Explore NVIDIA's Jetson platform for deploying AI at the edge in robotics, video analytics, healthcare, industrial automation, and retail. Dive into the key hardware features of the Jetson family, the unified software stack enabling seamless development to deployment, and the ecosystem facilitating rapid time-to-market. Discover the latest product announcements, roadmap, and success stories from partners in this comprehensive 54-minute video. Gain insights into AI challenges at the edge, Jetson's computer subsystems, unified memory architecture, and software stack including TensorRT and DeepStream SDK. Learn about industrial applications, developer kits, and get answers to questions on topics such as Jetson Nano circuits, smart city implementations, and energy consumption. Understand the roadmap for future developments, hardware partnerships, and performance optimizations for various AI applications.
NVIDIA Jetson: Enabling AI-Powered Autonomous Machines at Scale
Overview
Syllabus
Introduction
Why AI at the edge
Challenges
Complexity Accuracy
Jetson Platform
Jetson Computer
Jetson subsystems
Unified memory architecture
Software stack
Tensor RT
ML4 Benchmarks
Deep Stream SDK
Isaac SDK
Summary
Software
Ecosystem
Success
Future
Industrial
Developer Kits
CTSA Digital
Questions
How do you keep the overview
What circuits are available for Jetson Nano
Which type of smart city
New updates
Applications for Tiny Yellow
Availability of Jetson NX
What is differences between 10W and 5W operation
Energy consumption of Jetson
Google environmental sensor
Max power usage
Carrier boards
Recommendations
Roadmap
Hardware partners
Industrial protocols
Memory Upgrade
OpenCV Performance
Gigabit Ethernet Support
Tensor RT Compiler
Tensor IP
Exploration of different dimensions
Tensorflow
Jetson Nano
Synthetic Data
Conclusion
Taught by
NVIDIA Developer
