The company has developed a kind of "App Store" for medical care complete with 40 predictive and prescriptive apps targeting Physicians, Care Managers, Hospital Ops and Finance teams. Their claim is what used to take months to build and deploy, can now happen in a matter of weeks at a significant cost reduction regarding both deployment and ongoing platform operation. The market opportunity is huge. The United States has the biggest healthcare industry in the world, spending approximately $3 trillion a year. By 2018, healthcare will comprise close to 18% US gross domestic product.

We want to apply new data to our network and classify inputs If we overtrain / overfit our network to our training data then our accuracy will be deceiving. It might work very well for training data, but will not work on test data. In order to prevent overfitting we implement preprocessing techniques and tune our hyper parameters.

SYS-CON Events announced today that Conference Guru has been named "Media Sponsor" of SYS-CON's 20th International Cloud Expo, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. A valuable conference experience generates new contacts, sales leads, potential strategic partners and potential investors; helps gather competitive intelligence and even provides inspiration for new products and services. Conference Guru works with conference organizers to pass great deals to great conferences, helping you discover new conferences and increase your return on investment. All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

What could your company accomplish if every customer and employee interaction with technology was an intelligent one? The Accenture Technology Vision 2017 delves into a fascinating trend that's at the heart of my daily responsibilities--and I know of substantial interest to our clients. The AI Is the New UI chapter looks at how artificial intelligence (AI) will quickly become more than an underlying technology capability; it will permeate intelligent enterprises and advance to a fundamental tool for daily engagement with people--both customers and employees. We also describe in the Tech Vision how AI will, in time, become the digital spokesperson for leading enterprises. Customers will experience a company's brand through personalized, 100 percent consistent and natural interactions with AI service agents--and even engage with the brand through other companies' AI interfaces. This post highlights how we see this tech trend unfolding.

The history of Artificial Intelligence is long, but it's only been recently that technology companies and markets have begun to get excited about it… Why? After a few decades of exploration of symbolic AI methods, the field shifted toward statistical approaches, that have as of late started working in a broad array of tasks due to the explosion of data and computing power, this in turn has led to machine learning and, most importantly, enabled deep learning. This is great news for the tech industry. The downside is that there aren't enough data scientists that understand deep learning. For those who do, there is a huge demand for their services.

A version of this essay was originally published at Tech.pinions, a website dedicated to informed opinions, insight and perspective on the tech industry. A great deal has been written recently on the growing importance of voice-driven computing devices, such as Amazon's Echo, Google Home and others like them. At the same time, there's been a long-held belief by many in the industry that software innovations will be the key drivers in moving the tech industry forward ("software is eating the world," as venture capitalist Marc Andreessen famously said more than five years ago). The combination of these two -- software for voice-based computing -- would, therefore, seem to be at the very apex of tech industry developments. Indeed, there are many companies now doing cutting-edge work to create new types of software for these very different kinds of computing devices.

Machines have already surpassed humans in terms of image recognition ability. In the next 20 years, experts predict that machine learning will continue to make great strides on a number of human tasks. If this innovation is done in an ethical way, we can build a future in which humans are not competing with machines or being overtaken by robots, but instead entering into a new era of collaboration that frees up the human spirit for more meaningful tasks that require emotional intelligence.

Intended for executive leadership who are looking to better understand the implications of AI, and need to decide where to focus time and investment in machine learning (AI) technologies. The idea of AI--of machines that can sense, classify, learn, reason and interact--has been around for decades. Yet today, the combination of massive and available data sets, inexpensive parallel computing and advances in algorithms has enabled machines to function in ways not possible before. While "shiny" examples such as robotics, driverless cars and intelligent agents dominate the news – artificial intelligence has wide implications for all types of organizations – not just cutting edge technology giants. This report lays out the current state of AI for business, describes primary and emerging use cases, and states the risks, opportunities and organizational considerations that businesses are facing.

Of all the subdisciplines of AI, some of the most exciting advances have been made within machine learning. In short, machine learning is the ability for a program to absorb huge amounts of data and create predictive algorithms. If you've ever heard that AI allows computers to learn over time, you were likely learning about machine learning. Programs with machine learning discover patterns in data sets that help them achieve a goal. As they analyze more data, they adjust their behavior to reach their goal more efficiently.

Computers cannot think, though increasingly, they can do things only humans were able to do. A product of the field of research known as artificial intelligence, cognitive technologies have been evolving over decades. It is now possible to automate tasks that require human perceptual skills, such as recognizing handwriting or identifying faces, and those that require cognitive skills, such as planning, reasoning from partial or uncertain information, and learning. Technologies able to perform tasks such as these, traditionally assumed to require human intelligence, are known as cognitive technologies. Businesses are taking a new look at them because some have improved dramatically in recent years, with impressive gains in computer vision, natural language processing, speech recognition, and robotics, among other areas.