Book Reviews of On Intelligence

On Intelligence
On Intelligence
Author: Jeff Hawkins, Sandra Blakeslee
ISBN-13: 9780805074567
ISBN-10: 0805074562
Publication Date: 10/3/2004
Pages: 272
Rating:
  • Currently 4.8/5 Stars.
 2

4.8 stars, based on 2 ratings
Publisher: Times Books
Book Type: Hardcover
Reviews: Amazon | Write a Review

2 Book Reviews submitted by our Members...sorted by voted most helpful

reviewed On Intelligence on + 506 more book reviews
Helpful Score: 1
From the inventor of the palmpilot comes a revolutioonary new theory of intelligence and a bold vision for the future of intelligent machines. In an engaging style that captivates audiences from the merely curious to the professional scientist. On intelligence explains what intellignece is, how the brain works, and how this knowledge will finally make it possible for us to build intlligebt machines, in silkicon, that will not only imitate but exceed our human ability in surprising ways. The author is one of the most successful and highly regarded computer architects and entrpreneurs in Silicon Valley. He founded both Pal Computing and Handspring, created the Redwood Neuroscience Institute to promote research on memory and cognition and is a member of the scientific board of Cold Spring Harbor Laboratory. He lives in Northern Calif. Sandra Blakeslee has been writing aobut science and medicine for the New York Times for more than 30 yrs.. She is the coauthor of Phantoms in the Brain with V.S.amachandran and of Judith Wallerstein's bestselling books on psychology and marriage.
reviewed On Intelligence on + 29 more book reviews
It did not work. Hawkins work did not create Artificial General Intelligence (AGI).

The complexity of the human brain is awesome. The human brain is measured by about a billion cells that interact with one another to create thought. We still do not have a working AGI or processor design that mimics the brain in the same complexity that is needed to create artificial thought.

We may find a back door or a trick to make AGI work in machines without emulating the complexity or memory model of the biological human brain, but current work is not creating AGI.

New ways of thinking are needed and new models for memory to support AGI are needed.

We might beable to fake AGI in the short term by writing clever software, but there is no substitute for real AGI computers.