Microprediction: Building An Open AI Network (MIT Press)
A new book by Peter Cotton that argues for a new public utility for artificial intelligence has been named quant book of the year by Rebellion Research.
— Azat Aslanov
WEST PALM BEACH, FLORIDA, UNITED STATES, December 19, 2022 /EINPresswire.com/ — A new book by Peter Cotton argues for a new public utility to drive the cost of bespoke business optimization towards zero. It has been named Quant Book of the Year by Rebellion Research. The book was released by MIT Press in November and featured at the recent MIT AI & Quant Conference held on Dec 15th.
In the new work, Cotton presents an ambitious yet practical alternative to the expensive “artisan” data science that currently drains money from firms. The hope expressed in the book is that businesses might decompose their ongoing operations into commodity quantitative tasks that are then attacked by autonomous, itinerant algorithms authored by anyone.
Cotton operates an example of what the book called a “microprediction oracle” at Micropredition.Org – a self-service API allowing anyone to lure data and models towards their own bespoke business problem. The platform is used to generate predictions of electricity loads, stock volatilities, and other live quantities. It also serves as a way of benchmarking new approaches to time-series prediction, using a Python client library.
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