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Who’s driving your car?

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Abstract:

The future of autonomous driving (AD) vehicles depends on their AI inference models’ accuracies in correctly detecting and appropriately responding to real-world scenarios. Accuracies improve only with more training and test data. As one (1) test vehicle can generate up to 15 terabytes of big data per hour, developers must contend with potentially petabytes each day. In this webcast, IBM subject matter expert, Denver Hopkins, discusses the data challenges in training AD models, and the hybrid multi-cloud solutions that can address them.

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Speakers

Denver Hopkins

Portfolio Marketing Manager

IBM Systems, Enterprise Storage

Denver Hopkins is a 28-year technology veteran who works to demystify technology and make it more accessible and useful to the people it serves. He possesses a unique blend of marketing and IT experience including roles as a developer, provider, customer and consumer of marketing-focused IT products and services. He has served as a trusted advisor to companies both large and small, helping them make sense of emerging technology and use it more effectively. He is the founder of two startups-- one that developed a digital marketing platform and guided selling solutions for Global 2000 companies, and a digital agency that served the marketing needs of clients in the legal, medical, and financial sectors. Prior to joining IBM, Hopkins was CTO of Root Level Technology, an MSP that provides on-demand server and storage solutions to more than 10,000 customers worldwide. As a Portfolio Marketing Manager at IBM, he works to help IBM partners and customers realize the considerable competitive advantages available to them from the company's storage and software defined portfolio.

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