Job Requirements • Master's degree or equivalent work experience in machine learning • Strong hands on experience solving complex problems using unsupervised and supervised machine learning algorithms • Proficiency in feature selection and feature engineering • Strong experience with big data tools and techniques, like Hadoop and Spark • Broad knowledge of machine learning algorithms, with ability to select and apply appropriate algorithms to specific problem domains • Ability to collaborate with domain experts to efficiently and effectively identify and extract previously unfamiliar domain knowledge Preferred • Knowledge in Natural Language Processing, especially named entity recognition • Experience in problems associated with people-centric data, like name parsing, name comparison, address parsing etc. • Experience with frameworks and techniques in deep learning and deep neural networks • Experience with computer vision, particularly facial recognition and comparison About SureID SureID, Inc. integrates leading edge products and services into solutions that combine identity enrollment, authentication, background screening, and access management to make facilities, assets, and people safer and more secure. Using SureID's patented programs, highly secure facilities – such as military installations, government buildings, manufacturing and distribution sites, ports, and commercial builds – can increase security and streamline access for authorized personnel. SureID has a proven track record for successfully servicing government, military and commercial clients. The RAPIDGate Program already serves thousands of companies and hundreds of thousands of RAPIDGate badge-holders who enjoy streamlined access into Department of Defense and Homeland Security facilities. SureID is a privately-held company founded in November 2001 and headquartered in Hillsboro, OR.

As we have been writing for a while now, artificial intelligence will transform pretty much everything we do in our lives in the next five years. AI is actually in use today helping us to match faces, identify photos, videos, the spoken word, doing our taxes, improving collaboration, and even help in healthcare diagnosis, and soon, will help drive our cars and trucks for us. While AI has been around for a while, the big breakthrough was machine learning using deep neural networks that actually got smarter with more information you threw at it. GPUs, with NVIDIA being the biggest recent beneficiary, have become the most recent standard for cutting edge deep neural network training, and inference today is spread across CPUs, GPUs, FPGAs, ASICs and even DSPs. AI is a quick moving target and I think it's unwise to think the engines today will be static in the future.

In almost every list discussing future trends in the events industry, artificial intelligence is named. Along with developments in virtual and augmented reality, A.I. is breaking ground, not only in its capacities to serve human needs, but also in its potential for transforming customer service. In particular, A.I. allows for a heightened level of personalized service. As machines perceptively learn a user's behavior through data gathered from the user's interactions, this information is used to power highly relevant suggestions and services. Relevance combines with a natural user experience when smart technology such as chatbots provide a human-like interface.

And last year, one tech company, Alphabet's Google, published papers in all of them. According to the tally Google provided to MIT Technology Review, it published 218 journal or conference papers on machine learning in 2016, nearly twice as many as it did two years ago. "The top people care about advancing the world, and that means writing papers the world can use, and write code the world can use." So when Apple hired computer scientist Russ Salakhutdinov from Carnegie Mellon last year as its new head of AI, he was immediately allowed to break Apple's code of secrecy by blogging and giving talks.

And last year, one tech company, Alphabet's Google, published papers in all of them. According to the tally Google provided to MIT Technology Review, it published 218 journal or conference papers on machine learning in 2016, nearly twice as many as it did two years ago. "The top people care about advancing the world, and that means writing papers the world can use, and write code the world can use." So when Apple hired computer scientist Russ Salakhutdinov from Carnegie Mellon last year as its new head of AI, he was immediately allowed to break Apple's code of secrecy by blogging and giving talks.

These are some the most elite academic journals in the world. And last year, one tech company, Alphabet's Google, published papers in all of them. The unprecedented run of scientific results by the Mountain View search giant touched on everything from ophthalmology to computer games to neuroscience and climate models. For Google, 2016 was an annus mirabilis during which its researchers cracked the top journals and set records for sheer volume. Behind the surge is Google's growing investment in artificial intelligence, particularly "deep learning," a technique whose ability to make sense of images and other data is enhancing services like search and translation (see "10 Breakthrough Technologies 2013: Deep Learning").

Robotics and artificial intelligence could affect almost a third of UK jobs by the 2030s, according to a study. However, the report from accountancy firm PwC also predicted that the nature of some occupations would change rather than disappear. It added that automation could create more wealth and additional jobs elsewhere in the economy. Jobs in manufacturing and retail were among the most at risk from the new technologies, the report said. The study estimated that 30% of existing jobs in the UK were potentially at a high risk of automation, compared with 38% in the US, 35% in Germany and 21% in Japan.

The rise of artificial intelligence (AI) is the great story of our time. Decades in the making, AI-infused machines will soon change our lives and work in ways that are easy to imagine but hard to predict. "The machine" has already won in stock picking. At Houston Methodist Hospital, AI software interprets results of breast x-rays 30 times faster than doctors do and with 99% accuracy. Soon, relying only on humans for discovery might become grounds for malpractice.

These are three terms that are heard all the time now, but often people still get confused about what each one really entails. Below is a quick rundown of each that will hopefully things out a little and give you a real insight as to what these interchangeable terms mean. Artificial Intelligence, or AI for short, is the broadest way in which to describe computer intelligence. Back in1956 it was described as "Every aspect of learning or any other feature of intelligence can in principle is that a machine can be made to simulate it" at the Dartmouth Artificial Intelligence Conference. AI can come in various forms including game-playing computer programs and voice recognition systems.

SYS-CON Events announced today that Loom Systems will exhibit at SYS-CON's 20th International Cloud Expo, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Founded in 2015, Loom Systems delivers an advanced AI solution to predict and prevent problems in the digital business. Loom stands alone in the industry as an AI analysis platform requiring no prior math knowledge from operators, leveraging the existing staff to succeed in the digital era. With offices in San Francisco and Tel Aviv, Loom Systems works with customers across industries around the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT.