- Gebundene Ausgabe: 256 Seiten
- Verlag: Portfolio Hardcover (30. August 2012)
- Sprache: Englisch
- ISBN-10: 1591844924
- ISBN-13: 978-1591844921
- Größe und/oder Gewicht: 23,1 x 15,7 x 3 cm
- Durchschnittliche Kundenbewertung: 3 Kundenrezensionen
- Amazon Bestseller-Rang: Nr. 55.741 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
Automate This: How Algorithms Came to Rule Our World (Englisch) Gebundene Ausgabe – 30. August 2012
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“[Steiner] excels in bringing a dry subject to life.”
“Algorithms are affecting every field of human endeavor, from markets to medicine, poker to pop music. Read this book if you want to understand the most powerful force shaping the world today and tomorrow.”
—Andrew McAfee, principal research scientist, MIT; coauthor of Race Against the Machine
—Randall Stross, author of Planet Google and The Launch Pad
Über den Autor und weitere Mitwirkende
( The Predictioneer's Game: Using the Logic of Brazen Self-Interest to See and Shape the Future ) und einige mehr, die von auomatischer psychologischer Persönlichkeitsklassifikation, Hochleistungsglasfaserkabeln, computergestützter medizinischer Diagnostik, Datenverarbeitung bei Facebook usw. erzählen.
Obwohl ich solche Themen auch sonst verfolge, war doch einiges für mich neu und spannend. Schwach ist nur das Kapitel über die geschichtliche Entwicklung von Algorithmen. Der Autor hat pflichtbewusst ein paar Bücher gelesen und rattert bekannte Mathematiker wie Gauss und Euler herunter, mehrfach mit dem undifferenzierten Verweis, daß mit deren Erkenntnissen heutzutage Millionen an der Wall Street verdient werden.Lesen Sie weiter... ›
In "Automate this - How algorithms came to rule our world" Steiner managed to interview some of the hidden masterminds - even of companies operating mostly in stealth mode. A creator of an algorithm turning his "child" into a cashcow has no need to tell the world about it! Steiner tells diverse success stories where algorithms really start "to rule the world". Every aspect of life is indeed affected - and any job: lawyers, doctors, psychiatrists, salesmen, journalists, artists, truck drivers, financial businessmen and many other. Steiner brilliantly brings light into the fight for talents between Wall Street and other tech companies. The chapter about psychologic analysis of humans by algorithms was to me the most fascinating. The astounding findings of Kahler and Capers are in Germany nearly unknown and not present in university lectures.
This is a book any person with base knowledge of information technology should read. It covers even the latest developments until end of 2011. Psychologists should as well read "The Process Therapy Model - The Six Personality Types With Adaptations" of Dr. Taibi Kahler directly - available via US-version of amazon.
I do have a vague idea though of how lines of code are taking over important tasks in my world: the Google search engine and algorithms of Amazon or of networks like Linkedin are probably the most important ones affecting my life already, today. Marketing automation is becoming a thing in my industry and as a teacher on writing better copy I've been asking myself how long it might take until machines will take over the writing work anyway – and what part of the process might remain with us, humans.
This book seems "old" (2012) measured by the speed of of current tech developments. But it was a great read for me. Christopher Steiner masterfully made it easy for me to follow along and I love his insights, examples and little stories.
The book has opened up my world quite a bit bringing me a) better understanding, b) less fear of not understanding what the term algorithms stands for, c) an interest in becoming part of the development of this big data industry (I suffer no shortage of ideas). And d) it adds to the strategic thinking for my own business.
Some ideas that I had died a sudden death during the reading of this book because one thing has become very clear to me now: At least in the services industry, work with data and do it the smart way or better don't even call yourself a business person.
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It's also highly offensive that he wrote a 200 page fluffy text on the vast subject of machine learning and put icing on the cake by peppering it with advertisements for companies that he's affiliated with. At the start of chapter 2 he says "all one needs to do is head to Y Combinator's Hackers News message board, which has grown into one of the more infuential Web sites in the world". Not only is this completely false, he received a grant from Y Combinator for his start up, which we know because he included similarly transparent advertisements earlier in the book. Are you kidding me?
It shouldn't come as a huge surprise that someone who wrote a book called "$20/gal..." is more interesting in attracting attention than conveying information. But skip this one. There's no reason to encourage authors to write cash-grab drivel like this.
Automate This is about the stories and business applications of machine learning. It’s a pleasant reading for both people in the field and others. Practitioners will find interesting applications of machine learning, although without any technical details. People outside of the field will get a feeling of what can be done with data mining algorithms.
Out of the second chapter, about the history of man and algorithms, I found the book really enjoying. Steiner’s book is also telling the story of Quants moving from the finance industry to the Silicon Valley. In summary, Automate This is an excellent book about machine learning, without mentioning it (the author uses the word “automated” for machine learning). Highly advised to anyone interested in knowing how machine learning is changing our world.
The author, lacking a more meaningful approach to this subject matter, decided to dramatize it as if to catch our attention. Duly noted, and poorly received.
For the algorithm novice, Steiner gives us hope when he explains why Wall Street was altered by quants who are no longer (thankfully) flocking to that field, and so hopefully they will be able to focus instead on music production, Top 40 hit generation, baseball recruiting, professional level poker playing, medical diagnostics, human psychology, customer experience, and other many areas, which show how much our world can now be dictated by the sophisticated algorithms developed over the last fifty years. In some places, the book reads as a cautionary tale for the college student or young professional looking to find an industry that will continue to grow with human capital instead of machines (hint, it is not medical diagnostics). It also shares success stories, which might point a more experienced algorithm researcher to a unique company or individual expert that have advanced missions in automated computing.
Overall the book is written without too much technical jargon, and it has an easy ready style. At times, it has painstakingly long chapters and it does not often rely on humor to entertain. But for someone looking to learn about the algorithmic transformation of our technological world and gain a sense for how that will only continue to spread, I would recommend Steiner’s book.
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