Rama Ramakrishnan, Professor of the Practice in Data Science and Applied Machine Learning at the MIT Sloan School of Management, guides us on an exploration of the AI model ChatGPT. The video traces the evolution of ChatGPT from its predecessors, GPT-3 and GPT-3.5. It demystifies the complex mathematical and neural network foundations that enable the model to predict and generate text based on vast amounts of data sourced from the internet.

Through this video, you’ll gain insights into:

The foundational “predict the next word” mechanism that powers GPT models.
The vast training datasets and the role of deep neural networks.
The emergence of unexpected capabilities as the model evolved.
The challenges faced, from generating nonsensical to biased outputs, and the steps taken to mitigate them.
The transition from GPT-3.5 to ChatGPT, emphasizing its conversational prowess.

For more MIT Sloan resources on teaching with generative AI, visit our Resource Hub: mitsloanedtech.mit.edu/ai/.