Graph Databases and AI

In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually optimize for? Drawing on conversations from across the season, the episode explores engagement, filter bubbles, popularity bias, ... Show More

Where did recommender systems come from, and how do we know when they're actually working? In part one of Data Skeptic's three-part Recommender Systems finale, Kyle traces the field from collaborative filtering and the Netflix Prize to matrix factorization and modern approaches, ... Show More

Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems, the limitations of optimizing purely for accuracy, and how ideas from social ch ... Show More

Graphs, but not as you would expect them: Graph analytics guru Amy Hodler speaks to Jon Krohn about the graph data structure and graph applications, graph algorithms, graph RAG, and graphs as memory systems for AI agents. We can use graphs in a surprising number of ways. Money la ... 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

Today Corey talks with Pranav Maheshwari from The Graph, an indexing protocol for querying networks like Ethereum and IPFS. We'll dive deep into how The Graph works, what it aims to solve, what complications it has faced as it has scaled out to its current state, and where it exp ... Show More

In this episode of the SuperDataScience Podcast, I chat with Vice President of Research at Sentient AI, Risto Miikkulainen. You will hear about the applications of AI across multiple fields, learn about the 2 types of AI - the Evolutionary Algorithms and Reinforcement Learning Al ... Show More

State space models (SSMs), granite models, and Mamba: Dell’s Tyler Cox and Shirish Gupta discuss with Jon Krohn why state space models can process information so efficiently, and how Dell’s AI factory helps enterprises manage custom AI workloads. Hear the latest on the Dell Pro A ... Show More

In this episode of the SuperDataScience Podcast, I chat with the President and Editor at KDNuggets, Gregory Piatetsky-Shapiro. You will hear about the recent advancements in Data Science, learn how Reinforcement Learning can greatly improve AI capabilities, and learn about the no ... Show More