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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

How synthetic data can accelerate iteration before real users interact with the system. If the student finds the interaction helpful. Keeping the goal of finding the interaction helpful but recognizing that this contains a lot of other concerns, such as clarity, concision, tone, and correctness. How will you measure success?

Testing 174
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Only engaged service teams can deliver next-level customer loyalty in an era of uncertainty

CIO Business Intelligence

They’re people — each with their own unique circumstances at home, families to support, and worries about the uncertainty that comes with a volatile global pandemic. In order to do that, team needs must be addressed with empathy and understanding — not unlike how agents themselves are expected to approach each customer interaction.

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Waterfall to Agile: A Necessary Mindset Shift For Business Analysts

BA Learnings

I tend to describe the agile approach as a way of working; A targeted way of working that allows us to make changes, respond to customers’ needs and manage uncertainty with minimal delays, and without needing to wade through “red tape”. From Direct Interaction With Multiple End Users To Product Owners.

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What your CFO really needs in periods of economic uncertainty

CIO Business Intelligence

The pressure is on to navigate economic uncertainty. Regardless of your company’s investment posture during this period of instability, interactions with the CFO have likely increased and become more consequential in the last few months. To effectively traverse these interactions, CIOs must start with empathy.

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Easily Build an Optimization App and Empower Your Data

Speaker: Gertjan de Lange

If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. Uncover how an interactive web application can be built on top of your model. Don't let uncertainty drive your business.

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Uncertainties: Statistical, Representational, Interventional

The Unofficial Google Data Science Blog

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

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How to Set AI Goals

O'Reilly on Data

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).