[TechTalk] by OpenAI - Learning Robotic Dexterity

In this talk, Matthias from OpenAI will present the recently published results of their robotics team. They showed that complex and human-like dexterous manipulation can be achieved on a real humanoid hand. They trained their system only on simulated data using large-scale deep reinforcement learning. Still, the system generalizes to the real world, which they achieved through a technique called domain randomization. This talk will not only present their results but will also introduce the fundamental ideas and algorithms behind reinforcement learning as well as domain randomization.
A basic understanding of Machine Learning and simple Neural Networks is recommended.

Matthias Plappert graduated from the Karslruhe Institute of Technology with a Masters degree in Computer Science and works as a research
scientist for OpenAI, where he wrote his master thesis.

Blog: https://blog.openai.com/learning-dexterity/
Paper: https://arxiv.org/abs/1808.00177
Video: https://www.youtube.com/watch?v=jwSbzNHGflM

This event is a co-organization of Hack & Söhne and Karlsruhe.AI
https://hackundsoehne.de/