Talk Abstract: Deep Learning gets Bigger: Larger Models, Better Distribution, and an end-to-end workflow for data science. What’s changing in machine learning and deep learning? The increasing need for larger models and memory to handle high definition video, large data sets, and complex models. Open sourced large model support, accelerated machine learning and where that expands what’s available today.
Bio: Scott Soutter is a Global Offering Manager with the IBM Cognitive Systems business, with responsibility for solutions in Deep Learning / Artificial Intelligence and High Performance Computing. Within this role, Scott has worked directly with governmental agencies, scientific and research communities, and commercial customers to incorporate novel approaches to applied artificial intelligence to the most complex compute problems globally. Previously, Scott was a global technical sales manager with IBM’s Software Defined Infrastructure business where he led a team of Global Solution Architects with expertise in cluster computing, high performance file systems, and complex industry architectures. During his twenty year career with IBM, Scott has been a global cluster sales executive for High Performance and Technical Computing, a technical architect for IBM UNIX systems sales, and a business development executive who helped build IBM’s largest x86 OEM customer. Scott holds a BA degree in Anthropology, and an MBA with a focus on Organizational Change. Scott Soutter resides in Portland, Oregon, with his family. In his spare time he enjoys fly fishing, amateur photography, and recreational swimming.