If you are a fan of Iron Man or the Avengers franchise, you know that when Tony Stark is talking to Jarvis, he is talking with Artificial Intelligence or AI. According to computer science, an'intelligent machine' is a rational agent who perceives its environment and takes those actions, which will maximize its chances of success for the specified goal. In simple terms, intelligence that is exhibited by the machines is termed as'Artificial Intelligence' or AI. Ever wondered how Google Now, Siri, and Cortana help you find information? They are all AI applications used on different platforms.

In our recent article about artificially intelligent (AI) robot writers, we talked about how media content is starting to be automatically generated using scripted methods that let you produce lots of content very easily. Here at Nanalyze, we love to write about technology in a way that is relevant to investors, straight forward, and doesn't pander to anyone. We typically don't cite authors on our articles because we believe the message is more important than the messenger (don't shoot the messenger and all that). We also believe that someday in our lifetimes, the occupation of being a "writer" is going the way of the dodo because artificial intelligence (AI) will do a better job than human authors. At that point, you could either make up fake names for your authors or what will most likely happen is we'll have different AI sages that are watched over by a human editor but that publish under a single brand name.

Do humans make computers smarter? Could machine learning save this sea cow? Artificial intelligence is fact, not fantasy! Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term.

Despite the desire for equitable hiring practices, humans have biases in every decision they make, and most of the time they don't realize it. Often, hiring managers recommend a candidate because of a personal connection such as alumni groups or an interest in sports, or qualified candidates are not considered because of a gap in employment. A diverse workforce is proven to increase an organization's revenue, but the key challenge is building and retaining that diverse and competitive workforce. It's met with personal bias from an archaic, bias-prone process that relies on resumes. This is one of the most pressing challenges organizations face, because without the right talent, they cease to compete with their products or services.

Technology is rapidly changing how people do everything; from taxis to food delivery, from dating to media consumption and everything in-between. There have been many visible ways in terms of technology impacting healthcare. From microscopes & stethoscopes invented hundreds of years ago, to MRI machines today, to the goal of creating a Tricorder in a Star Trek-like future, technology is making sweeping changes in healthcare and undoubtedly India will be a big beneficiary. The main drivers, today and in the future, are smartphones, always-on connectivity, big data and artificial intelligence (AI). In the way regular mobile phones became ubiquitous, soon most people in India will have powerful and connected supercomputers in their pocket as prices for smartphones and internet access continue to drop and become more accessible.

An Artificial Neural Network (ANN) is a computational model that is inspired by the way biological neural networks in the human brain process information. Artificial Neural Networks have generated a lot of excitement in Machine Learning research and industry, thanks to many breakthrough results in speech recognition, computer vision and text processing. In this blog post we will try to develop an understanding of a particular type of Artificial Neural Network called the Multi Layer Perceptron. The basic unit of computation in a neural network is the neuron, often called a node or unit. It receives input from some other nodes, or from an external source and computes an output.

Today at the O'Reilly AI Conference in New York, Baidu Research announced DeepBench, the first open source benchmarking tool for evaluating deep learning performance across different hardware platforms. The announcement was made during a presentation by Greg Diamos and Sharan Narang of Baidu Research's Silicon Valley AI Lab. "Deep learning developers and researchers want to train neural networks as fast as possible. Right now we are limited by computing performance," said Dr. Diamos. He added: "The first step in improving performance is to measure it, so we created DeepBench and are opening it up to the deep learning community. We believe that tracking performance on different hardware platforms will help processor designers better optimize their hardware for deep learning applications."

Machine learning and Artificial Intelligence are two buzz terms that could have a profound effect on the overall customer experience related to financial institutions. These technologies are picking up steam as they make their way toward the mainstream in financial services, ultimately, making everything faster and more intuitive. Machine learning is a subset of artificial intelligence that enables computers to learn without being explicitly programmed. With machine learning, computers can analyze new information and compare it with existing data to look for patterns, similarities, and differences. David Gilvin, partner, banking & financial markets leader, IBM Digital Consulting, IBM, discussed this burgeoning theme during a session titled, "Machine Learning & Artificial Intelligence Powering Next Gen CX in Financial Services," at the recent Money20/20 Conference in Las Vegas.

Oxford University researchers have developed an artificial intelligence that can accurately read lips using deep learning technology from DeepMind. The team calls its AI LipNet and it uses a technique called deep learning. Basically, the team trained the AI with many different videos of people talking and the AI learned how to lip-read by itself. Deep learning is extremely powerful. Earlier this year, DeepMind's deep learning AI AlphaGo beat the human champion at the game of Go, and deep learning has been applied to all sorts of other problems.

But after decades of anticipating the advent of "adult" robots, artificial intelligence is finally growing up and starting to get real jobs. The implementation of AI has been a slow and, at times, clunky process. We had ELIZA by 1966, but it wasn't until three decades later -- in 1997 -- that Deep Blue was able to beat chess champion Garry Kasparov. Fast-forward almost two more decades: my laptop just underlined "Gary" in red, because it knew that, despite G-A-R-Y being the far more common spelling, Kasparov's first name has two Rs. And then there's our dear friend Siri, who can show us where to get sushi, find a picture of Batman, or even tell us a story.