Doing AI
A Business-Centric Examination of AI Culture, Goals, and Values
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Doing AI
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Narrado por:
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Derek Shoales
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De:
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Richard Heimann
Acerca de esta escucha
When businesses try to "do AI", they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place.
Doing AI explores AI for what it actually is - and what it is not - and the problems it can truly solve. Author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values.
As the chief AI officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help listeners understand AI, avoid common pitfalls, and identify beneficial applications for their companies.
This book is a must-listen for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new "solution" that doesn't solve anything.
©2021 Richard Heimann (P)2021 Ascent AudioLos oyentes también disfrutaron...
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If you want to understand how improve decision making and find out what are the mental models, then keep reading...Do mental models affect an individual’s behavior? This audiobook shows how mental models are intertwined with decision making which is essential for business planning. Mental models are important for: Productivity, professional success, greater happiness, critical thinking, and decision-making. Focus on what really matters, and make complex decisions with speed and confidence.
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1 out of 5 stars
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boring . literally useless
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If you want to make effective and informed decisions, through critical thinking and creative problem solving, then keep reading.... Do you keep jumping to the wrong conclusion? Are you tired of repeatedly making the same mistakes? Do you often find your decisions are based on assumptions rather than knowing the facts? The solution is critical thinking and problem solving, a valuable skill that you can use at work and in your personal life, to develop better decision making skills in order to create a healthier more rational environment.
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Given the large amounts of data we use everyday; whether it is in the web, supermarkets, social media etc., analysis of data has become integral to our daily life. The ability to do so effectively can propel your career or business to great heights. Machine learning is the most effective data analysis tool. While it is a complex topic, it can be broken down into simpler steps, as show in this audiobook. We are using Python, which is a great programming language for beginners. Python is a great language that is commonly used with machine learning.
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5 out of 5 stars
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Lo que los oyentes dicen sobre Doing AI
Calificaciones medias de los clientesReseñas - Selecciona las pestañas a continuación para cambiar el origen de las reseñas.
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Total5 out of 5 stars
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Ejecución5 out of 5 stars
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Historia4 out of 5 stars
- Ted
- 02-21-25
The first half is fantastic
I highly recommend the first half of the book. The second half is good but very repetitive.
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Total5 out of 5 stars
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Ejecución5 out of 5 stars
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Historia5 out of 5 stars
- Christine
- 02-07-24
Brandolini's Law in action
This book is really well done. The introduction breaks apart the various things we might mean when we say AI and how the subfields have developed over time. Then it moves into how to avoid over-complicating our solutions by trying to unnecessarily introduce AI.
I listened to the book, but I want to go back and read a print copy so I can underline passages and highlight key questions and considerations like why do we use human performance as the benchmark for AI? Which human? The best, average?
I wish all the executives with magical thinking around AI would read this book and a few others before the stake their companies future and millions of jobs on buzzword projects, but the anthropomorphized vision of computers remains the dominate narrative.
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