Fraud Detection with Graphs

In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling attacks to explainable recommendations and user-selected algorithms, we look at wha ...  Show more

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

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 episode nine we talk with George Dahl, of  the University of Toronto, about his work on the Merck molecular activity challenge on kaggle and speech recognition. George recently successfully defended his thesis at the end of March 2015. (Congrats George!) We learn about how net ...  Show more

Our guest today is Samuel Cohen, PhD student at University College London (UCL) and visiting research scientist at Facebook AI Research (FAIR). In our conversation, we first dive into Samuel's first experience in AI, an internship at Check Point Software Technology where he devel ...  Show more

Thanks to machine learning and artificial intelligence, programs that used to take a week can now quickly search 50,000 IP addresses for vulnerabilities in organisations like yours to get into. Reformed Hacker and Brand Ambassador for CTRL Group Bastien Treptel speaks with Associ ...  Show more