Remove Experimentation Remove Machine Learning Remove ROI
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What you need to know about product management for AI

O'Reilly on Data

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

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How to Set AI Goals

O'Reilly on Data

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. They don’t automatically generate revenue and growth, maximize ROI, or keep users engaged and loyal. automated retirement portfolio rebalancing and maximized ROI). Conclusion.

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Machine Learning Product Management: Lessons Learned

Domino Data Lab

Machine Learning Projects are Hard: Shifting from a Deterministic Process to a Probabilistic One. Over the years, I have listened to data scientists and machine learning (ML) researchers relay various pain points and challenges that impede their work. Product Management for Machine Learning.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

It is also important to have a strong test and learn culture to encourage rapid experimentation. What do you recommend to organizations to harness this but also show a solid ROI? Given enough trials and data, Machine Learning techniques are likely to add great value in the forecasting process. It is fast and slow.

Insurance 250
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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

People have been building data products and machine learning products for the past couple of decades. ML apps needed to be developed through cycles of experimentation (as were no longer able to reason about how theyll behave based on software specs). This isnt anything new. and immediately start on 1.1.

Testing 174
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Is the gen AI bubble due to burst? CIOs face rethink ahead

CIO Business Intelligence

Determining the ROI for “ubiquitous” gen AI uses, such as virtual assistants or intelligent chatbots , can be difficult, says Frances Karamouzis, an analyst in the Gartner AI, hyper-automation, and intelligent automation group. CIOs need to be able to articulate the business value and expected ROI of each project.

ROI 143
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The CIO’s 2024 AI playbook

CIO Business Intelligence

For enterprise executives in 2024, that means right-sizing those expectations and getting to work: justifying the right use cases, forming teams, and tracking progress and ROI. After a year of frenzied experimentation and investment, executives will have to identify truly valid use cases (and ROI) for AI in 2024.

ROI 105