Generator AI & Machine Learning Speaker Series
April 8, 2025. Refreshments at 4pm. Talk begins promptly at 4:30pm.
For: Everyone
Olin Hall Classroom #120
"Encoder-Only Transformers, the Unsung Hero of the AI Revolution" with Josh Starmer
Fourth in a series of technical experts in the area of ML from the corporate sector invited to present to Babson community (in layman’s terms) on the use of ML in their organizations. The scope is to enlighten the general audience, consisting of students and faculty, on the use of technical ML tools but in a way that is understandable and intuitive rather than technical.
Our visiting speaker for this event will be Josh Starmer, the creator and host of the YouTube Channel StatQuest with Josh Starmer, the best-selling author of The StatQuest Illustrated Guide to Machine Learning as well as The StatQuest Illustrated Guide to Neural Networks and AI, and most recently the creator and teacher of the Coursera MOOC Attention in Transformers, featured by Andrew Ng.
Josh is renowned for his exceptional, engaging style in simplifying complex concepts in data science, machine learning, and statistics, making them clear and understandable without losing technical rigor. His talent for breaking down technical topics has earned him a substantial following of over 1.3 million subscribers on his channel. This session promises to be highly valuable for anyone interested in AI, machine learning, or data science
Although more people are familiar with generative AI tools based on Decoder-Only Transformers like ChatGPT, Encoder-Only Transformers, like BERT, can be much more useful. Encoder-Only Transformers are the backbone for RAG (retrieval augmented generation), sentiment analysis and classification problems, and clustering. In this talk, we'll describe how Encoder-Only Transformers work and discuss business use cases.
Contact Davit Khachatryan with any questions.
