by the system. Machine learning is majorly deployed for solving classification and regression problems.

During its wheeled treks on the Red Planet, NASA's Spirit rover may have encountered a potential signature of past life on Mars, report scientists at Arizona State University (ASU). To help make their case, the researchers have contrasted Spirit's study of "Home Plate" -- a plateau of layered rocks that the robot explored during the early part of its third year on Mars -- with features found within active hot spring/geyser discharge channels at a site in northern Chile called El Tatio. The work has resulted in a provocative paper: "Silica deposits on Mars with features resembling hot spring biosignatures at El Tatio in Chile." As reported online last week in the journal Nature Communications, field work in Chile by the ASU team -- Steven Ruff and Jack Farmer of the university's School of Earth and Space Exploration -- shows that the nodular and digitate silica structures at El Tatio that most closely resemble those on Mars include complex sedimentary structures produced by a combination of biotic and abiotic processes. "Although fully abiotic processes are not ruled out for the Martian silica structures, they satisfy an a priori definition of potential biosignatures," the researchers wrote in the study.

Employees of Datatonic, a Europe-based data analytics consultancy, recently participated in a week-long hackathon ("Data in Motion Hack Week") organized by Traffic for London (TfL), that city's official transport authority. As you might expect, the goals of the hackathon included stimulating developer creativity to overcome, through innovative use of public-cloud infrastructure and open data, high-priority TfL challenges such as limited overall transport capacity, endemic road congestion and air-quality degradation. Most of the other teams chose to focus on data mashups or visualizations to give London residents information for making better route decisions during their commutes. The Datatonic hackers, in contrast, looked to machine learning (ML). By augmenting real-time data visualization with an ML model, they found they could predict areas of congestion during the morning and evening commutes, which currently stand at 30 million daily journeys, and more than 1 million net-new journeys expected by 2018.

New analytics engine for users allows anyone to receive fast, accurate imaging analysis for key clinical conditions, by simply uploading their scans to Zebra's online system Zebra Medical Vision (https://www.zebra-med.com/), the leading machine learning imaging analytics company, is launching Profound (http://profound.zebra-med.com) The company's new service allows people to upload their medical imaging scans such as CTs and Mammograms to Zebra's online service, and receive an automated analysis for key clinical conditions. This Smart News Release features multimedia. "We are all anxious about our health. Undergoing an imaging scan such as a CT or a Mammogram is stressful for many people, often compounded by a long wait for results, with additional follow-up tests and examinations." said Elad Benjamin, co-founder and CEO of Zebra Medical Vision.

Passengers embark on the U.S. side of the last hand-pulled ferry at Los Ebanos, Texas on the Mexico-U.S. border in 2008. LOS EBANOS, Texas -- All along the winding Rio Grande, the people who live in this bustling, fertile region where the U.S. border meets the Gulf of Mexico never quite understood how Donald Trump's great wall could ever be much more than campaign rhetoric. Erecting a concrete barrier across the entire 1,954-mile frontier with Mexico, they know, collides head-on with multiple realities: the geology of the river valley, fierce local resistance and the immense cost. An electronically fortified "virtual wall" with surveillance technology that includes night-and-day video cameras, tethered observation balloons and high-flying drones makes a lot more sense to people here. If a 30- to 40-foot concrete wall is a panacea for illegal immigration, as Trump insisted during the campaign, the locals are not convinced.

Airbus's vision for driverless flying taxis is one step closer to becoming a reality. MTSI and SOAR Oregon have been jointly awarded a'Flight Test and Range' to test the single seater self-piloted flying vehicle that can carry both cargo and human passengers. Airbus's innovation division, A³, unveiled plans for'Project Vahana' earlier this year, and says it hopes to have a full-sized prototype in the air by the end of 2017 and a model for sale on the market by 2020. Airbus's innovation division, A³, previously unveiled plans for'Project Vahana', which aims to have a full-sized prototype in the air by the end of 2017 and a model for sale on the market by 2020. Project Vahana began earlier this year and is one of the first projects at A³, the advanced projects and partnerships outpost of Airbus Group in Silicon Valley. The first conceptual renders have been revealed showing a sleek self-flying aircraft with room for one passenger who sits under a canopy that retracts similar to a motorcycle helmet visor.

The issue of robotics, artificial intelligence, and their impact on companies, economies, and society as a whole is one in which S&P Global takes great interest. I attended a recent forum on the issue sponsored by the Council on Foreign Relations in New York, and published this overview on S&P Global's Global Credit Portal. Robots aren't here to take your job. Not yet, anyway, according to experts in the field of robotics and artificial intelligence (AI) who spoke at a conference sponsored by the Council on Foreign Relations in New York. Robotics and AI have tremendous disruptive potential and positive economic contributions to make, but the elimination of vast numbers of jobs as a result--in a relatively short time--may not be on the immediate horizon, speakers at the Nov. 14 session said. Inevitably, such a discussion turns quickly from the broad concepts of AI and robotics to a more specific application: autonomous cars.

The U.S. State Department generates some two billion e-mails every year. A significant fraction of these contain sensitive or secret information and so have to be classified, a process that is time-consuming and costly. In 2015 alone, it spent $16 billion to protect classified information. But the reliability of this process of classification is unclear. Nobody knows whether the rules for classifying information are applied consistently and reliably.