Artificial brain

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An artificial brain (or artificial mind) is software and hardware with cognitive abilities similar to those of the animal or human brain. [1]

Contents

Research investigating "artificial brains" and brain emulation plays three important roles in science:

  1. An ongoing attempt by neuroscientists to understand how the human brain works, known as cognitive neuroscience.
  2. A thought experiment in the philosophy of artificial intelligence, demonstrating that it is possible, at least in theory, to create a machine that has all the capabilities of a human being.
  3. A long-term project to create machines exhibiting behavior comparable to those of animals with complex central nervous system such as mammals and most particularly humans. The ultimate goal of creating a machine exhibiting human-like behavior or intelligence is sometimes called strong AI.

An example of the first objective is the project reported by Aston University in Birmingham, England [2] where researchers are using biological cells to create "neurospheres" (small clusters of neurons) in order to develop new treatments for diseases including Alzheimer's, motor neurone and Parkinson's disease.

The second objective is a reply to arguments such as John Searle's Chinese room argument, Hubert Dreyfus's critique of AI or Roger Penrose's argument in The Emperor's New Mind . These critics argued that there are aspects of human consciousness or expertise that can not be simulated by machines. One reply to their arguments is that the biological processes inside the brain can be simulated to any degree of accuracy. This reply was made as early as 1950, by Alan Turing in his classic paper "Computing Machinery and Intelligence". [note 1]

The third objective is generally called artificial general intelligence by researchers. [3] However, Ray Kurzweil prefers the term "strong AI". In his book The Singularity is Near , he focuses on whole brain emulation using conventional computing machines as an approach to implementing artificial brains, and claims (on grounds of computer power continuing an exponential growth trend) that this could be done by 2025. Henry Markram, director of the Blue Brain project (which is attempting brain emulation), made a similar claim (2020) at the Oxford TED conference in 2009. [1]

Approaches to brain simulation

Estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil, and Anders Sandberg and Nick Bostrom), along with the fastest supercomputer from TOP500 mapped by year Estimations of Human Brain Emulation Required Performance.svg
Estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil, and Anders Sandberg and Nick Bostrom), along with the fastest supercomputer from TOP500 mapped by year

Although direct human brain emulation using artificial neural networks on a high-performance computing engine is a commonly discussed approach, [4] there are other approaches. An alternative artificial brain implementation could be based on Holographic Neural Technology (HNeT) non linear phase coherence/decoherence principles. The analogy has been made to quantum processes through the core synaptic algorithm which has strong similarities to the quantum mechanical wave equation.

EvBrain [5] is a form of evolutionary software that can evolve "brainlike" neural networks, such as the network immediately behind the retina.

In November 2008, IBM received a US$4.9 million grant from the Pentagon for research into creating intelligent computers. The Blue Brain project is being conducted with the assistance of IBM in Lausanne. [6] The project is based on the premise that it is possible to artificially link the neurons "in the computer" by placing thirty million synapses in their proper three-dimensional position.

Some proponents of strong AI speculated in 2009 that computers in connection with Blue Brain and Soul Catcher may exceed human intellectual capacity by around 2015, and that it is likely that we will be able to download the human brain at some time around 2050. [7]

While Blue Brain is able to represent complex neural connections on the large scale, the project does not achieve the link between brain activity and behaviors executed by the brain. In 2012, project Spaun (Semantic Pointer Architecture Unified Network) attempted to model multiple parts of the human brain through large-scale representations of neural connections that generate complex behaviors in addition to mapping. [8]

Spaun's design recreates elements of human brain anatomy. The model, consisting of approximately 2.5 million neurons, includes features of the visual and motor cortices, GABAergic and dopaminergic connections, the ventral tegmental area (VTA), substantia nigra, and others. The design allows for several functions in response to eight tasks, using visual inputs of typed or handwritten characters and outputs carried out by a mechanical arm. Spaun's functions include copying a drawing, recognizing images, and counting. [8]

There are good reasons to believe that, regardless of implementation strategy, the predictions of realising artificial brains in the near future are optimistic.[ citation needed ] In particular brains (including the human brain) and cognition are not currently well understood, and the scale of computation required is unknown. Another near term limitation is that all current approaches for brain simulation require orders of magnitude larger power consumption compared with a human brain. The human brain consumes about 20  W of power, whereas current supercomputers may use as much as 1 MW—i.e., an order of 100,000 more.[ citation needed ]

Artificial brain thought experiment

Some critics of brain simulation [9] believe that it is simpler to create general intelligent action directly without imitating nature. Some commentators [10] have used the analogy that early attempts to construct flying machines modeled them after birds, but that modern aircraft do not look like birds.

See also

Notes

  1. ↑ The critics:
    • Searle, John (1980), "Minds, Brains and Programs", Behavioral and Brain Sciences , 3 (3): 417–457, doi:10.1017/S0140525X00005756, archived from the original on December 10, 2007, retrieved May 13, 2009
    • Dreyfus, Hubert (1972), What Computers Can't Do, New York: MIT Press, ISBN   0-06-090613-8
    • Penrose, Roger (1989), The Emperor's New Mind: Concerning Computers, Minds, and The Laws of Physics, Oxford University Press, ISBN   0-14-014534-6
    Turing's (pre-emptive) response: Other sources that agree with Turing:

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The Chinese Room Argument holds that a digital computer executing a program cannot have a "mind", "understanding", or "consciousness", regardless of how intelligently or human-like the program may make the computer behave. The argument was presented by philosopher John Searle in his paper, "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980. Similar arguments were presented by Gottfried Leibniz (1714), Anatoly Dneprov (1961), Lawrence Davis (1974) and Ned Block (1978). Searle's version has been widely discussed in the years since. The centerpiece of Searle's argument is a thought experiment known as the Chinese Room.

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<i>The Age of Spiritual Machines</i> 1999 non-fiction book by Ray Kurzweil

The Age of Spiritual Machines: When Computers Exceed Human Intelligence is a non-fiction book by inventor and futurist Ray Kurzweil about artificial intelligence and the future course of humanity. First published in hardcover on January 1, 1999 by Viking, it has received attention from The New York Times, The New York Review of Books and The Atlantic. In the book Kurzweil outlines his vision for how technology will progress during the 21st century.

<span class="mw-page-title-main">Mind uploading</span> Hypothetical process of digitally emulating a brain

Mind uploading is a speculative process of whole brain emulation in which a brain scan is used to completely emulate the mental state of the individual in a digital computer. The computer would then run a simulation of the brain's information processing, such that it would respond in essentially the same way as the original brain and experience having a sentient conscious mind.

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<span class="mw-page-title-main">Neural network</span> Structure in biology and artificial intelligence

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<span class="mw-page-title-main">Hubert Dreyfus's views on artificial intelligence</span> Overview of Hubert Dreyfuss views on artificial intelligence

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References

  1. 1 2 Artificial brain '10 years away' 2009 BBC news
  2. ↑ "Aston University's news report about the project". Archived from the original on 2010-08-05. Retrieved 2010-03-29.
  3. ↑ Voss, Peter (2006), "Essentials of general intelligence", in Goertzel, Ben; Pennachin, Cassio (eds.), Artificial General Intelligence, Springer, ISBN   3-540-23733-X, archived from the original on July 23, 2013
  4. ↑ see Artificial Intelligence System, CAM brain machine and cat brain for examples
  5. ↑ Jung, Sung Young, "A Topographical Development Method of Neural Networks for Artificial Brain Evolution" Archived June 29, 2011, at the Wayback Machine , Artificial Life, The MIT Press, vol. 11, issue 3 - summer, 2005, pp. 293-316
  6. ↑ "Blue Brain in BBC News". Archived from the original on 2019-07-13. Retrieved 2009-07-27.
  7. ↑ (in English) Jaap Bloem, Menno van Doorn, Sander Duivestein, Me the media: rise of the conversation society, VINT research Institute of Sogeti, 2009, p.273.
  8. 1 2 , A Large-Scale Model of the Functioning Brain.
  9. ↑ Goertzel, Ben (December 2007). "Human-level artificial general intelligence and the possibility of a technological singularity: a reaction to Ray Kurzweil's The Singularity Is Near, and McDermott's critique of Kurzweil". Artificial Intelligence. 171 (18, Special Review Issue): 1161–1173. doi: 10.1016/j.artint.2007.10.011 . Retrieved April 1, 2009.
  10. ↑ Fox and Hayes quoted in Nilsson, Nils (1998), Artificial Intelligence: A New Synthesis, p581 Morgan Kaufmann Publishers, ISBN   978-1-55860-467-4
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