Abstract: 

Creativity is now not only a human exclusive.

This workshop is designed to explore how artificial intelligence can be used to generate creative outputs and to inspire technical audiences to use their skills in new and creative ways.

The workshop will also include a series of code exercises designed to give participants hands-on experience working with AI models to generate creative outputs. Some of the exercises we will cover include:

- Generating poetry using NLP models like LSTM and Transformer.

- Creating digital art using computer vision models like Deep Dream and StyleGAN.

- Generating music using GANs and other AI models.

Using reinforcement learning to generate creative outputs that match certain criteria or goals.

Overall, this workshop is ideal for technical audiences who are interested in exploring the creative possibilities of artificial intelligence. Participants should have a basic understanding of machine learning concepts and be comfortable coding in Python. Join us at odsc.com to discover new ways of using AI to create, innovate and inspire!

Session Outline:

We will cover a variety of topics related to creativity in AI, including:

- Introduction to Creativity in AI: An overview of the different types of AI models and how they can be used to generate creative outputs.

- Natural Language Processing (NLP) for Creativity: A deep dive into how NLP can be used to generate creative outputs like poetry, song lyrics, and prose.

- Computer Vision for Creativity: How computer vision can be used to generate creative outputs like art and graphic design.

- Reinforcement Learning for Creativity: How reinforcement learning can be used to train AI models to generate creative outputs that match certain criteria or goals.

- Ethical and Legal Considerations in AI: The ethical implications of using AI to generate creative outputs and how to ensure that these models are used responsibly and ethically.

Tools:
We will use OpenAI gym to try our RL algorithms. OpenAI is a non profit organization that wants to open source all their research on Artificial Intelligence. To foster innovation OpenAI created a virtual environment, OpenAi gym, where it’s easy to test Reinforcement Learning algorithms.

In particular, we will look at popular techniques like Multi Armed Bandit, SARSA and Q-Learning with practical python examples.

Bio: 

Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks. He now works in Thomson Reuters as VP of Labs, and also provides consultancy and training for small and large companies. His previous experience includes being Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through acquisition and an IPO.