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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

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Bringing an AI Product to Market

O'Reilly on Data

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

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Embracing Generative AI in health: focus on adoption, execution, outcomes and the human side

CIO Business Intelligence

These include capturing clinical encounters and summarising interactions such as past medical histories and health recommendations, providing patients with tailored educational materials and follow-up care recommendations, and reducing wait times by identifying patients most in need of care and targeting them with personalised coaching.

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Expectations vs. reality: A real-world check on generative AI

CIO Business Intelligence

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times. What are you measuring?

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Assembly required: 8 myths about knowledge management debunked

CIO Business Intelligence

This knowledge, generated through observation, reflection, study, and social interaction, led to a new companywide policy: “Let the grinder warm up for 15 minutes,” resulting in millions of dollars of extra profit at no additional cost. Serendipitous interactions are important for creative, innovative, or nonformulaic activities.

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Generative AI’s change management challenge

CIO Business Intelligence

And while 68% of leaders believe their companies have implemented adequate measures to ensure responsible use of AI, only 29% of their frontline employees feel that way. There are other ways in which employees’ concerns about AI is unevenly distributed, too. Leaders are more likely to be optimistic, and frontline workers concerned, BCG found.

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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

Chatbots cannot hold long, continuing human interaction. Traditionally they are text-based but audio and pictures can also be used for interaction. They provide more like an FAQ (Frequently Asked Questions) type of an interaction. Consequently, they can have extended adaptable human interaction. Industry 4.0