Artificial Curiosity | a women++ webinar in collaboration with Visium
Build an AI agent that not only plays different games but is also curious!
Humans have been able to achieve incredible feats, such as landing on the moon, exploring the depth of the seas, more than doubling their life expectancy, harnessing the power of wind, etc… The main drivers of such advances have usually been the questions “Why?” and “What if?”. Curiosity has allowed humans to learn more about their surroundings, sometimes doing things that are counterproductive in the short term or for the individual but greatly beneficial in the long run.
The field of Reinforcement Learning explores how a reward can teach an artificial agent to behave in a certain way. During this workshop, we are going to build our own agent that will be able to learn to play different games, but with a twist: we are going to make it curious!
Our agent will not only try to find the short term benefits but will learn new strategies that can give bigger delayed rewards.
What will you learn
- Build an AI agent able to play various games such as Super Mario
- Learn about Reinforcement Learning
- Learn about curiosity and intrinsic motivation
Recommended experience in
- Python (Intermediate level recommended)
- Jupiter notebooks (Know how to use)
- Common ML jargon (To be familiar with it)
Follow along
This session is presented by Visium
Axel Uran
Experienced AI speaker and AI Consultant with a strong history in working in various industries. In 2018, after finishing his master in Computational Neurosciences from the EPFL, Axel joined Visium, working closely with Thibault and Gaétan in helping businesses leverage the ever-growing potential of AI and ML. Prior to that, he worked as a data scientist in a Dutch Neuromarketing company & the digital epidemiology laboratory at the campus Biotech from the EPFL.
Gaétan Ramet
After his Master in Electrical Engineering at EPFL, Gaétan was the first Machine Learning Engineer to join Visium in its mission to democratize AI, successfully leading projects around Anomaly detection, Object Tracking and Generative Models, among others. Beforehand, Gaétan worked on Speech Emotion Recognition at Swisscom.
Thibault Calvayrac
Thibault has been working as a Machine Learning Engineer with Visium for the past two years. He developed and led projects in a wide range of domains, from computer vision and sales forecasting to generative models and document analysis. Previously, he applied deep reinforcement learning at Sony, designing a system which can create novel machine learning systems automatically.
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