Matt Coatney is a technology executive, business advisor, entrepreneur, author, and speaker. His focus is on bringing advanced artificial intelligence and analytic technologies to market. He has co-founded three companies, advised several others, and contributed to the early success of two different tech startups. Matt has also launched data analytics products designed for the fields of life sciences, healthcare, government, finance, and law. Currently Matt is the VP of Services for Exaptive; he previously was the IT strategy lead for global law firm WilmerHale, and was in charge of technology and operations for a legal search product at LexisNexis.

Deep learning is giving industry leaders a boost that puts them head and shoulders above the competition. In order to meet this raised bar, companies must stay on the "bleeding edge" of machine learning techniques. In this video, Matt Coatney explains how neural networks can handle heightened levels of abstraction to identify even partially obscured facial features. Executives, managers, and entrepreneurs from either technical or business backgrounds will walk away with a better understanding of recent advances in deep learning and how they can be leveraged in the modern digital economy. Beyond personal photos, innovators can apply the techniques outlined in this video to an array of scenarios, from satellite imagery to warehouse and supply chain management.

Nintendo is doubling production of the Nintendo Switch, as fans struggle to buy the consoles weeks after it was launched. The console originally launched at the beginning of this month. But even on that release date, it wasn't really possible to buy it – all the pre-orders had been snapped up in advance and people were left waiting for weeks. That trend has continued in the weeks since, with consoles occasionally arriving on retailers like Argos and the Nintendo official store but quickly being bought. Even big websites like Amazon don't have much stock, leaving people waiting until the end of the month.

Two people have died after mysterious ghost calls flooded the 911 emergency dispatch system in Dallas, Texas. Six-month-old Brandon Alex passed away on Saturday after falling out of his bed. His babysitter found him unconscious but still breathing and called 911 three times, but was repeated placed on hold and eventually hung up after failing to get through for more than 30 minutes, reports Dallas News. The youngster was taken to hospital by his mother, Bridget Alex, but didn't regain consciousness. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Autonomous vehicles are already a common sight on the streets of Silicon Valley, an international hub for self-driving technology. But this month, California set the stage for the next phase of innovation that could dramatically alter transportation and mobility across the globe. The state has proposed regulations to allow fully autonomous vehicles to drive on public roads – meaning empty cars with no steering wheels and no backup driver inside. The new rules are a game-changer for the nascent industry, opening the doors to a host of complex questions about legality, ethics and safety. The regulations, which could go into effect this year, pave the road for a deployment that could revolutionize modern society.

AI stands for Artificial Intelligence, computer systems that can achieve intelligent activities like those of human brains such as learning, reasoning, and judgment. The learning method employed by early AI systems was to have computers learn the rules and logically find solutions based on the rules. As such, the systems were limited in that they only found solutions within the scope of what they had learned. More recent types of AI being used today are designed based on hypotheses of data that people would enter, implemented as programs, and analyzed and developed for a specific application. One disadvantage of being based on hypotheses envisioned by people is that they usually do not produce results that surpass human ideas and are not general purpose. One well known AI system is IBM's Watson, which is described by Wikipedia as a question-answering computer system capable of answering questions posed in natural language.

Machine learning is typified by algorithms that are capable of deriving patterns and'intelligence' from vast quantities of training data. As company's such as DeepMind are beginning to show us however, the real improvements come when the machines are capable of learning independently of data fed it by us. A recent paper from researchers at the University of Toronto highlights some of the progress being made. The team developed an algorithm that attempts to learn from human instructions. In other words, it doesn't require a database of past examples, as is the norm today.

"A company's data is its most valuable weapon," according to Steve Miranda, Oracle's executive vice president of applications development. Most of the finance executives I know would agree with this statement. After all, finance professionals have built whole careers on data and numbers. And yet, very few of today's finance teams make the best use of the data they have. Part of the problem is that there is just so much of it.

If you're a CEO and sometimes think your technical team speaks a different language, you're not alone. My world is saturated with tech jargon because I am a venture capitalist who reviews and meets with hundreds of tech startups every month. But which buzzwords are the most important for a CEO to understand? Which tech terms have gained prominence because they point to significant trends that, if not harnessed, can leave a business eclipsed? Look no further than the taxi industry and how it was outmaneuvered by the tech-savvy Uber for a prime example.

The media often likes to proclaim "The Year of This" or "The Year of That." With the greater attention given to advancing capabilities in artificial intelligence and machine learning, it seemed like a no-brainer to declare 2017 "The Year of AI." However, in the interest of truth and the pursuit of all things real, it appears we may have been all wrong. According to a new report from big data management company Talend, 2017 will not be the year of AI, but will actually be the year of (wait for it) real-time analytics. This finding, which is based on a survey of 189 people who attended a Talend event in Paris last fall, may run counter to the prevailing wisdom that AI and ML are taking off in big ways, and that they are doing so right now.