Chapter
The Future Role of Simulation in Neural Networks
2:06:40 - 2:11:47 (05:07)
As neural networks continue to develop and become more similar to humans, the use of simulation for training set creation and learning new tasks will become increasingly valuable. Although there may still be a domain gap, neural nets are becoming more efficient at learning from structured data and can understand the high level structures in simulations.
Clips
This podcast discusses how the value of simulation to neural nets will be similar to the value of simulation to humans, as neural nets converge to human intelligence.
2:06:40 - 2:08:25 (01:45)
Summary
This podcast discusses how the value of simulation to neural nets will be similar to the value of simulation to humans, as neural nets converge to human intelligence. The conversation explores the usefulness of simulations, including their use in creating training sets, counterfactual or edge case scenarios, and for various professional industries such as video games.
ChapterThe Future Role of Simulation in Neural Networks
Episode#333 – Andrej Karpathy: Tesla AI, Self-Driving, Optimus, Aliens, and AGI
PodcastLex Fridman Podcast
As neural nets become more advanced, they will increasingly become more data efficient at learning new tasks, requiring fewer examples to train additional behaviors.
2:08:25 - 2:11:47 (03:21)
Summary
As neural nets become more advanced, they will increasingly become more data efficient at learning new tasks, requiring fewer examples to train additional behaviors. Pre-training a massive neural net like GPT will become increasingly useful at training any arbitrary new task.