After looking at the emerging Technology Trends in the HR Space and the scope for People Analytics, the logical step forward was to explore the latest Buzz Word in Technology –"Machine Learning" and its applicability in the HR Space. Although Machine Learning and AI are gaining or rather re-gaining traction in present times, the technology is still in its nascent stages, with more tug in the academia and research domain than in business applications although google, Facebook, IBM (Watson/IRIS) and the likes have been building their commercial success on Machine learning which has in turn renewed interest in this sphere. This article explores the possibilities of using Machine learning in the Talent and HR space. To quote Tom Mitchell "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E." In plain words, the machine is able to improve the outcome of tasks performed, by learning through prior experience of the task-performance outcome: Much like humans do. This concept defies the hitherto ideal program concept that a machine would function according to a specific code based on a set algorithm.

Here at GoodPractice the IT boffins think this idea can be applied to our leadership and management content. Imagine a site that could learn who you are and invisibly adapt to your shifting interests. It would be a site that was just plain interesting. For each individual the content would be equally pertinent, but only by being subtly different. GoodPractice has always strived to present truly useful content.

Artificial intelligence (AI) and a world in which machines threaten humanity's status quo has been the preserve of science fiction for decades. In the Eighties, Terminator was set in a post-apocalyptic world in which cyborgs rule, RoboCop's protagonist was part-man, part-machine and Short Circuit toyed with the idea of robots developing human-like minds, with rather more endearing results. The reality is the bot has bolted. AI is walking and talking among us. In 2016, we use voice-recognition systems, driverless cars are being trialled and robotic hotel receptionists work in Japan.

Retired U.S. Air Force Col. Gene Lee (seated) is operating a simulator developed by Nick Ernest (standing left) for military training and research. Ernest, a University of Cincinnati graduate and Psibernetix president and CEO, is standing next to David Carroll of Psibernetix. Gene Lee has decades of experience as a fighter pilot and aerial combat instructor. The talent Lee, a retired U.S. Air Force colonel, has as a pilot allowed him to easily and consistently defeat other computer programs used in research and training. That was until he began working with a system developed by a University of Cincinnati doctoral graduate in collaboration with the Air Force Research Laboratory based at Wright-Patterson Air Force Base.

Mobile systems are relying more on cloud-based services that, themselves, are becoming more intelligent. Machine intelligence is now able to learn from experience and objectives. The next decade will be full of major benefits to society. When I was a young graduate student in computer science at Stanford University in 1968 to 1972, I took a class from one of the most famous professors in artificial intelligence at the time, John McCarthy. Our assignments were often to write small programs in LISP, a language most noted for nesting of statements that began and ended with a parenthesis.

Technology that can mine the clinical patient data that already exists is finally available - now is the time to speculate to accumulate. The intersection of technology and health has thrown up almost as many questions as it has solutions. "Innovation through collaboration: Bringing disruption to the patient" was the title of the recent Financial Times Digital Health Summit Europe, which took place in London in June. Speaking at the event was ICON's Chief Information Officer, Tom O'Leary. Since its inception in 1990, ICON has been offering a range of drug development services to the pharmaceutical industry, running clinical trials worldwide across all therapeutic areas, diseases, and indications, on behalf of pharmaceutical, biotechnology, and medical device companies.

There is a need for a new global platform to monitor, consider, and make recommendations about the implications of emerging technologies in general, and AI more specifically, for international security. The doomsday scenarios spun around this theme are so outlandish – like The Matrix, in which human-created artificial intelligence plugs humans into a simulated reality to harvest energy from their bodies – it's difficult to visualize them as serious threats. Meanwhile, artificially intelligent systems continue to develop apace. Self-driving cars are beginning to share our roads; pocket-sized devices respond to our queries and manage our schedules in real-time; algorithms beat us at Go; robots become better at getting up when they fall over. It's obvious how developing these technologies will benefit humanity. But, then – don't all the dystopian sci-fi stories start out this way?

To both kick off and maintain relationships and also spark ideas I've found Charlie App to be useful, it does a lot of the googling for you if you are doing some research on a contact. My brother, Tristan, and our little sister's boyfriend, Will, and I set up our own company, Howdy Hub, to help build powerful connections. LinkedIn is a remarkable vault of human professional interconnectivity but it tends towards making a link only after a physical meeting. We complement LinkedIn to allow people to discover others around them at meetups and conferences or when joining a new community. Howdy is developing artificial intelligence to recommend who is a match for your professional needs.

Machine Learning is a very hot topic these days. Getting started can be fast and easy. In this video post, I walk through the steps to build a simple Universal Windows Application (UWP) that connects to the Microsoft Cognitive Services and the Emotion API. The Microsoft Cognitive Services are a set of APIs that enable your apps to leverage powerful algorithms using just a few lines of code. They work across lots of various devices and platforms such as iOS, Android, and Windows, keep improving and are easy to set up.

Turi, formerly Dato, today released the newest version of its GraphLab Create platform and several other features designed to make it easier to add machine learning features to applications. The new version of GraphLab Create includes a toolkit that allows sales, marketing and other teams to predict which potential clients are likely to take an action like subscribing to a service. The GraphLab update also includes a new object detection toolkit and a way to explore and evaluate models without writing more code. "Not everyone is comfortable putting a predictive model into production, not even data scientists," Carlos Guestrin, CEO of Turi, said in a statement. "Today we're addressing the need for trustworthy machine learning with new'views' that let our customers visualize the performance of their models before they're deployed."