Data Skeptic26 Joulu 2025

Video Recommendations in Industry

In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog "Silence Nogood." They explore the intersection of human curation and machine learning in content discovery, discussing the concept of "algatorial" curation—where algorithms and editorial expertise work together. Key topics include the cold start problem, why every metric is just a "proxy metric" for what users actually want, the challenge of filter bubbles, and the importance of balancing familiarity with discovery. Cory shares insights on why TikTok's algorithm works so well (clean data and massive interaction volume), the crucial role of homepage curation, and how human curators help by contextualizing content, cleaning data, and identifying positive feedback loops that algorithms might miss.

The conversation covers practical challenges like measuring "surprise and delight," the content deluge created by democratized creation tools, and why trust in tech companies is essential for better personalization. Cory emphasizes that discovery is "a good type of friction" and explains how the CODE framework (Capture, Organize, Distill, Express, plus Analysis) guides professional curation work. Looking to the future, they discuss the need for systems thinking that creates narrative connections between content, the potential for conversational AI to help users articulate preferences, and why diverse perspectives beyond engineering are crucial for building effective discovery systems. Resources mentioned include the newsletter "Top Information Retrieval Papers of the Week" and Notebook LM for synthesizing research.

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Fault Tolerant Distributed Gradient Descent

Nirupam Gupta, a Computer Science Post Doctoral Researcher at EDFL University in Switzerland, joins us today to discuss his work "Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent...

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Decentralized Information Gathering

Mikko Lauri, Post Doctoral researcher at the University of Hamburg, Germany, comes on the show today to discuss the work Information Gathering in Decentralized POMDPs by Policy Graph Improvements. Fol...

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Leaderless Consensus

Balaji Arun, a PhD Student in the Systems of Software Research Group at Virginia Tech, joins us today to discuss his research of distributed systems through the paper "Taming the Contention in Consens...

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Automatic Summarization

Maartje ter Hoeve, PhD Student at the University of Amsterdam, joins us today to discuss her research in automated summarization through the paper "What Makes a Good Summary? Reconsidering the Focus o...

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Gerrymandering

Brian Brubach, Assistant Professor in the Computer Science Department at Wellesley College, joins us today to discuss his work "Meddling Metrics: the Effects of Measuring and Constraining Partisan Ger...

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Even Cooperative Chess is Hard

Aside from victory questions like "can black force a checkmate on white in 5 moves?" many novel questions can be asked about a game of chess. Some questions are trivial (e.g. "How many pieces does whi...

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Consecutive Votes in Paxos

Eil Goldweber, a graduate student at the University of Michigan, comes on today to share his work in applying formal verification to systems and a modification to the Paxos protocol discussed in the p...

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Visual Illusions Deceiving Neural Networks

Today on the show we have Adrian Martin, a Post-doctoral researcher from the University of Pompeu Fabra in Barcelona, Spain. He comes on the show today to discuss his research from the paper "Convolut...

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