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Paperback Gary Marcus Was Right: One Neuroscientist's War Against the Trillion-Dollar AI Hype Machine Book

ISBN: B0DZB87N5J

ISBN13: 9798312926347

Gary Marcus Was Right: One Neuroscientist's War Against the Trillion-Dollar AI Hype Machine

The AI hype machine is running at full throttle, but is it leading us towards prosperity, or peril?

In Gary Marcus Was Right, Daniel Vincent Kramer takes you on a gripping journey through the heart of the artificial intelligence industry, exposing the overblown promises, dangerous shortcuts, and fundamental flaws that lie beneath the surface of today's most celebrated technologies. From the rise of large language models like ChatGPT to the relentless pursuit of Artificial General Intelligence (AGI), this book pulls back the curtain on an industry consumed by its own hype.

This book is more than just a critique; it's a call to action. Through the lens of Gary Marcus, one of the industry's most vocal skeptics and a champion of neuro-symbolic AI, Daniel Vincent Kramer reveals why deep learning alone is not enough and why a more balanced, scientifically grounded approach is essential for building AI that truly benefits humanity.

Inside Gary Marcus Was Right, you'll discover:

The truth behind deep learning's "black box" problem and why it limits AI's potential.

How large language models hallucinate plausible-sounding but false information-and why this is more than just a bug.

The dangers of the "AI arms race" among tech giants like OpenAI, Microsoft, Google, and Meta.

Why neuro-symbolic AI offers a better path forward by combining deep learning with logic and reasoning.

Practical insights into how we can move beyond hype to build safer, more ethical, and more effective AI systems.


From Silicon Valley boardrooms to global policy debates, Gary Marcus Was Right takes a hard look at the players driving today's AI frenzy: Sam Altman (OpenAI), Satya Nadella (Microsoft), Dario Amodei (Anthropic), and others-and challenges their vision for our technological future.

The revolution in AI needs a reality check. This is it.

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