Customizing a Graph Solution

Ekaterina (Kat) Fedorova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively coordinate to game recommendation algorithms. Kat's research reveals surprising findings: algorithmic "protest movements" can paradoxically he ...  Show more

Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose between mainstream and niche algorithms. His research shows specialized recommenders improve utility for niche users while raising questions abo ...  Show more

SummaryIn this episode of the Data Engineering Podcast Prashanth Rao, an AI engineer at KuzuDB, talks about their embeddable graph database. Prashanth explains how KuzuDB addresses performance shortcomings in existing solutions through columnar storage and novel join algorithms. ...  Show more

In this conversation, Jillian Forde interviews Dave Bechberger, Principal Graph Architect at AWS, where they talk through the fundamentals of graphs and their applications. This is a wide ranging conversation on graphs from their use cases in generative AI, choosing between Amazo ...  Show more

SummaryIn this episode of the AI Engineering Podcast Mark Brooker, VP and Distinguished Engineer at AWS, talks about how agentic workflows are transforming database usage and infrastructure design. He discusses the evolving role of data in AI systems, from traditional models to m ...  Show more

In this episode, we explore foundational algorithms and data structures that every developer and computer science enthusiast should know. Covering everything from Binary Search Trees (BSTs) to advanced concepts like Dynamic Programming and Greedy Algorithms, this episode is packe ...  Show more