Remove Events Remove Experimentation Remove Risk Remove Uncertainty
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? Those F’s are: Fragility, Friction, and FUD (Fear, Uncertainty, Doubt). encouraging and rewarding) a culture of experimentation across the organization. Test early and often.

Strategy 289
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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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How to create a culture of innovation

CIO Business Intelligence

Prioritize time for experimentation. It requires bold bets and a willingness to persevere despite setbacks, criticism, and uncertainty,’’ wrote McKinsey senior partners Laura Furstenthal and Erik Roth in a recent blog post. “By Here, they and others share seven ways to create and nurture a culture of innovation.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. The AGI would need to handle uncertainty and make decisions with incomplete information.

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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 trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions.

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Estimating causal effects using geo experiments

The Unofficial Google Data Science Blog

How can we connect an event of purchase to the event of perceiving the ad if the purchase does not happen immediately? A geo experiment is an experiment where the experimental units are defined by geographic regions. The expected precision of our inferences can be computed by simulating possible experimental outcomes.