Artificial intelligence’s promise is to change how we work and live. With cognitive applications in healthcare, retail, financial services, manufacturing, and transportation, AI is already transforming industries, saving lives, and delivering efficiencies. But deploying AI solutions isn’t easy. Do you optimize for compute, throughput, power, or cost? How do you manage the data? For the various AI frameworks like TensorFlow, Caffe, Torch, would more and faster training of the models be beneficial? What if you could run AI and BI workloads on one platform and deliver faster and better analytics?
Karthik Lalithraj explains how a GPU-accelerated database helps you deploy an easy-to-use, scalable, cost-effective, and future-proof AI solution that enables data science teams to develop, test, and train simulations and algorithms while making them directly available on the same systems used by end users.
This session is sponsored by Kinetica.
Karthik Lalithraj is a principal solutions architect at Kinetica. With over 18 years of software experience in a variety of roles and responsibilities, Karthik takes a holistic view at software architecture with special emphasis on helping enterprise IT organizations improve their service availability, application performance, and scale. Karthik has successfully helped recruit and build enterprise teams and architect, design, and implement business and technical solutions with numerous customers in various business verticals. Previously, Karthik led the presales big data organization at Terracotta/Software AG. Karthik holds a bachelor’s degree in electronics and communication from the National Institute of Engineering in India.
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