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About the Local Maximum Podcast

The phrase “Local Maximum” is a mathematical term, and it refers to a point at which you need to step down in order to reach new heights. But people - not just points - can get caught in a local maximum. That means they’ve gone as far as they can through one strategy which has gone stale and they need to search for new ideas.

In product design and machine learning, we sometimes ask if we’re in a local maximum, and whether starting from a fresh perspective can lead to better results.

So this podcast is about examining technology, engineering, and social trends through the lense of expanding perspectives and moving beyond the Local Maximum both for ourselves AND for our algorithms.

Sometimes I’ll interview engineers and entrepreneurs that I admire, that have actually built something valuable that most people wouldn’t have thought about, or that have ideas I want to explore further. I go over techniques to understanding the world of AI and Machine Learning that an average person can understand - and I show how to get our algorithms to be more flexible through the same process we use on people. I can also use my unique experience to examine current events.

The world is on the cusp of big changes - it’ll come from transportation, mainly automated cars and trucks. It’ll come from bitcoin and ethereum and all of these cryptonetworks. And we’re still seeing the spread of narrow AI vs general AI, but it’s a really really smart narrow AI we have now.

But I realized I didn’t want to do it alone; and I wanted to do with a community of interested and interesting people. And that’s where this podcast comes in, The Local Maximum.

Max Sklar is a machine learning engineer at Foursquare. He focuses on using machine learning and heuristics to develop new features and products. More recently he has led the development effort of the Marsbot app, a bot that texts local recommendations, and on a new methodology for Ad Attribution - a step forward for the industry.

Max has spoken at a variety of conferences and universities, including the ACM conference on Recommender Systems, the Cambridge Workshop on Urban Data Science, and Talkabot 2016.

He holds a masters degree from NYU in Information Systems, and a Bachelor of Science in Computer Science from Yale. He is also a board member of the Yale Alumni Service Corps, and recently led a volunteer trip to the Fort Mojave Indian Reservation in October.

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