Artificial intelligence research continues to accelerate as human and machines collaborate to solve more complex problems. A new survey by the National Academy of Science identifies the frontiers of AI research that include "augmented cognition" along with "integrative" AI. In a workshop report on IT innovation just released by the National Academy's science, engineering and medicine branches, a section on "Developing Smart Machines" describes ongoing AI research efforts along with machine learning, a discipline some experts consider a subfield of AI. "Machine learning is what lets computers discover patterns within data and then use those patterns to make useful, and ideally correct, predictions," the report states. The authors quotes Jaime Carbonell, a professor of computer science at Carnegie Mellon University, as noting" "Machine learning essentially is the engine that is driving modern artificial intelligence." Machine learning "often deals with unbalanced data sets in which the ultimate focus of decision making is precisely the outlier cases," that is, the extreme cases that contrast sharply with typical data and provide opportunities for the "most important learning opportunities."

Elsewhere, I have suggested that there are three junctures at which any data mining project may go the most wrong: 1. problem definition, 2. data acquisition and 3. model validation (see the Data Mining and Predictive Analytics Web log). Data acquisition is a superset of statistical sampling, and the text by Lohr is highly recommended for this topic. Model validation is well explained in the literature: see, for instance, Weiss and Kulikowski. Problem definition involves understanding the business problem and mapping an appropriate technical solution to it. This may not be as simple as it sounds, and it is easy to be naïve about the best way to construct a technical solution which most naturally solves the given problem.

This episode of Fresh Machine Learning is all about a relatively new concept called a Generative Adversarial Network. A model continuously tries to fool another model, until it can do so with ease. At that point, it can generate novel, authentic looking data! Thanks for watching my videos, I do it for you. I left my awesome job at Twilio and I'm doing this full time now.

Everyone who gets going in Machine Learning (and Deep Learning) gets overwhelmed by the plethora of MOOCs available. Here, I try to give a comprehensive survey of such courses available freely on the internet. You can take this post as an complementary to this and this previous posts. I will try to highlight some important pointers such as the difficulty of the courses, the correct order in which these should to be completed, the right audience for these courses. You will get a feel of how these courses give you a stack of skills in your arsenal and how you can use them to develop practical machine learning systems.

Today eBay announced it will acquire SalesPredict, an Israel-based company that leverages advanced analytics to predict customer buying behavior and sales conversion. SalesPredict is eBay's latest acquisition that will support its artificial intelligence, machine learning and data science efforts. It follows eBay's recent acquisition of Expertmaker, in order to further bolster our structured data efforts. Financial terms of the deal were not disclosed. Upon the close of the transaction, a number of SalesPredict's employees will join eBay's structured data organization, working from eBay's Israeli Development Center in Netanya.

We were all quite pumped a few weeks ago when Anki announced its plan to move beyond smartphone controlled cars into emotionally intelligent robots. At the time of the announcement Anki indicated that it would release an SDK with the inclusion of Cozmo, but until now details on what that SDK would be were sparse. Now we know, and the SDK is so jam-packed with goodies it could turn Cozmo into the Commodore 64 of robotics--a device that changes how people interact with abstruse technology. The Commodore 64 changed the way we thought about computers. Before that ugly box got plugged into TVs across the United States computers were still for the very rich, the very smart, and the ladies programming the IBM beasts that took up entire floors of buildings.

Intelligence, defined as the ability to acquire knowledge and skills. Intelligence for the longest time possible is associated with the human brain. Artificial intelligence is basically defined as intelligence that is originating from machines. Most computer applications only make existing processes and functions faster and maybe more efficiently but cannot create new duties altogether. However, artificial intelligence has already challenged this notion.

Robotics, artificial intelligence, and automation are all going full steam ahead. In the uncertain future, one thing we can all count on is that just about all jobs and professions will be affected. The most important question for most of us is, "Will I lose my job?" Opponents of minimum wage increases say that if fast food industries are forced to bump up entry level salaries, they'll install robots instead. A new report from McKinsey & Company might give solace to burger flippers, but perhaps no one else in the workforce, as reported on SiliconBeat. The report breaks U.S. jobs into three categories based on the tasks involved.

"Patience is not simply the ability to wait - it's how we behave while we're waiting" - Joyce Meyer The recent death of Tesla's autopilot driver is a devastating human tragedy. The amount of the outpouring sympathy to driver's family is also understandable - because of the intriguing novelty surrounding self-driving cars. As a result, Artificial Intelligence (AI) nowadays is almost synonymous with the entire concept of autonomous cars. Not a single day goes by without seeing, or hearing, yet another prediction of cars without steering wheels roaming the highways. Apparently, this may all happen by the end of this decade.

We aim to create and innovate with the product design of a new generation of fortune teller robotic machines that work with Artificial Intelligence applications to provide a new market of psychic services for the consumer and business to business corporate industries.