ChatGPT, the large language model developed by OpenAI, is changing the way we interact with artificial intelligence. With its ability to generate human-like text, code, poetry, and even perform various technical tasks, it's no surprise that ChatGPT is quickly becoming one of the most popular AI models. In this talk, we'll showcase the mind-blowing capabilities of ChatGPT, demonstrating how it's making our lives easier, smarter, and more efficient. Join us to explore the many exciting possibilities of this revolutionary AI technology.
And Yes, ChatGPT did write this abstract.

In this talk, I'll show you some of the mind-blowing capabilities of ChatGPT, demonstrating how it's making our lives easier, smarter, and more efficient. Join us to explore the many exciting possibilities of this revolutionary AI technology.

ChatGPT, It Will Blow Your Mind

A conversation for handling generative AI in computer science education, particularly programming. We'll tackle concerns about balancing AI with programming fundamentals and discuss the copyright implications for developers. Plus, discover new approaches for navigating the AI dilemma in the classroom while embracing its inevitable ubiquity. 

Generative AI and Computer Science in Higher Education

In this talk, I will cover the science behind ChatGPT. I will discuss the core architecture of chatGPT, the training methodology, and the training data. I will cover the basics of language representation, transformers and large-scale pretraining of language models. I will trace the evolution of GPT from its first version to GPT-3, and then GPT 3.5, their similarity and difference. Finally, I will discuss instructGPT and how it utilizes reinforcement learning to deliver the impressive performance that ChatGPT has today.

In this talk, I will cover the science behind ChatGPT. I will discuss the core architecture of chatGPT, the training methodology, and the training data.

The Science Behind ChatGPT

The talk consist of implementing your own reinforcement learning from human feedback large language model in your own colab notebook, then, discussing what you might expect to see when such an agent is scaled up to the sizes of GPT3.5 and beyond using some of the literature on what exactly emerges with scaling up the parameters and training data. 

implement your own reinforcement learning from human feedback large language model and discus what you might expect to see when such an agent is scaled up using some of the literature on what exactly emerges with scaling up

The Sessions

Will ChatGPT Do X? Build Your Own Mini-ChatGPT and Then Decide for Yourself

The Science Behind ChatGPT

Generative AI and Computer Science in Higher Education

ChatGPT, It Will Blow Your Mind

Everything ChatGPT Virtual

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