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.

"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.

Much has been made of the fact that Dallas police used a robot to kill the gunman who fatally shot five officers last week. A lot of breathless speculation has gone into exactly what type of vehicle was used to carry the bomb to Micah Johnson's position, in what was widely reported as the first time that tactic was used on U.S. soil. Now, Dallas police have released additional details about the technology it used to end the standoff. On Saturday, authorities reported using a Remotec model F-5 to deliver a one-pound payload of C-4 and detonation cord to the target. In a news conference on Monday, Dallas Police Chief David Brown clarified that officials used a Remotec Andros Mark V-A1.

One of the most advanced prosthetic arms yet is coming to market this year, brought to you by robot-friendly U.S. military agency DARPA and the Segway inventor Dean Kamen. Mobius Bionics LLC, a medical device company, will produce the Luke arm commercially, named for the lifelike replacement Luke Skywalker received at the end of Star Wars Episode V: The Empire Strikes Back. The Defense Advanced Research Projects Agency (DARPA) funded the arm and Dean Kamen's DEKA company designed it, with the goal to "develop an advanced electromechanical prosthetic upper limb with near natural control that would dramatically enhance independence and improve quality of life for amputees," according to the Mobius Bionics press release. The prosthesis combines a number of features to accomplish that goal. The system can accommodate people with varying levels of amputation.