Varsity A/B Testing

Varsity A/B Testing

When you want to understand if doing something causes something else to happen, like if a change to a website causes and dip or rise in downstream conversions, the gold standard analysis method is to use randomized controlled trials. Once you’ve properly randomized the treatment and effect, the analysis methods are well-understood and there are great tools in R and python (and other languages) to find the effects. However, when you’re operating at scale, the logistics of running all those tests, and reaching correct conclusions reliably, becomes the main challenge—making sure the right metrics are being computed, you know when to stop an experiment, you minimize the chances of finding spurious results, and many other issues that are simple to track for one or two experiments but become real challenges for dozens or hundreds of experiments. Nonetheless, the reality is that there might be dozens or hundreds of experiments worth running. So in this episode, we’ll work through some of the most important issues for running experiments at scale, with strong support from a series of great blog posts from Airbnb about how they solve this very issue. For some blog post links relevant to this episode, visit lineardigressions.com

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Episoder(323)

Constitutional AI

Constitutional AI

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A Data-Driven Reality Check on AI in Business (Interview with Tom Davenport, Babson College)

A Data-Driven Reality Check on AI in Business (Interview with Tom Davenport, Babson College)

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Understanding AI Text Watermarking

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Better Know a Benchmark: Humanity's Last Exam

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A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

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10 Aug 33min

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

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3 Aug 25min

Distillation, or, How to Steal a Model

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27 Jul 23min

Invisible LLM Failures and AI Fluency with Chris Potts (Stanford)

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What happens when a Stanford linguistics professor turns his attention to AI chatbots — and the surprisingly invisible ways humans misunderstand them? Chris Potts joins the show to unpack the hidden f...

20 Jul 41min

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