What if you could QA everything and make your best employees 10–100x more efficient? In the past two years in the market, Dell EMC has realized some key things about providing AI value. Engineers and executives want AI to do more than researchers typically consider. Business leaders want AI to consume all of the data that matters (images, audio, video, text, structured, etc.). Businesses also want AI to get smarter “automagically.”
Ben Taylor shares real use cases of business transformation and realized value in production using deep learning and discusses some of the executive conversations and behaviors Dell EMC is seeing in the market. You’ll get a sense of what the state of the art looks like across multiple industries and see what is actually being done versus what is still a toy problem. Along the way, Ben outlines the top reasons why the majority of AI projects fail to ship value and touches on concerns around IP and AI liability (i.e., automated adverse impact).
This session is sponsored by Dell EMC.
Ben Taylor is a cofounder at Ziff.ai, delivering automated deep learning into production. Ben has over 14 years of machine learning experience and is known for pushing the boundaries for what is possible with deep learning, including predicting country of origin, genetic haplogroups from a face, and even the ranking of ABC’s The Bachelor contestants. Previously, he worked in the semiconductor industry for Intel and Micron in photolithography, process control, and yield prediction and as a Wall Street quant building sentiment stock models for a hedge fund trading the S&P 1500 on news content on a 600 GPU cluster. Ben left finance and the semiconductor industry to work for Sequoia-backed startup HireVue, where he led the company’s machine learning efforts around digital interview prediction and adverse impact mitigation.
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