The development of artificial intelligence (AI) has had a huge influence on today's society, as ongoing discussions evaluate the impacts of creating machines and computer systems that can react and perform like humans. These systems can process information in a more cognitive way, making them capable of more human-like functions like learning, decision-making, and visual perception. Hollywood portrayals of hyper-intelligent robots taking over the planet might make artificial intelligence seem intimidating, but there is a lot that can be gained by through these advanced computer systems. Without the element of human error, intelligent machines are capable of unmatched precision and accuracy, and since they don't require fundamental human needs like oxygen or food, they can perform tasks with far fewer limitations. In fact, AI is already popping up everywhere in our daily lives – through social media recommendations, virtual assistants on our smartphones, and even self-driving cars.

"May you live in Interesting times" widely known as a Chinese proverb, and ironically also referred to as a Chinese curse. Though no etymological trace has been found to its Chinese origin, it is used in an ironic sense, since historically "interesting times" are characterized by chaos, disruption and instability as opposed to peace, order and stability in uninteresting times:-) By that definition, ours is the cursed generation, since there has never been a more interesting time in the history of the human race than today, as we are being swept up slowly but surely in the wave of disruption that is impacting the human way of life. This disruption is visible in our work, our leisure, our consumption patterns, our relationships, and our cultural and social interactions. And this disruption is primarily driven by two but related factors. The first one- A near exponential reduction in cost of technology and the second- the convergence or coming together of various diverse technologies to drive rapid innovation at scale and at speed. The most widely talked about, predicted and feared development is Artificial Intelligence with Machine Learning- the ability of algorithms and systems to replicate human ability of "thinking", "Decision making" and "self learning" ( and soon consciousness) so as to eventually replace human beings across a large variety of jobs.

By 2020, medical data is expected to double every 73 days. With the rapidly growing amount of health data being produced, it is no surprise that medical knowledge is being drowned in the sea of scientific data. To make use of the incredible amounts of medical data, health professionals are increasingly turning to artificial intelligence (AI) to help find patterns in the deluge of data to provide better diagnostics and treatment. And now, the Chan Zuckerberg Initiative may speed progress in that area. The philanthropic arm of Facebook CEO Mark Zuckerberg and his wife Priscilla Chan has just purchased a Canadian healthcare startup, Meta, which uses AI to find, review and compile scientific papers. Meta is the Chan Zuckerberg Initiative's first outright acquisition and will be made free to use for all researchers.

Voice-based artificial intelligence assistants can understand human speech better than ever. But while AI can decipher our words and context to deliver fast results and actions, AI doesn't understand the tone, or one's feelings. Researchers from MIT set out to change that, creating a wearable that can detect the tone of a conversation. In the future, the tool might help people with anxiety or Asperger's syndrome better deal with stressful situations. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Institute of Medical Engineering and Science (IMES) published their findings on an AI-based wearable system that would correlate audio and vital-sign data to act as a social coach for the wearer.

This blog post is the result of my efforts to show to a coworker how to get the insights he needed by using the streaming capabilities and concise API of Apache Spark. In this blog post, you'll learn how to do some simple, yet very interesting analytics that will help you solve real problems by analyzing specific areas of a social network. Using a subset of a Twitter stream was the perfect choice to use in this demonstration, since it had everything we needed: an endless and continuous data source that was ready to be explored. Spark Streaming is very well explained here and in chapter 6 of the ebook "Getting Started with Apache Spark," so we are going to skip some of the details about the Streaming API and move on to setting up our app. Let's see how to prepare our app before doing anything else.

Phrases such as "machine learning" and "artificial intelligence" are thrown around so often by so many people, they risk becoming buzzwords along the lines of "Big Data." But unlike "Big Data," which was always a somewhat-nebulous term, "machine learning" is a definitive process that, when applied correctly, can result in some impressive feats. For instance, check out how Google used it to radically transform the sophistication of Google Translate, one of its core services. For those tech professionals who wish to break into machine learning and artificial intelligence, make no mistake about it: there's a lot of education and training involved. Google wants to make that journey a little easier, though, with a new three-hour course that offers a quick overview of deep-learning fundamentals.

A group of Chinese ophthalmologists and scientists developed a deep learning algorithm to identify congenital cataracts, a rare eye disease responsible for nearly 10 percent of all vision loss in children worldwide. The researchers suggest the algorithm would assist humans, instead of replacing them. "For doctors, technology is not sufficient to determine the best course of treatment with 100 percent certainty, and doctors should therefore make good use of the machine's suggestion to identify and prevent the potential misclassification and complement their own judgment," said study co-author Haotian Lin, a professor of ophthalmology at Sun Yat-sen University. "The results of our comparative analysis showed that both artificial intelligence and human intelligence have strengths and limitations." Using CUDA, TITAN X Pascal GPUs and the cuDNN-accelerated Caffe deep learning framework, the researchers algorithm was able to catch the disease with more than 90% accuracy.

Researchers at the Massachusetts Institute of Technology have developed wearable tech that could help avoid crossed wires and miscommunication. Using artificial intelligence to detect the "tone" of a conversation based on speech patterns, the researchers were able to use a wearable band to "classify the overall emotional nature of the subject's historic narration". More simply, the band could spot signs of sadness, anger, boredom and so on from a person's voice. The project, by Tuka AlHanai and Mohammad Mahdi Ghassemi at CSAIL, is one of many aimed at'social coaching' designed to help people with chronic social disorders become more comfortable with the complexities of communication. Day-to-day life is underpinned by social interactions that play a key role in our mental health and development.

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. The only necessary mathematical background is familiarity with elementary concepts of probability. The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes.

The world's best artificial intelligence poker player seems to know exactly when to hold'em and when to fold'em. An artificial-intelligence program known as Libratus has beat the world's absolute best human poker players in a 20-day No-Limit Texas Hold'em tournament, defeating four opponents by about $1.77 million in poker chips, according to Pittsburgh's Rivers Casino, where the "Brains vs. Artificial Intelligence" poker tournament was held. At the end of each day, at least one of the human players was beating the AI program. But in the end, it was not enough. "We appreciate their hard work, but unfortunately, the computer won," said Craig Clark, general manager of Rivers Casino.