Summary of Thinking Machines

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Rating

8

Qualities

  • Scientific
  • Eye Opening
  • Background

Recommendation

In his engaging overview of artificial intelligence (AI), tech journalist Luke Dormehl lucidly sets out the origins of AI, probes its applications and speculates with relish about its wider or wilder potential – for good, ill or some incomprehensible moral hinterland. “Narrow AI” pervades modern life – in wearable devices, smartphones, smart homes, translation apps, digital assistants, and more – while a “wide AI” looms. This presages great benefit – or maybe a “Technological Singularity” that will displace humankind from cognitive dominance.

About the Author

United Kingdom-based journalist Luke Dormehl‘s previous books include The Formula: How Algorithms Solve All Our Problems…and Create More.

 

Summary

“The Giant Brain” and “Good Old-Fashioned AI”

Long the stuff of sci-fi films such as 2001: A Space Odyssey, artificial intelligence (AI) is now taking center stage in real-world applications such as stock trading, language translation, facial recognition and driving – with even wider, wilder uses in development. The pressing question is, what role will people play in a future of increasingly smart, capable machines?

In 1945, ENIAC, the first programmable computer, epitomized the metaphor of seeing computing as a “giant brain,” an idea computing borrowed from cognitive psychology and behaviorism. Pioneering computer scientist Alan Turing, mathematician John von Neumann and information theorist Claude Shannon were the three prime movers of early AI. Turing’s concept of a machine that could emulate any other machine – a “Universal Turing Machine” – sparked a new paradigm. Shannon showed how switching transistors could perform simple logical operations when chained into complex algorithms. In 1950, Turing predicted people would accept the idea of “machines thinking” by 2000. His timing was optimistic, but AI’s booming pace today shows his prescience. In ...


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