In April, data-driven publisher Inkitt announced that it is partnering with Tor Books to release the first novel selected by an algorithm for publishing. Here, Inkitt’s founder and c.e.o Ali Alibazaz explains why he believes that AI is reaching a tipping point in the industry – but not in the way you might think.
by Andrew Rhomberg, founder of Jellybooks The upcoming book The Bestseller Code? – ?Anatomy of the Blockbuster Novel is getting a great deal of buzz. Can one genuinely predict what kind of book will become a NYTimes best-seller? The promise of a formula for predicting a best-seller is getting many in the publishing industry and those who write about books excited. Several journalists contacted me for an opinion about the book because of my background in pub tech and reader analytics. Thus I became interested in reading the book and the book’s publisher St. Martin’s Press was kind enough to provide me with an advance reader copy last week. First of all this is a delightful book to read. I would recommend it as both an entertaining and educational read for anybody interested in the business of books. This is not a magisterial work like “Merchants of Culture” by J. Thompson, but a book written for the mass market with lots of anecdotes and examples that readers and authors can relate to. It is a book for a general audience and avoids as far as possible jargon and “academic” language. The “code” is based on some of the latest advances in […]
AI is reaching a tipping point in the industry – but not in the way you might think.
Machine learning can indeed help book publishers predict a bestseller. How exactly is this done? Neil Balthaser explains.
EY’s Hermann Sidhu explains how data analytics is revolutionizing audit and facilitating AI, machine learning, robotics and blockchain.