Book Review Prediction Machines the Simple Economics of Artificial Intelligence
Learn how evolve your business organization in 2020 by understanding the economics of Bogus Intelligence
Review
Want to learn the economics of Bogus Intelligence?
Hi at that place lovely reader! The following is a review of the book Prediction Machines: The Simple Economics of Bogus Intelligence by Ajay Agrawal, Joshua Gans and Avi Goldfarb. We promise you like it!
Prediction Machines is a short volume by iii top economists with an outstanding AI foundation from the Academy of Toronto.
They view the current wave of Artificial Intelligence machines in the same terms as previous technological revolutions like electricity or the cyberspace, which leads to a very insightful analysis that is refreshing, center-opening, and highly interesting for those that are wondering how Bogus Intelligence might affect their business, and searching for the way to surf this moving ridge to their reward.
The loftier level analysis of this trend of AI results in a simple yet relevant conclusion: this new technology, at the stage it is at in 2020, is mostly an increase in the prediction capacity that we accept at the moment. Car Learning and Artificial Intelligence volition impact our decision making and productivity through putting accurate, inexpensive, and scalable predictions at our disposal.
What does this mean? How can AI impact your business? Y'all ameliorate read the book if you want to find out.
Using numerous examples the book also discusses how this trend has been used by the worlds top companies (Google, Amazon, Baidu, amid others) and past small startups to heighten their profits, it speaks about complements to prediction (similar judgement), what will happen to these complements with AI, the importance of Information, the always present question of whether we will loose our jobs to AI, and topics like monopolies and Artificial General Intelligence.
About the book
Authors
- Ajay Agrawal is a Professor of Strategic Direction and Peter Munk Professor of Entrepreneurship at the Academy of Toronto's Rotman Schoolhouse of Direction. He is as well co-founder of The Next 36 and Side by side AI, co-founder of the AI/robotics company Kindred, and founder of the Create Destruction Lab.
- Joshua Gans is a Professor of Strategic Management and the holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at Toronto's Rotman Schoolhouse of Management. He is a frequent contributor to many major media outlets and as well writes regularly at several blogs like Digitopoly.
- Avi Goldfarb is the Ellison Professor of Marketing at Toronto's Rotman School of Management. He is too Chief Data Scientist at The Creative Destruction Lab, having much of his research covered in the regular press.
Pages: 222 pages of content and 50 pages of notes and references.
Publication yr: 2018
Yous can see an outline of what the economics of Artificial Intelligence is about in the following video:
The post-obit is the official website of the book: https://www.predictionmachines.ai/.
Who is this book for?
This volume has no technical baggage whatsoever, and so anybody who runs a business organisation tin sympathise it and retrieve pretty clear conclusions from information technology. At no point it goes into the mathematical or algorithmic details of Motorcar Learning, or Data Science, and so information technology should exist understandable for everybody.
Information technology is oriented more often than not for business owners, and entrepreneurs that want to see how AI tin impact their environment, all the same, people with experience in the field of AI, Data Scientist and engineers will likewise enjoy it, as information technology treats these 'new' technologies in a refreshing and inspiring fashion.
Summary of Prediction Machines and the Economics of Artificial Intelligence
Fun, full of examples, and very insightful and practical Prediction Machines follows its inescapable logic to explicate how to navigate the changes on the horizon that Artificial Intelligence is opening up. It's impact volition exist profound, so you meliorate be ready for information technology. For us, there is no better way to do this than past reading this profound withal surprisingly elementary book. Enjoy it!
Lastly, you can buy the book on amazon here:
Prediction Machines: The simple economics of Artificial Intelligence
Lastly, this book is a great complement to other not-technical books like Weapons of Math Destruction or if y'all are looking to get a little flake technical only with care, books like The Hundred-Folio Machine learning book. You can find all of them hither:
Enjoy, thank you for reading How to Learn Auto Learning, and have adept intendance!
Other resources you might similar are:
Other resources around this topic are:
- Weapons of Math Destruction by Cathy O'Neil: A volume similar to this ane, roofing the discrimination and problems that arise from the united nations-ethical use of AI.
- Medium Mail: Bias in Bogus Intelligence.
Til' the next time!
Source: https://howtolearnmachinelearning.com/books/artificial-intelligence-books/prediction-machines-the-simple-economics-of-artificial-intelligence/
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