If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Lack of explainability of decisions made by Artificial Intelligence (AI) programs is a major problem. This inability to understand how AI does what it does also stops it from being deployed in areas such as law, healthcare and within enterprises that handle sensitive customer data. Understanding how data is handled, and how AI has reached a certain decision, is even more important in the context of recent data protection regulation, especially GDPR, that heavily penalizes companies who cannot provide an explanation and record as to how a decision has been reached (whether by a human or computer).
One must know about the various techniques to make predictions in machine learning by Spark. Supervised learning is to direct the data towards a specific label by training a certain set of unlabelled dataset. It is used to classify data- for example spam filtering or image recognition. Unsupervised learning is used for clustering data based on certain similar features in the set of unlabelled data. This is used to predict purchase patterns of customers on sites like Amazon and also for applications on social networking sites.
Artificial intelligence and the internet of things are changing the way we watch and play golf. While you might not recognize the changes the next time you watch a PGA Tour tournament, you will likely appreciate the improved entertainment value. For those weekend duffers among us, hopefully, the tech will help us finally perfect our golf games. Televising golf tournaments has always presented a challenge since there is action happening concurrently at 18 holes. Broadcasters need data at their fingertips and an easier way to connect the dots and to see the patterns the data is revealing.
The automobile industry has never taken a break from innovating since the debut of the Motorwagen, the world's first car. Automakers are continuously attempting to make their vehicles faster, safer, and more comfortable. To make driving more comfortable car manufacturers looked to automation technologies to make driving less tedious. To start with, (Level 1) automation enhanced the quality of driving using technologies like cruise control. Taking things a step further, cars began to feature assisted steering and acceleration (Level 2).
Robert Bosch Venture Capital GmbH (RBVC), the venture capital arm of global automotive parts supplier Bosch Group, has completed an investment in mapping startup DeepMap Inc, a start-up based in Palo Alto, California that is building high definition maps specifically for self-driving vehicles. DeepMap is focused on solving the mapping and localization challenge for autonomous vehicles. The investment amount was not disclosed. "Maps explicitly designed to be read by machines are a critical enabling technology for safe autonomy. DeepMap fills a vacuum in the market.
While many companies are turning to machine learning tools to fight hackers, they may not be as helpful as they seem thanks to a talent shortage and a lack of transparency. By the end of 2017, some 61% of businesses had implemented artificial intelligence (AI) into their organizations--a 23% jump from the previous year, according to Narrative Science. And the incorporation of AI into business will only rise: The number of medium and large enterprises using machine learning is predicted to double by the end of 2018, said Deloitte. Machine learning is a form of AI that interprets massive amounts of data, applying algorithms to the material, and making predictions off its observations. Common technologies that employ machine learning include facial recognition, speech recognition, translation services, and object recognition.
Automakers, insurers, and related partners see a big role for blockchain. What will change in the realms of payments, insurance, security, and safety? When it comes to cars and blockchain, no one has all the answers yet. But there is plenty to prepare for and think about – not only in the auto industry but also in related industries such as insurance. First things first: While we have found interesting examples of blockchain in action, most companies and industries remain in an early stage of exploration and adoption.
The announcement Wednesday that Anthem is supporting a 12-month trial by doc.ai and Harvard Medical School researchers to examine whether artificial intelligence can improve patient outcomes is the latest effort by the health insurance industry in the AI space. Financial terms of the partnership weren't disclosed. "Anthem is focused on leading our industry in the safe and responsible use of artificial intelligence and emerging technologies to create a better healthcare future for all Americans," Anthem CEO Gail Boudreaux said in a statement. "We are pleased to partner with doc.ai on this innovative study that can have near-term benefit for our employees and, longer-term, the potential to redefine how we treat disease and manage chronic medical conditions to achieve better personalized health outcomes." Some see the health insurance industry's shift to value-based care and population health and a greater acceptance of machines to help deliver medical care to patients will help turn artificial intelligence into a multi-billion-dollar market.