Remove Book Remove Experimentation Remove Interactive Remove Uncertainty
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CIOs press ahead for gen AI edge — despite misgivings

CIO Business Intelligence

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 141
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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

This thought was in my mind as I was reading Lean Analytics a new book by my friend Alistair Croll and his collaborator Benjamin Yoskovitz. They preserve almost all original intent, but if you read the book, or see the cycle elsewhere, please don''t be surprised to see a slightly different version. KPI: Property bookings.

Metrics 156
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How to Set AI Goals

O'Reilly on Data

My book, AI for People and Business , introduces a framework that highlights the fact that both people and businesses can benefit from AI in unique and different ways. In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time.