We are already using functional programming using Scala with the previous blog series of Self-Learn Yourself Scala in 21 Blogs (#1, #2, #3). Let's start with defining functional programming which is a programming paradigm that models computation as the evaluation of expressions and expressions are built using functions that don't have mutable state and side effects. But any guess how old is functional programming; you don't believe it's started around 1930 when the lambda calculus introduced. And now the lambda calculus is a formal mathematical system to investigate functions, function apps, and function recursion. At first glance it may seem odd to compare oop and functional programming at a pure versus impure level.

Without this change, the answer to the essay's title question arguably is'no' – with it, the answer plausibly becomes'maybe'. Either outcome holds very interesting implications for nurses.

Researchers from MIT's Computer Science and Artificial Laboratory (CSAIL) alongside machine learning-startup PatternEx have created a new cybersecurity defense system that makes use of both unsupervised and supervised learning methods. Human analysts are then presented with the data and given an opportunity to identify actual attacks, which are then fed back into the machine. The system learns and refines its accuracy over time. CSAIL research scientist Kalyan Veeramachaneni, one of AI,2's co-creators, described it this way: "The more attacks the system detects, the more analyst feedback it receives, which, in turn, improves the accuracy of future predictions. That human-machine interaction creates a beautiful, cascading effect."

Poachers have a new enemy: artificial intelligence. Scientists have developed an AI system that can continuously learn and adapt to illegal activities and help rangers move swiftly to protect endangered animals in the wild. Researchers are using artificial intelligence (AI) to solve increasing poaching activities, applying computer science and game theory to lead the innovation to outwit poachers in the wild. A team of scientists have successfully created an AI system that "learns" information and uses data to map out ranger patrols that are most effective in protecting endangered animals living in the wild. These ranger patrols are still the most direct wildlife protection methods against poachers.

Artificial Intelligence seems to be everywhere at the moment. Massive tech companies are spending vast amounts of money on research and development of ever more sophisticated AI-focused tools, services and other assorted products. News outlets give a huge amount of coverage to events in which AI is the star of the show. Perhaps most importantly, AI is being discussed more by the public at large. Yet for the vast majority of people, AI is a nebulous area.

Skytree – The Machine Learning Company is disrupting the Advanced Analytics market with our enterprise-grade machine-learning platform that gives organizations the power to discover deep analytic insights, predict future trends, make recommendations and reveal untapped markets and customers. Skytree's mission is to bring the power of state-of-the-art machine learning to everyone: including data scientists, developers and non-experts alike. The Skytree machine-learning platform is built for speed and scalability, allowing users to build the most accurate machine-learning models, faster. Skytree machine-learning software delivers an end-to-end model building experience, from data preparation to model creation and deployment. Skytree automates the machine learning model-building process, saving you time.

IBM's California research lab sits atop a green hill in Almaden, 15 miles south of downtown San Jose. There aren't any signs that suggest if you drive up the narrow road that wraps around the hill you'll find a research facility at the top. No signs that the research center is home to a Fortune 500 company. No signs -- even inside -- that the company once dominated the personal computer industry. After decades in the spotlight as a hardware-centric firm selling PCs, servers and mainframes, the 105-year-old tech giant has made a dramatic shift into a realm that few understand: cognitive computing.

Artificial intelligence (AI) is all around us. Unlike the Terminator robots, AI exists in subtle ways, embedded in our daily activities thanks to the rise of big data and machine learning. When Facebook tries to connect users with new friends or businesses, Netflix suggests a new TV series to watch, or Amazon recommends a book, these are all examples of AI presented to people via machine learning – a statistical method that finds patterns and makes predictions based on vast volumes of data. After years of hype, most organisations now have a solid understanding of the potential of big data. In fact, the majority of them are actively pursuing means to capitalise on all the information they capture.

For the third time, we present another round of incredible deep learning applications! Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_c... The thumbnail image background was created by Steven S. (CC BY 2.0) - https://flic.kr/p/sdUQ7

Another self-driving car startup is about to hit the roads. The Wall Street Journal reports that Drive.ai, a Silicon Valley startup that received 12 million in funding last year, has been granted a license to test autonomous vehicles on California roads. It's the 13th company to receive permission. Rather than programming a car so that it knows exactly what to do, Drive.ai That means, like a human, the more time it spends driving and the more scenarios it encounters, the better it'll get at responding to them.