Low-level task-based AI gets commoditized quickly, and more general AI is decades off. In the meantime, it’s unclear whether new AI startups will be able to succeed or whether the value will instead accrue to Google and Facebook.
While most of the machine learning talent works in big tech companies, massive, timely problems lurk in every major industry outside tech. If you believe the “software is eating the world” hypothesis, then every company in every industry will need to become a tech company.
Bradford Cross explains how vertical AI startups leverage subject-matter expertise, AI, and unique data to deliver their product’s core value proposition. Drawing on his personal experience, Bradford outlines why vertical AI startups are interesting and discusses big problems for the future in different verticals, such as finance, healthcare, transportation, energy, agriculture, and the environment.
Bradford Cross is a founding partner at DCVC, a leading machine learning and big data venture capital fund. Previously, Bradford founded Prismatic, which used machine learning for personalized content ranking and natural language processing for topic classification, and FlightCaster, which used machine learning to predict the real-time state of the global air traffic network using FAA, carrier, and weather data. A hedge fund investor and a venture investor, Bradford started his career working on statistical value and momentum strategies at O’Higgins Asset Management and was a founding partner of Data Collective. He was also a systems engineer and worked on distributed systems at Google. Bradford studied computer engineering and finance at Virginia Tech and mathematics at Berkeley.
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