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Frecuencia de actualización:
every 26 days
Duración media del audio:
28 minutes
Inglés
Estados Unidos
6 episodios
desde 26 de mayo de 2026
episodic

ÚLTIMO EPISODIO 🔗

On this episode of Between Two Joels, Dig Insights AI leaders Joel Armstrong and Joel Anderson argue that synthetic data was never the point. The point is the questions it lets you ask faster and cheaper. Using the not-quite-death of phone research as a guide, they map where synthetic data will act…

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Buscar episodios anteriores de Between Two Joels.

EPISODIOS ANTERIORES

On this episode of Between Two Joels, Joel Armstrong and Joel Anderson map the three-era evolution of synthetic data in market research — from the early LLM gold rush, through the digital-twins era, to where the field actually stands today. Along the way, they share the results of their tests and s…
On this episode of Between Two Joels, Joel Armstrong and Joel Anderson explore the evolution of idea generation methodology. They dig into how idea generation changed from GPT-3-era prompting to a new system that pairs large language models with classical machine learning to score and refine ideas …
On this episode, Joel Armstrong and Joel Anderson dig into synthetic subgroup boosting — how it works, why borrowing data from similar groups can sharpen small samples, and what the bias-variance trade-off has to do with liking cheese in Washington State. They also break down the AI news of the wee…
On this episode of Between Two Joels, Dig Insights AI leaders Joel Armstrong and Joel Anderson dig into one of the most-cited papers in synthetic data research — and ask a simple question: what does 88% accurate actually mean? They unpack how digital twins are built, how accuracy gets measured, and…

01: System 0

· transcripción
On the debut episode of Between Two Joels, Dig Insights AI leaders Joel Armstrong and Joel Anderson break down “System Zero” — a new framework for understanding how AI is reshaping consumer decision-making. All while reacting to the latest AI investment news and debating where people will (and won’…
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