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Microprediction: Building An Open AI Network (MIT Press)
New Book Makes the Case for Cheaper Artificial Intelligence
— Joseph Langsam
WEST PALM BEACH, FLORIDA, UNITED STATES, December 10, 2022 /EINPresswire.com/ — In his new book published recently by MIT Press, Peter Cotton examines the impact of the artificial intelligence (AI) revolution on small businesses and organizations that cannot afford in-house teams of data scientists. Cotton concludes that the world is missing a public utility – a substrate where algorithms, data, and models can self-organize – while companies are missing an important strategic approach that would enable them to benefit from it.
Microprediction: Building an Open AI Network draws on ideas from statistics, reinforcement learning and privacy preserving computation. But the author’s focus is on the central economic problem of machine learning: how to produce and distribute it far and wide at the lowest possible cost.
Peter Cotton is a twenty year industry veteran, and heads data science for institutional money manager Intech Investments. The book is accompanied by code repositories on GitHub focussed on the benchmarking of autonomous algorithms for prediction of time-series, covariance estimation, derivative-free optimization. The author maintains Microprediction.Com, a live platform where anyone can publish data to be predicted and anyone can run an algorithm to predict it.
Joana Donovan
Microprediction LLC
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