Technical Talks

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Reducing Student Loans with Bot-Powered Humans

William Falcon William Falcon | AI Researcher | Facebook / NYU

Learn how NextGenVest is using deep learning to scale human advice over SMS to help Gen Z reduce student loan burdens. Despite the average college graduate owing $37,000 in student loans, they leave $2.7 billion in free money unclaimed because they do not have access to guidance. 

In this talk we’ll start with an overview of state-of-the-art chatbot models and explore their benefits and limitations. This first part will aim to bridge the gap between research state-of-the-art and business practicality. We’ll proceed with a technical overview of our neural-network based model, reward function and design choices from both a technical and business perspective.

We’ll end by showing performance in the wild through our real-time SMS chats and our impact on the broader education system compared to ongoing DOE efforts. We’ll end with a brief discussion about using human-first bots and why AI-assisted human interactions should be human-first.

William Falcon
William Falcon
AI Researcher | Facebook / NYU

William is an AI researcher working on his PhD at NYU and Facebook AI Research. His research focuses on developing new methods for biologically inspired unsupervised learning methods. Before his PhD, he Co-founded AI startup NextGenVest (acquired by Commonbond), led iOS at Bonobos and built products at Goldman Sachs and other companies. He received his BA in Stats/CS/Math from Columbia University.