How to Speak Machine : Computational Thinking for the Rest of Us
Book Details
Format
Undefined
ISBN-10
039956442X
ISBN-13
9780399564420
Publisher
Not Stated
Country of Manufacture
US
Country of Publication
GB
Publication Date
Jan 1st, 1900
Weight
360 grams
Dimensions
14.80 x 21.70 x 2.80 cms
Ksh 4,700.00
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A simple, enduring framework for understanding the complex world of AI and machine learning.
“Before you can get machines to do what you want, you’d better learn to speak their language. John Maeda engineers rapprochement between humans and our computational creations in this engaging, enlightening book.”
—Douglas Rushkoff, author of Team Human
As the capabilities of AI and language models like ChatGPT continue to advance, it is more important than ever to understand the implications and potential pitfalls of these technologies.
In this book, John Maeda draws on his extensive experience as one of the world''s preeminent interdisciplinary thinkers on technology and design to provide actionable guidance for businesses, product designers, and policymakers.
Using thoughtful explorations and occasionally whimsical examples, he identifies a framework that describes the key capabilities and pitfalls of any machine learning system, and offers a vision for how they can be used to create inclusive and world-changing products.
This is essential reading for anyone seeking a high-level understanding of how machines “think” and what the future may hold.
“Before you can get machines to do what you want, you’d better learn to speak their language. John Maeda engineers rapprochement between humans and our computational creations in this engaging, enlightening book.”
—Douglas Rushkoff, author of Team Human
As the capabilities of AI and language models like ChatGPT continue to advance, it is more important than ever to understand the implications and potential pitfalls of these technologies.
In this book, John Maeda draws on his extensive experience as one of the world''s preeminent interdisciplinary thinkers on technology and design to provide actionable guidance for businesses, product designers, and policymakers.
Using thoughtful explorations and occasionally whimsical examples, he identifies a framework that describes the key capabilities and pitfalls of any machine learning system, and offers a vision for how they can be used to create inclusive and world-changing products.
This is essential reading for anyone seeking a high-level understanding of how machines “think” and what the future may hold.
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