#65 - Book Vibes

Unlocking Book Recommendations with Vibes: An Inside Look at the Future of Reading

Discover how hardcover is revolutionizing book discovery through its innovative recommendation system called Vibes. In this episode, we explore the technology behind personalized book suggestions, how Vibes creates tailored recommendations, and what’s coming next for this powerful tool.

Key Topics:

- The concept of book Vibes: understanding the fingerprint of books based on reading data

- How Vibes uses a recommendation engine powered by vector databases and machine learning models

- Behind the scenes of generating book vectors and how cosine similarity finds similar reads

- The process of training the model with millions of books and the importance of probabilistic genres

- How user preferences and collaborative ranking refine recommendations

- The role of genre data, axioms, and World types in shaping book suggestions

- Excluding books and authors from recommendations and the impact of user feedback

- Plans for expanding Vibes’ features, including API access and customization options

- Visualizing vectors and genres to better understand book relationships