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520: The future of AI in product management – with Mike Todasco

Product Innovation Educators

Mike brings valuable insights about the revolutionary transformation of product development through artificial intelligence. The Future of AI in Product Development: Team Collaboration In our discussion, Mike shares an exciting vision of how AI will transform team collaboration in product development.

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Building Resolution Bot: How to apply machine learning in product development

Intercom, Inc.

We are at the start of a revolution in customer communication, powered by machine learning and artificial intelligence. At Intercom, we have taken advantage of these technologies relatively early. It’s also easy to over- or under- invest in the technology. The cupcake approach to building bots.

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I Have Waited 20 Years to Build This. Meet Enola, your Super-Analyst

Piyanka Jain

When I built my first AI model back in 2002, as part of my master’s thesis, I couldn’t have imagined the GenAI-native world we live in today. Back then, artificial intelligence was mostly theoretical, and building even a simple agent required weeks of work and heaps of computing power. No back-and-forth.

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The Strategy Stack: Connecting Business, Product, and Technology Strategy

Roman Pichler

To ensure that the right technologies are applied, you’ll benefit from using a technology strategy. The company took the strategic decision to heavily invest in artificial intelligence and now uses AI to help Office users be more productive. [1] Similarly, the technology strategy is directed by the business strategy.

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519: Product verification, most important of the 19 activities of product management – with Nishant Parikh

Product Innovation Educators

Drawing from his 20+ years of technology experience and extensive research, Nishant shared insights about how these activities vary across different organizational contexts – from startups to enterprises, B2B to B2C, and Agile to Waterfall environments.

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Why Machine Learning Solutions are Difficult to Implement without Machine Learning Operations?

The Product Coalition

According to Gartner , 85% of machine learning solutions fail because they use raw data. Data scientists work in isolation from operations specialists, and enterprises spend up to three months deploying an ML model. In this article, we will tell you what MLOps is and why businesses need to implement machine learning solutions.

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5 Machine Learning Lessons for Product Managers

Mind the Product

Artificial intelligence (AI) is probably the biggest commercial opportunity in today’s economy. We all use AI or machine learning (ML)-driven products almost every day, and the number of these products will be growing exponentially over the next couple of years. What does it mean for us as product managers?