The Intelligence Ceiling : What Actually Limits AI - and the One Question That Decides How Far Machine Minds Can Go
Language: English
Published by Amazon Digital Services LLC - Kdp Aug 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 26.55
Quantity: 2 available
Add to basketItem description from seller
Neuware - Everyone is mapping what AI can do. Almost no one is mapping what it can't ->The Intelligence Ceiling is a field guide for leaders who have to makeconsequential bets on AI while the ground keeps shifting: founders, executives, investors, and the operators everyone turns to when a new modeldrops. It refuses both the hype and the panic. Instead, it draws the hardlines that will actually determine where machine intelligence stops, stalls, or surprises us - and shows you how to build a strategy on foundations that>The book maps four hard ceilings on AI and the one open question that sits>- The physical ceiling - the energy, thermodynamic, and infrastructure limitsno algorithm can outrun.- The computational ceiling - what complexity theory and the mathematics ofintelligence say scaling can and can't reach.- The economic ceiling - where value actually migrates as AI commoditizes, andwhy being an 'AI adopter' is not a durable advantage.- The governance ceiling - how the EU AI Act and the geopolitics of chips andenergy constrain what gets built, and by whom.- The open question - whether a machine can possess genuine agency orexperience, where quantum computing really fits, and why the honest answer is>What sets this book apart is calibration. Every claim is labeled: establishedscience, reasonable speculation, or the author's own defensible bet. It neverpretends an open question is closed. And it's written by an operator who worksinside the live AI economy and has spent two decades building high-performance>You won't finish it with certainty. You'll finish it with something moredurable: a first-principles way of thinking about machine intelligence thatholds up in a boardroom, a due-diligence call, or a strategy offsite - andthat makes you the most clear-eyed voice in the room, not the most enthusiasticor the most alarmed, but the most accurate.…
Seller Inventory # 9798189627910
- Title
- The Intelligence Ceiling : What Actually Limits AI - and the One Question That Decides How Far Machine Minds Can Go
- Author
- Jake Shannon
- Publisher
- Amazon Digital Services LLC - Kdp Aug 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798189627910
- Item weight
- 222 grams
- Dimensions
- 229x152x9 mm
- Series
- Book 1 of 2: Mental Self-Defense Series
and that boundary is where the real strategic edge lives.
The Intelligence Ceiling is a field guide for leaders who have to make
consequential bets on AI while the ground keeps shifting: founders,
executives, investors, and the operators everyone turns to when a new model
drops. It refuses both the hype and the panic. Instead, it draws the hard
lines that will actually determine where machine intelligence stops, stalls,
or surprises us — and shows you how to build a strategy on foundations that
don't go stale every quarter.
The book maps four hard ceilings on AI and the one open question that sits
above them all:
- The physical ceiling — the energy, thermodynamic, and infrastructure limits
no algorithm can outrun.
- The computational ceiling — what complexity theory and the mathematics of
intelligence say scaling can and can't reach.
- The economic ceiling — where value actually migrates as AI commoditizes, and
why being an "AI adopter" is not a durable advantage.
- The governance ceiling — how the EU AI Act and the geopolitics of chips and
energy constrain what gets built, and by whom.
- The open question — whether a machine can possess genuine agency or
experience, where quantum computing really fits, and why the honest answer is
still "we don't know."
What sets this book apart is calibration. Every claim is labeled: established
science, reasonable speculation, or the author's own defensible bet. It never
pretends an open question is closed. And it's written by an operator who works
inside the live AI economy and has spent two decades building high-performance
human systems — not an academic theorizing from the outside.
You won't finish it with certainty. You'll finish it with something more
durable: a first-principles way of thinking about machine intelligence that
holds up in a boardroom, a due-diligence call, or a strategy offsite — and
that makes you the most clear-eyed voice in the room, not the most enthusiastic
or the most alarmed, but the most accurate.
"Synopsis" may belong to another edition of this title.
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