building_an_open_ai_network

MIT Press

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Awards & notoriety

The book is rated 5 stars by all reviewers on Amazon … except by one self-confessed dufus.

Reviewers and social media recommendations

Rachid Lassoued, Global Head of Financial Engineering & Risk, Bloomberg

Great initiative and quite innovative framework developed in your platform (and your great book which is certainly one of the most interesting reads I had in 2022)

Oledkssy Lialka, Data Scientist, Kiarna

Microprediction by Peter Cotton is a smart read. The author lays down the foundations of greenfield mass prediction as a service with an economic rationale and a high-level system design vision. The evolution alike we’ve already seen with the cloud infrastructure. The read is dense and packed with statistics, economics, and optimal control, all intertwined into a cohesive and engaging story. Remember to throw it into your weekender bag. Trust me, you will enjoy it.

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Joseph Langsam, PhD, Board on Mathematical Sciences and Analytics, National Academies Sciences, Engineering and Medicine; coeditor of Handbook on Systemic Risk

Cotton is a brilliant, original, ‘out of the box’ thinker with command of his subject. Cotton’s Microprediction is necessary reading for those whose success depends upon data-driven predictions.”

See MIT Press.

Matthew Kolakowski, Data Scientist

If you want to read a book that will open your mind to new horizons on prediction, buy this one now. Peter takes a fantastic approach and examines the possibilities of microprediction. Great book and a must have on your data science reading list.

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Allesandro Chiruzzi, Lead Data Scientist

Peter Cotton might not be ‘the man who solved the market’, but his book sure has a lot of insights and a vision on how to solve many data-related problems companies (of any size) will be facing in the very next future. Microprediction might have a serious and corporate looking front cover, but don’t let that fool you. Inside you’ll find a witty and engaging read, rarely seen in books dealing with such topics.

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Scott Treloar, CIO Noviscient

Very interesting book. I bought two because it is so good

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Azat Aslanov, PhD Senior Data and Systems Analyst, QBE Insuranc

As for a quant that runs aground on the technical clumsiness of the underlying data pipelines world of today, the brilliant exploration of fascinating novel ideas is a breath of fresh air: from statistical crowd-sourcing to interplay between software-engineered oracles and reinforcement learning to temporal difference.

See full review in Goodreads.

Michael Tselman, AI architect and senior engineer

A fascinating, different, thought provoking view and proposal for predictive Data Science

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Chris Hanlon, CFO at DirectBooks

Masterful

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Mark Trinquero. AWS Solutions Architect.

Excellent read (note: You may not agree with every point made) Peter’s deep knowledge of AI/ML/DS domains, combined with expertise in crowdsourcing & belief in the fundamental power of markets provide a very solid argument for building open AI networks that can serve as public utility (creating novel approaches that can even outperform “SOTA” models)

See amazon reviews.

Vacslav Glukov, AI Research, Engineering

You may agree or disagree with some points, it may take some time to get used to the author’s style (for those who never read Peter’s texts before). But - what a joy!

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Robert Carver, Writer and Trader.

Visionary book

See full review in Risky Finance

Anon

Brilliant book

From amazon reviews.

Anon

Those expecting bland generalization to sell another “AI book” for the heck of it are in for a shock.

amazon reviews.

Henry Elgrissy, Defindor

GO BUY THE BOOK. It’s very good

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Curtis Raymond, Data Science Manager, Priceline

This is definitley one of my favorite books!!

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Graham L. Giller, Phd Author of Adventures in Financial Data Science

Microprediction aims to disrupt what Cotton has coined the ‘artisan data science’ economy and to bring the cost of all prediction to zero.

See MIT Press

Prof William T. Ziemba, University of British Columbia (Emeritus); Distinguished Visiting Research Associate, London School of Economics

Peter Cotton surveys the advantages, costs, and pitfalls involved in the real-time crowdsourcing of data and artificial intelligence. Readers will explore the frontier of this increasingly popular and valuable modeling approach, catching a glimpse of where it might someday lead.

See MIT Press.

Anon

Important contribution to development of real world applied AI/ML at scale.

From amazon reviews.

George M George

Highly recommend Peter Cotton’s recent book on microprediction! Great read, can’t agree more, and looking forward to the microprediction network becoming more entrenched in reality.

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