Sep 9–12, 2019

Executive Briefing: Managing AI products

mayukh bhaowal (Salesforce)
11:05am11:45am Wednesday, September 11, 2019
Location: LL21 A/B

Who is this presentation for?

product managers, engineering managers, CTOs, CEOs

Level

Beginner

Description

There is an evolution in Product Management correlated with the shift from the digital revolution to the AI revolution. The AI product managers are rising. As AI and ML eat software, more and more PMs and execs need to level up their skills to manage these products and provide requirements and specifications which will add value to the data engineering and data science teams. This will lead to actually solving customer pain points and not just building a cool technology solution.

Imagine a new recommendation feature. Traditionally a PM would work with a designer and come up with the UI/UX specification around the layout, when and where to show the recommendations, what is the behavior on interacting with the recommendations etc. However, product specifications around UX, layout or interactions are of no value to a machine learning engineer or a data scientist, who would need to operationalize a machine learning system to power such recommendations.

Mayukh Bhaowal discusses the top areas an AI product manager needs to focus on above and beyond a traditional PM including mapping of business problems to machine learning problems, understanding data and labelled data nuances, defining crisp model evaluation criteria, model explainability, ethics/bias and the distinction between research and production when it comes to AI powered products and features.

Prerequisite knowledge

Knowledge of AI product space

What you'll learn

1. Product management is an evolving sport. With AI eating software, it has changed the software PM role fundamentally 2. AI product managers and execs need unique skill sets above and beyond traditional PMs to be successful in the real world building AI/ML products 3. AI product managers and execs need to think differently about customers, their use cases, and how they can translate them into tangible requirements for data engineers and data scientists
Photo of mayukh bhaowal

mayukh bhaowal

Salesforce

Mayukh Bhaowal is a director of product management at Salesforce Einstein working on automated machine learning. Previously, Mayukh worked at startups in the domain of machine learning and analytics. He served as head of product of ML platform startup Scaled Inference, backed by Khosla Ventures, and led product at ecommerce startup Narvar, backed by Accel. He was also a principal product manager at Yahoo and Oracle. Mayukh holds a master’s degree in computer science from Stanford University.

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