This guest post was written by Daniel Emaasit, a Ph.D Student of Transportation Engineering at the University of Nevada, Las Vegas. Daniel's research interests include the development of probabilistic machine learning methods for high-dimensional data, with applications to urban mobility, transport planning, highway safety, & traffic operations. Don't miss Daniel's webinar on Model-Based Machine Learning and Probabilistic Programming using RStan, scheduled for July 20, 2016 at 11:00 AM PST. This blog post follows my journey from traditional statistical modeling to Machine Learning (ML) and introduces a new paradigm of ML called Model-Based Machine Learning (Bishop, 2013). Model-Based Machine Learning may be of particular interest to statisticians, engineers, or related professionals looking to implement machine learning in their research or practice.

Co-authored by Rob Thomas (@robdthomas) Machine Learning represents the new frontier in analytics, and is the answer of how many companies can capitalize on the data opportunity. Machine Learning was first defined by Arthur Samuel in 1959 as a "Field of study that gives computers the ability to learn without being explicitly programmed." Said another way, this is the automation of analytics, so that it can be applied at scale. What is highly manual today (think about an analyst combing thousand line spreadsheets), becomes automatic tomorrow (an easy button) through technology. If Machine Learning was first defined in 1959, why is this now the time to seize the opportunity?

This summer schools is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.

The marriage of computing power and data is finally bearing fruit in the field of cognitive computing, sometimes called machine learning or, more controversially, artificial intelligence. In its most everyday form, we see it in tools such as Google Translate or Microsoft's Bing Translate, which can translate phrases and documents effortlessly across multiple languages. More futuristically, the promise of self-driving vehicles, which can complete entire road journeys without driver intervention, is already being realised. Yet the biggest revolution in work is happening at some of the most basic levels, such as reading and dissecting legal documents to extract meaning and useful information. The tedious slog of work can be transformed by computers which are able to read and parse legal phrases, and summarise them or enter relevant details into a database or spreadsheet.

I'm seated in a giant ballroom where vast rows of chairs face seven glowing supercomputers. Each liquid-cooled rack of servers is lit with a different color. Though they stand on a dais at the Paris Las Vegas resort as still as statues, the computers are locked in heated battle with each other. "The race for third is very tight," says Hakeem Oluseyi, an astrophysicist, in a rousing voice. ForAllSecure's team Mayhem stands as a silent sentinel in the DARPA Cyber Grand Challenge.

In collaboration with the Norwegian University of Science and Technology (NTNU) and the leading research institute SINTEF, Telenor will establish a lab focused on artificial intelligence and big data at NTNU in Trondheim, Norway. As the second initiative, Telenor will develop and launch a dedicated, next-generation Internet of Things (IoT) network in several Norwegian cities. Norwegian startups and students will get cost-free access to the IoT network in order to develop and test their products and services. The first pilot will be located in Oslo, in collaboration with StartupLab. "We need to build critical competencies within artificial intelligence and we want to give Norwegian startups the resources they need to succeed. This is imperative for our ability to seize digital opportunities and contribute to creating new jobs. Startups play a key role in net job creation. We aim to stimulate productivity in Norway by developing new competencies and supporting the startup community," says Sigve Brekke, President and CEO, Telenor Group.

By happy circumstance, Santa Clara-based chip maker NVIDIA finds itself in the position of being an artificial intelligence (AI) startup king maker. The company designs and manufactures the entire computing platform for deep learning, the fastest growing field in AI, building everything from graphics processing units (GPUs) to software to systems purpose-built for deep learning. As the name might suggest, GPUs were developed to improve the computer graphics experience by offloading certain computationally intense image processing tasks from the standard central processing unit (CPU). The particular strength of a GPU is performing large numbers of parallel floating point calculations. This helps computer screens to increase in detail and complexity without sacrificing system performance, and modern gaming would not be possible without it.

Intel has introduced a quadcopter called Aero at its annual developers conference, and we'll bet you can guess its target audience based on the event. That's right, Aero was specifically designed not for hobbyists or for commercial purposes, but for developers who want to create and test apps for drones. The company said it's the "fastest path available from Intel for developers to get applications airborne." Aero is powered by an Atom processor and comes equipped with Intel's RealSense camera for vision. It's also preloaded with AirMap, an app that tells you where you can and can't fly, gives you real-time info on wildfires and the like, as well as gives you an easy way to plot routes.

Nasa launches million dollar contest to create'Valkyrie' AI robot that will accompany astronauts on ... Will Content Marketing Die To Robotic AI?

Zoltan Istvan, who represents the Transhumanist Party and bills himself as "the science candidate" in the 2016 U.S. presidential election, has garnered more media coverage than many third party candidates, with recent mentions in Vocativ, The Verge, USA Today, and Pacific Standard. He also writes regularly for Motherboard and The Huffington Post. Istvan's popularity is likely due to a combination of his quirky campaign style (he drives around in a bus painted to resemble a coffin with "Science vs. The Coffin" written above the bumper) and an unconventional platform that pushes for gene editing, human life extension, and morphological freedom (the right to do anything to your body so long as it doesn't harm others). As a broader movement, transhumanism focuses on leveraging science and technology toward the ultimate goal of overcoming death, largely through as-yet-unproven methods such as mind uploading, in which a person's entire consciousness would be transferred to a digital system or machine.