ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community. ODSC West 2019 is one of the largest applied data science conferences in the world. Our speakers include some of the core contributors to many open source tools, libraries, and languages. Attend ODSC West 2019 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.

It's karaoke-rehearsal time at Knollwood Military Retirement Community, a 300-bed facility tucked away in a leafy corner of northwest Washington, D.C. Knollwood resident and retired U.S. Army Colonel Phil Soriano, 86, has hosted the facility's semi-monthly singalongs since their debut during a boozy snowstorm happy hour in 2016. For the late August 2019 show, he'll share emcee duties with a special guest: Stevie, a petite and personable figure who's been living at Knollwood for the last six weeks. Soriano wants to sing the crowd-pleasing hit "YMCA" while Stevie leads the crowd through the song's signature dance moves. But Stevie is a robot, and this is harder than it sounds. "We could try to make him dance," says Niamh Donnelly, the robot's lead AI engineer, though she sounds dubious. She enters commands on a laptop.

LA JOLLA--(October 7, 2019) Father of genetics Gregor Mendel spent years tediously observing and measuring pea plant traits by hand in the 1800s to uncover the basics of genetic inheritance. Today, botanists can track the traits, or phenotypes, of hundreds or thousands of plants much more quickly, with automated camera systems. Now, Salk researchers have helped speed up plant phenotyping even more, with machine-learning algorithms that teach a computer system to analyze three-dimensional shapes of the branches and leaves of a plant. The study, published in Plant Physiology on October 7, 2019, may help scientists better quantify how plants respond to climate change, genetic mutations or other factors. "What we've done is develop a suite of tools that helps address some common phenotyping challenges," says Saket Navlakha, an associate professor in Salk's Integrative Biology Laboratory and Pioneer Fund Developmental Chair.

By the time today's youth retire, or perhaps sooner, they might see artificial intelligence and machine learning change just about everything in the fab shop. There's an old saying in manufacturing: Automation is only as good as what you tell it to do. Richard Boyd has spent a career proving this statement wrong. Boyd has worked with Hollywood studios and computer gaming companies; launched Virtual World Labs that concentrated on virtual reality, augmented reality, and artificial intelligence; and then sold that company to Lockheed-Martin, where he worked for a time before striking out on his own again. A speaker at this year's FABTECH show in Chicago, Boyd is founder and CEO of Tanjo (rhymes with "bongo"), a Carrboro, N.C., company specializing in AI and machine learning.

Chris Moody knows a thing or two about the universe. As an astrophysicist, he built galaxy simulations, using supercomputers to model the way the universe expands and how galaxies crash into one another. One night, not long after he'd finished his PhD at UC Santa Cruz, he met up with a few other astrophysicists for beers. But that night, no one was talking about galaxies. Instead, they were talking about fashion.

Artificial intelligence can make it nearly impossible for fraudsters to make a false claim appear real, the founder of an A.I. vendor suggests. If an auto insurance claim is fraudulent, A.I. software could pick up on that as long as it has enough data about other fraudulent – and legitimate – claims, said Gary Saarenvirta, founder and CEO of Toronto-based Daisy Intelligence. Daisy's software is designed to detect "outliers," or things that are out of the ordinary. Insurers tend not to share their full definition of a "normal" claim. As a result, it is actually impossible for someone to manufacture a claim that also sits in the middle of what the insurer says is normal in every way, Saarenvirta told Canadian Underwriter in an interview.

Readers familiar with our work may want to skip to the Comparing Details heading below. Not because "Technical Analysts" see patterns of past price changes in the stock which may currently fit some part of their folklore and could stir up temporary trading interest. That sector of attention among the investment establishment has, in over 50 years of my observation, consistently failed to provide reliable profitable evidence of the value of studying centuries of stock prices by looking at them in the rear-view mirror. If studying the past can provide some reliable means of dealing with future events, then Artificial Intelligence gets morphed into genuine intelligence thru learning. Our understanding of global and local weather appears to be in this process.

The "ICART 2020 12th International Conference on Agents and Artificial Intelligence" conference has been added to ResearchAndMarkets.com's offering. The purpose of the International Conference on Agents and Artificial Intelligence is to bring together researchers, engineers, and practitioners interested in the theory and applications in the areas of Agents and Artificial Intelligence. Two simultaneous related tracks will be held, covering both applications and current research work. One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence.

As a general partner at a company that helps Israeli companies penetrate new markets and an advisor to companies on go-to-market strategies, I see remarkable innovation from startups, but I also see an astonishing lack of adoption and fear of artificial intelligence (AI) within companies. In the sales and marketing departments, specifically, I see this as a huge disadvantage. Here is why -- and some steps you can take today to start adopting AI within your organization. Let's imagine Amy, a salesperson in an enterprise SAAS company. Her days used to consist of a good amount of administrative work, manually entering data into Salesforce, looking for potential customers, cold calling, sending emails and scheduling meetings -- many times without any results.

AI is constantly in the news these days, identifying prospects for the technology doing both good and bad. One topic that's generating a lot of buzz is the use of AI for creating "deepfakes," a term originally coined in 2017. Deepfakes uses neural networks to combine and superimpose existing images and videos onto source images or videos using a deep learning technique known as generative adversarial networks (GANs). Three of the most common deepfakes techniques are known as "lip-sync," "face swap," and "puppet-master." These techniques, however, can create a disconnect that may be uncovered by a clever algorithm as a way to combat deepfakes.