In the course of our work with Intel's data science and artificial intelligence initiatives, we often encounter people who are excited about the potential of artificial intelligence, and eager to learn more about the things Intel is doing to drive the industry forward. In many cases, these people have read about Intel's focus on AI, and now they are asking how they can get more involved in this forward-looking field. They often ask how they can advance their data science careers in the direction of AI. In Part 1 of this blog series, we talked about steps organizations can take to cultivate in-house expertise in advanced analytics and data science. In this second part of the post, we will take things down to a more personal level, and talk about steps individuals can take to chart a future that involves creating AI solutions.

Anyone who's ever landed in the passenger seat with someone learning to drive will admit to being at least slightly nervous. Thanks to advances in artificial intelligence (AI) controls, you may never again have to worry if Jr. makes a mistake behind the wheel. Just make sure your car has enough miles under its belt to know how to avoid a wreck. That's right, artificial intelligence is coming to consumer vehicles, and it could happen as soon as five years from now. While the media has focused primarily on the way this new technology allows for potentially self-driving cars, there are a number of other features and perks that come along with it.

When 27-year old Mayank Ranka is looking for love, he turns to a chatbot. "It instantly finds me a match which is all I need at the end of the day. The even better part is I can end the conversation anytime I want and not chat ever again," says Mumbai-resident Mayank, who works with an event company in Mumbai. Tech-savvy singles like Mayank don't blink before using a speed-dating chatbot like Neargroup which helps them zoom into the right date. The chatbot's in-built AI helps the user to find the right match based on nearby locations, interests and also conversations.

Artificial Intelligence (A.I.) will soon be at the heart of every major technological system in the world including: cyber and homeland security, payments, financial markets, biotech, healthcare, marketing, natural language processing, computer vision, electrical grids, nuclear power plants, air traffic control, and Internet of Things (IoT). While A.I. seems to have only recently captured the attention of humanity, the reality is that A.I. has been around for over 60 years as a technological discipline. In the late 1950's, Arthur Samuel wrote a checkers playing program that could learn from its mistakes and thus, over time, became better at playing the game. MYCIN, the first rule-based expert system, was developed in the early 1970's and was capable of diagnosing blood infections based on the results of various medical tests. The MYCIN system was able to perform better than non-specialist doctors. While Artificial Intelligence is becoming a major staple of technology, few people understand the benefits and shortcomings of A.I. and Machine Learning technologies. Machine learning is the science of getting computers to act without being explicitly programmed. Machine learning is applied in various fields such as computer vision, speech recognition, NLP, web search, biotech, risk management, cyber security, and many others.

Austin's South by Southwest is historically known as a music showcase, yet the Interactive portion of the conference is now the biggest draw for tens of thousands of attendees who come from across the globe. Alan Melson, KERA's VP of Digital, has been writing about the conference this weekend. I spoke with him about what's on tech folks' minds. Alan, it seems like every year there are several recurring themes that emerge from South By Southwest Interactive. What seems to be bubbling up this year?

Aircraft Beach Mountain People marching Police/Security Flower 12. 12 From University-lab to spin-off and your mobile phone • 1000 others * UvA / Euvision / Qualcomm Universities win Start-ups win Snoek et al., TRECVID 2004-2015 13. 13 Latest jump due to deep learning 2006 2009 2015 Meanaverageprecision Progress in video recognition 14. 14 The more features the better Typical shallow learning architecture e.g. That is: given a video, can we find the best matching sentence? That is: given a video, can we find the best matching sentence?

It's almost impossible to escape the impact frontier technologies are having on everyday life. At the core of this impact are the advancements of artificial intelligence, machine learning, and deep learning. These change agents are ushering in a revolution that will fundamentally alter the way we live, work, and communicate akin to the industrial revolution – more specifically, AI is the new industrial revolution. The most exciting and promising of these frontier technologies is the advancements happening in the deep learning space. While still nascent, it's deep learning percolating into your smartphone, driving advancements in healthcare, creating efficiencies in the power grid, improving agricultural yields, and helping us find solutions to climate change.

The following is paid content sponsored by Veritone. Big Data is everywhere, and it keeps getting bigger. It's estimated that 90 percent of all data on the internet has been generated in the past two years, more than three-quarters of it audio and video clips, and the pace continues to accelerate exponentially. For law enforcement, this creates an information overload of evidence that can't be easily searched or analyzed. This recent explosion of law enforcement data, particularly video and audio that by its nature is unstructured and unsearchable, means police are collecting information without the tools to manage it or turn it into actionable intelligence.

Intermountain Healthcare has approximately 150 protocols built into its electronic health record (EHR) system, alerting clinicians when the patient information they enter indicates certain conditions and then guiding them through further examinations and potential treatments. A 12-member team of doctors, nurses and analytics experts takes upwards of a year to analyze data and build each protocol, said Marc Probst, the chief information officer at the not-for-profit health system based in Salt Lake City. Recently, though, Intermountain teamed with a company that uses artificial intelligence (AI) to do the same work. But AI works faster and more thoroughly, taking just 10 days to develop a protocol that included additional data points not previously identified, Probst said. "The power in that is amazing. We're going to be in the thousands of protocols soon," Probst said, adding that Intermountain is now piloting AI use in building protocols.

Diane Greene, senior vice president of cloud services at Google Inc., speaks during the company's Cloud Next '17 event Photographer: David Paul Morris/Bloomberg I attended Google's annual, enterprise-focused event, Google Cloud Next '17, last week in San Francisco, paying close attention to all the announcements coming out of the three-day event. I attended their industry analyst event as well, held the day before. The conference is Google's chance to showcase their achievements from the past year, as well as announce new products and services within their cloud and collaboration portfolio. Competition for the public cloud and collaboration is intense with giants like Microsoft, Amazon.com Here's my take on some of the key items coming out of Day 1 of the conference--it's a lot, so let's dive in.