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| Deep Learning Necessary for Autonomy/ADAS, Offers Competitive Advantage Computers have been programmed to drive cars autonomously today, but deep learning will be necessary to enable autonomous vehicles that are capable of understanding all of the nuances involved in getting safely from Point A to Point B. Deep learning, or machine intelligence, is where the highest level of development work is taking place to reach a point where the vehicle can flawlessly determine a course of action in context. Analysts say that automakers who do the best at integrating deep learning in a vehicle's architecture will gain a profound competitive advantage. Human and machine interaction is key to creating smarter machines, agreed automakers who recently gathered for the WardsAuto UX Conference in October. That collaboration can help users accept machine errors while teaching the machine to understand human preferences. Automakers, suppliers and technology companies will continue the deep learning discussion on November 9 at the half-day conference entitled WardsAuto FOCUS: AI in Automotive. The event gathers thought leaders inside the auto industry, as well as technology innovators from the West Coast -- people coming to Detroit to share their AI expertise with automotive professionals at the major automakers and suppliers. Sign up now to see these presentations: Automotive Applications for Artificial Intelligence A big-picture look at current and future applications for artificial intelligence from one of the Auto Industryâs top Tier 1 suppliers. â Presented by Dr. David Atkinson, Head of Systems & Technology and Chief Research Scientist for Artificial Intelligence, Continental, Silicon Valley Research & Development Center. Deep Learning Deep learning enables machines to become smarter than humans at specific tasks. Among other things, it can be used to train vehicle guidance systems to recognize other cars, people and bikes more accurately than a human. Hear how Deep Learning will transform the auto industry by creating superhuman levels of perception and performance. â Presented by Bill Veenhuis, senior solutions architect-Automotive Group, NVIDIA. Talking to Machines: Overview on the Role of Personal Assistants and Other Services Using algorithms to converse naturally with machines is becoming important because they simplify the user interface and make it more personal at the same time. AI and neural networks already have become part of driving for those who use smartphone personal assistants through Apple CarPlay and Android Auto. But personal assistants such as IBMâs Watson, Amazonâs Alexa and others are accessing vehicle and driver information to take the relationship to a whole new level â Presented by Christopher C. Bernholt, Sr. Software Developer at Pillar Technology. Natural Language Processing Natural speech recognition is reinventing the relationship between people and technology. Learn how speech software leader Nuance is using a variety of AI technologies to use reasoning and knowledge to fill in blanks that are inferred but not mentioned explicitly in order to create dialog that is more conversational than conventional menu-based voice recognition systems. â Presented by Charles Ortiz, director-Nuance Laboratory for AI and NLP, Nuance Communications. AI, 5G and Connectivity To fully revolutionize the automotive industry, AI requires the speed that only a 5G mobile network can satisfy. But the telecommunication industry must hammer out new standards and update its infrastructure before the ultra-low latency connection can go live. â Presented by Julie Kunstler, Principal Analyst, Ovum Research, Informa. Using AI to Drive Sales How companies are using artificial intelligence to process big data, extract signals and better understand customer needs and behavior. â Presented by Ari Tuchman, Ph.D., CEO and Co-founder, Quantifind. |
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