#28: Intro to Convolutional Neural Nets and Implications of Deep Learning and AI
Artificial Intelligence has entered a great age of productivity, with massive strides in Computer Vision, Natural Language Processing and Task Learning being enabled by the exponential growth in data availability and the computing power enabled by General Purpose GPU (GPGPU) computing. Developers can now create near state of the art AI applications on their laptops.
This talk will cover one of the main tools in deep learning and AI: Convolutional Neural Networks (CNN), how to build one, and how to apply it to a problem like handwriting recognition. It will then explore some of the current problems and approaches in the field of AI such as self driving cars, machine translation, and robotics.
Speaker - Naren Dasan. Naren is an engineer at NVIDIA Automotive Division. He is currently working on systems for real time execution of neural networks on embedded platforms for autonomous vehicles. Naren's research interest are in Robotics, Computer Vision, and Artificial Intelligence. He has published research in Object Reconstruction and Recognition and Swarm Robotics. Naren is a senior in Computer Engineering at University of Illinois Urbana-Champaign.