PredictionIO is an open source machine learning server, and is a recent addition to the Apache family. PredictionIO is bundled with HBase, and is used as event data storage to manage the data infrastructure for machine learning models. In this integration task, we will use MapR-DB within the MapR Converged Data Platform to replace HBase. MapR-DB is implemented directly in the MapR File System. The resulting advantages is that MapR-DB has no intermediate layers when performing operations on data.

Machine learning is a subfield of computer science, that grew out of the quest for artificial intelligence. It is so pervasive in today's world that you probably use it often in daily life, without even realising it. Machine learning has given us self-driving cars, effective web search, recommendations that you get when you visit web sites or social media sites, face detection in a digital photo album, stock trading etc. Machine learning enables computers to analyze vast amounts of data and automatically detect patterns and features, or make predictions regarding certain conditions. In a dynamic disease like cancer, gauging and diagnosing such a complex heterogeneity is the biggest challenge. After decades of cancer research, it has become increasingly clear that no two patients' cancers are exactly the same, and even within one person's tumor there is a wild diversity of cells.

How will the Artificial Intelligence will affect our life by 2030? We all have seen many science-fiction movies, which present us how the life on Earth will look in the future. Have you ever thought how the Artificial Intelligence will affect our life by 2030? In the future, A.I. will change the way we work, travel or take care of our health. Experts from Stanford University are involved in a study.

Artificial intelligence is very interesting topic of research for many modern scientists. The concept of machine intelligence is really fascinating. It gives human a power to design something that can live on its own. The AI technology has become really advanced and its only matter of time when the machines will be able to learn almost anything. The machine learning algorithms are already very smart, however the processing power has been a challenge in last decade.

An artificial intelligence software developed that can assist in predicting breast cancer risk.

Knowing that an AI wrote Sunspring makes the movie more fun to watch, especially once you know how the cast and crew put it together. Director Oscar Sharp made the movie for Sci-Fi London, an annual film festival that includes the 48-Hour Film Challenge, where contestants are given a set of prompts (mostly props and lines) that have to appear in a movie they make over the next two days. Sharp's longtime collaborator, Ross Goodwin, is an AI researcher at New York University, and he supplied the movie's AI writer, initially called Jetson. As the cast gathered around a tiny printer, Benjamin spat out the screenplay, complete with almost impossible stage directions like "He is standing in the stars and sitting on the floor." Then Sharp randomly assigned roles to the actors in the room.

Previously I explored the value of eminence and thought leadership to consulting firms, and how unfortunately the power of inbound content marketing has a dark side that forms part of a three-pronged attack on the consulting industry. Meanwhile, the tireless invention and innovation efforts of research teams in companies around the world have helped to keep the pace of technological advancement in computer processing power at or above Moore's Law for several decades. This has given technology companies the ability to put more computing power than the entire Apollo space program into the pockets of more than a billion people around the world. It seems like everything has become digital, including music, books, and even movies. Increasingly intelligent digital technologies and mercurial customer expectations threaten both people and enterprise at every turn.

The technology press is abuzz these days with stories about Machine Learning (ML) and Artificial Intelligence (AI) -- every other week it seems we're hearing about a new AI surpassing human ability at some task or other, and just as often we hear about exciting new start-ups revolutionizing traditional problem spaces using machine learning. We also see the odd notable AI failure every now and then. It can be hard to conceptualize what people are talking about when it comes to AI; and of course there's also the question of the so-called Singularity (an artificial "superintelligence" arising and causing runaway technological growth): just how near is it? This post is the first in a series on machine learning, and aims to bring some clarity to the subject, explaining how the concepts of machine learning and artificial intelligence relate to each other. It also describes at a high-level how basic ML works today to solve problems.

Is Humanising Chatbots the Next Inevitable Improvement?

When it comes to enterprise customer care, machine learning enables virtual assistant solutions to automate tasks that used to require a live agent: password resets, address and complex information collection, even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take enterprise customer care to the next level.