One cannot open up their computer or turn on their television for any significant amount of time without seeing or hearing about artificial intelligence. The term evokes an almost immediate emotional reaction, often with ideas of a dystopian future where the human race is no longer master of the planet. Without delving too deep into that rabbit hole, I would instead leave The Terminator and other equally bleak futures out of this particular conversation and instead focus on artificial intelligence and the law. The current application of artificial intelligence to the practice of law was a discussion topic at our most recent board of directors meeting for Loyola Law School. The discussion centered around the ability of a computer to perform a task or series of functions that had traditionally been the responsibility of a legal professional or team of professionals.

While AI can lift competition and productivity, it also can act as a great leveler, putting smaller players on the same footing as goliaths. Take pharmaceutical research, for example. Large companies have the budget and resources to physically test millions of drug candidates, giving them an advantage over startups and researchers. But smaller labs can achieve similar results by harnessing neural networks that simulate how a potential drug molecule will bind with a target protein. Deep learning can help smaller companies and other researchers discover promising drug treatments by improving the speed and accuracy of molecular docking, the process of computationally predicting how and how well a molecule binds with a protein.

I hate to be the bearer of bad news but today's AI is not as advanced as robo-graders want you to think. If someone you love depends on the SATs or GREs this should trouble you. A recent article by NPR discussed the use of computers to robo-grade essays in exams such as the SAT and GRE. Developers interviewed in the article claim that "computers are already doing jobs as complicated and as fraught as driving cars, detecting cancer, and carrying on conversations, they can certainly handle grading students' essays." According to AI researcher and Assistant Professor Zack Lipton at Carnegie Mellon University, "machine learning can find complex patterns, but all it's doing is discovering associations in the data. For a model to output reasonably correlated predictions, it will use whatever associations it can discover."

According to Hollywood, we are all just one short step away from living in a world run by computers. Artificial intelligence (AI) is advancing rapidly into territory that was previously in the realm of science fiction. Some see this future as a welcome utopia while others live in fear of life with Terminator- or Matrix-style outcomes. No matter which outcome you believe is most likely, the truth probably lies somewhere in between. You see, the biggest problem with computers is also their greatest advantage – they are programmed by humans.

Like many parents in the United States, Rob Glaser has been thinking a lot lately about how to keep his kids from getting shot in school. Specifically, he's been thinking of what he can do that doesn't involve getting into a nasty and endless battle over what he calls "the g-word." It's not that Glaser opposes gun control. A steady Democratic donor, Glaser founded the online streaming giant RealNetworks back in the 1990s as a vehicle for broadcasting left-leaning political views. It's just that any conversation about curbing gun rights in America tends to lead more to gridlock and finger-pointing than it does to action.

The user uses the control panel (A) to specify the detail information to visualize (e.g., level of detail, rule filters). The rule-based explanatory representation is visualized as a matrix (B), where each row represents a rule, and each column is a feature used in the rules. The user can also filter the data or use a customized input in the data filter (C) and navigate the filtered dataset in the data table (D). Abstract--With the growing adoption of machine learning techniques, there is a surge of research interest towards making machine learning systems more transparent and interpretable. Various visualizations have been developed to help model developers understand, diagnose, and refine machine learning models. However, a large number of potential but neglected users are the domain experts with little knowledge of machine learning but are expected to work with machine learning systems. In this paper, we present an interactive visualization technique to help users with little ...

Dutch universities are seeing significant growth in the number of students who want to study artificial intelligence in the coming academic year. At some educational institutions, the number of applications doubled compared to the current academic year. Interest in related courses, like data science and business analytics, is also on the rise, NOS reports.

Spark Notes is a recurring series about the lightbulb moments in sexual development. My parents were both readers, and they didn't let us watch that much TV. By the time I was 11, books had been my primary source of entertainment for as far back as my memory could go. Getting my adult library card in sixth grade was, in that context, a milestone of tremendous importance, a first moment of awe at being inducted into the grown-up world. Wandering into the adult stacks for the first time, I remember seeing the name Asimov in the "A" section in huge letters across dozens of titles, and taking two or three of them down to check them out.

A foundation in statistics is required to be effective as a machine learning practitioner. The book "All of Statistics" was written specifically to provide a foundation in probability and statistics for computer science undergraduates that may have an interest in data mining and machine learning. As such, it is often recommended as a book to machine learning practitioners interested in expanding their understanding of statistics. In this post, you will discover the book "All of Statistics", the topics it covers, and a reading list intended for machine learning practitioners. All of Statistics for Machine Learning Photo by Chris Sorge, some rights reserved.

In collaboration with more than 20 national universities, iFlytek launched its "Brain Science and Education" program on Saturday. The program will focus on the study of cognitive development of children, in a bid to explore new methods for individual learning and teaching. The domestic intelligent voice recognition technology company will invest more than 2 billion yuan ($299.03 million) in the program over the next 10 years. "I believe the program will be of great significance to the development of China's cognitive science and education industry," Liu Qingfeng, iFlytek's chairman, said at the launch event for the program, which was held in Beijing on Saturday. Liu also introduced some major breakthroughs the company achieved in the past year that would be applied to the new program.