Practical AI GANs, RL, and transfer learning oh my!
Jun 11, 2019
Delve into the fascinating world of generative adversarial networks (GANs) and uncover how they create stunning artworks and music. Explore the power of deep reinforcement learning, where machines learn to navigate complex environments through rewards. Discover the magic of transfer learning, enabling AI models to adapt with minimal data in fields like computer vision. The discussion is enriched by ethical considerations and the human touch needed in AI, making this a captivating journey through the realms of creativity and technology.
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AI Models vs. Methodologies
- Listeners often confuse AI models with methodologies like Reinforcement Learning, GANs, and Transfer Learning.
- These methodologies represent different approaches to utilizing AI models, not distinct model architectures themselves.
Reinforcement Learning Basics
- In reinforcement learning, an agent learns by taking actions in an environment and receiving rewards for desirable outcomes.
- This reward system shapes the agent's policy, guiding it towards optimal behavior.
RL in Robotics
- Chris Benson worked with reinforcement learning specialists at a previous employer.
- These specialists focused on applying reinforcement learning techniques to robotics.