A majority of people are skeptical of the government adopting artificial intelligence tools to manage its citizen services, but more men than women say they are comfortable with the technological shift, according to a new survey. In a report published by Accenture, one-third of men said they trusted AI to manage their health care, while only 20 percent of women felt the same way. Though the gender gap was widest for health care, researchers found that in six different categories of citizen services, men trusted A.I. technology more than women did. The online survey was conducted by McGuire Research Services in January 2017 and included 500 people living in the Washington, D.C., metropolitan area. Though agencies have already begun delegating some of their repetitive tasks to artificial intelligence, the overall results show a sizable portion of the public distrusts the use of such tools in government services that directly involve citizens. Both genders felt roughly the same about using AI to register to vote, with 46 percent of men and 45 percent of women saying they trusted such government tools.

Wondering what Artificial Intelligence, or AI, is all about? Where does data science leave off? And where and how does machine learning apply? AI will likely define the next generation of software. Given all the talk and confusing terminology out there, we've got the perfect overview course for those of you who are just getting started.

Many people find mathematics daunting. If true, this piece is for you. If not, this piece is still for you. What do you think of when you think about mathematics? Perhaps you think about x's and y's, intractable fractions, or nonsensical word problems.

Five years ago, in 2012, I decided to experiment in improving my teaching by creating a flipped classroom (and semi-MOOC) for my course "Business Analytics Using Data Mining" (BADM) at the Indian School of Business. I initially designed the course at University of Maryland's Smith School of Business in 2005 and taught it until 2010. When I joined ISB in 2011 I started teaching multiple sections of BADM (which was started by Ravi Bapna in 2006), and the course was fast growing in popularity. Repeating the same lectures in multiple course sections made me realize it was time for scale! I therefore created 30 videos, covering various supervised methods (k-NN, linear and logistic regression, trees, naive Bayes, etc.) and unsupervised methods (principal components analysis, clustering, association rules), as well as important principles such as performance evaluation, the notion of a holdout set, and more.

Summer is not without its annoyances -- mosquitos, wasps, and ants, to name a few. As the cool breeze of September pushes us back to work, labs across the country are reconvening tackling nature's hardest problems. Sometimes forces that seem diametrically opposed come together in beautiful ways, like robotics infused into living organisms. This past summer, researchers at Harvard and Arizona State University collaborated on successfully turning living E. Coli bacteria into a cellular robot, called a "ribocomputer." By taking archived footage of movies, the Harvard scientists were able to successfully store the digital content on the bacteria that is most famous for making Chipotle customers violently ill.

This tutorial is based on the Neural Network Module, available on ATOMS. This Neural Network Module is based on the book "Neural Network Design" book by Martin T. Hagan. A function is implemented in neural network module to simplify the plotting of 2 groups of data points. First, we split the data to the source (P), and target (T). We transpose the data to match the format required by the module.

A Chicago startup has raised $2.5 million in hopes of using artificial intelligence and Big Data to help insurance companies make smarter underwriting decisions more quickly. DataCubes raised the money from Seyen Capital and MK Capital. The company was founded last year by Kuldeep Malik, a co-founder of mobile-advertising software company Persio (formerly called Iris Mobile), and Harish Neelamana, who previously worked for insurers Zurich and Allstate. "I wanted to create a Big Data solution to solve a tangible business problem; my friend Harish is an expert in commercial insurance," Malik says. They're trying to disrupt the commercial insurance business by using artificial intelligence and machine learning.

A Stanford University expert has claimed that computer programmes will soon be able to guess your political leaning and IQ based on photos of your face. Dr Michal Kosinski went viral last week after publishing research suggesting artificial intelligence (AI) can tell whether someone is straight or gay based on photos. Now the psychologist and data scientist has claimed that sexual orientation is one of many character traits the AI will be able to detect in the coming years. Stanford researcher Dr Michal Kosinski went viral last week after publishing research (pictured) suggesting AI can tell whether someone is straight or gay based on photos. AI-powered computer programmes can learn how to determine certain traits by being shown a number of faces in a process known as'training'.

A 52 million-year-old ankle fossil dug up in France shows the first primates were high flying acrobats in a find that could rewrite human history. The shape and size of the tiny bone suggests our earliest ancestors flexed and sharply extended their ankles to launch themselves into the air. For years, scientists believed the ancestors of today's humans, monkeys and apes were relatively slow and deliberate. But the new study found the first primates, which were about the size of a chipmunk, instead leapt through the trees. A 52 million-year-old ankle fossil (pictured) shows the first primates were high flying acrobats in a find that could rewrite human history.

Summary: I learn best with toy code that I can play with. This tutorial teaches backpropagation via a very simple toy example, a short python implementation. Edit: Some folks have asked about a followup article, and I'm planning to write one. Feel free to follow if you'd be interested in reading it and thanks for all the feedback! However, this is a bit terse…. A neural network trained with backpropagation is attempting to use input to predict output.