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Wednesday, October 17 • 10:00am - 10:30am
Lightning Talks

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Surface and Interface — Alan Laidlaw, Home Depot
When the USAF discovered that their planes were crashing because the cockpits weren't shaped for pilots, they went back to the data. They found that the initial specs for pilot dimensions didn't fit a single pilot. The data wasn't wrong, there just wasn't an average pilot. So they told the plane manufacturers to fix it.
The manufacturers came back with adjustable seats. They turned what was previously a surface into an interface.
In order to apply ML, data science and UX need to overlap. This talk explores how to do that in the enterprise.

Gallery Wall Synthesis and Visualization in AR — Tomer Weiss, Wayfair
We present a design tool which allows users to create a gallery wall design, and visualize it in AR. To use our tool, a user selects the wall area to decorate, and an art piece. Then, our system automatically generates a recommendation based on art sampled from a database. The system takes into account common design criteria. With a mobile phone, the user can instantly visualize the resulting layout placed on a wall, browse wall art pieces, and generate new layout suggestions. We demonstrate how our tool can be applied for creating different wall art layouts for different decoration scenarios.

A fashion-aware fashion recommender — Amy Winecoff, Data Scientist at True Fit
This presentation introduces a style recommender for clothing and footwear. Fashion recommendation problems are characterized by sparse user/product interactions, large catalogs of styles, and many new users and products, i.e., the cold start problem. We present a hybrid recommender system that leverages a collaborative filter to decrease data sparsity prior to training a supervised learning algorithm based on user and product features. This addresses data sparsity issues and produces recommendations that are personal and do not require previous user product interactions.

State of AI in Africa — Matt Grasser, Director of Inclusive FinTech at Bankable Frontier Associates
Earlier this year, BFA launched the first-ever report on artificial intelligence as it relates to financial services in Africa and the low-income customer. For financial services providers in Africa, the real value of AI and its forms, such as machine learning, lies in practical applications that can reduce the cost to serve and acquire customers -- creating more viable business models for broader segments of the market. Several financial services providers are already using AI to eliminate business inefficiencies, manage business and customer risk and create more seamless customer experiences. More and more providers, not just the large players, have the opportunity to do the same.

Wednesday October 17, 2018 10:00am - 10:30am EDT
Horace Mann