Chapter
Strengths and Limitations of Using Pixels for Computer Vision in Driving Tasks
1:20:36 - 1:27:35 (06:59)
The use of pixels in computer vision for driving tasks has been the focus of the field for a long time, but it still requires significant engineering efforts in developing the pipeline to effectively train and evaluate neural network-based systems. While vision is the main tool for perceiving the external world, it requires additional reasoning to infer human behavior and common sense physics.
Clips
The key to successful annotation lies in finding the right balance between machine and human annotation.
1:20:36 - 1:23:05 (02:29)
Summary
The key to successful annotation lies in finding the right balance between machine and human annotation. While machines are efficient at tasks such as three-dimensional reconstruction, humans excel at tasks such as recognizing objects in an image.
ChapterStrengths and Limitations of Using Pixels for Computer Vision in Driving Tasks
Episode#333 – Andrej Karpathy: Tesla AI, Self-Driving, Optimus, Aliens, and AGI
PodcastLex Fridman Podcast
The task of autonomous driving relies heavily on computer vision, but it also requires some common sense physics to predict the world beyond just the pixels.
1:23:05 - 1:27:35 (04:30)
Summary
The task of autonomous driving relies heavily on computer vision, but it also requires some common sense physics to predict the world beyond just the pixels. Using pixels as a sensor is cheap and effective, but designing and engineering the entire data pipeline and neural network is a challenging task.