Artificial brain

Other fields of psychology: AI · Computer · Consulting · Consumer · Engineering · Environmental · Forensic · Military · Sport · Transpersonal · Index

Artificial brain (or artificial mind) is a term commonly used in the media^[1] to describe research that aims to develop software and hardware with cognitive abilities similar to those of the animal or human brain. Research investigating "artificial brains" plays three important roles in science:

An ongoing attempt by neuroscientists to understand how the human brain works, known as cognitive neuroscience.
A thought experiment in the philosophy of artificial intelligence, demonstrating that it is possible, in theory, to create a machine that has all the capabilities of a human being.
A serious long term project to create machines with strong AI, capable of general intelligent action (or Artificial General Intelligence), i.e. as intelligent as a human being.

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' 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".^[3]

The third objective is generally called artificial general intelligence by researchers.^[4] However Kurzweil prefers the more memorable 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]

Brain simulation projects[]

aHuman, hybrid of latest neurobiology data and Numenta findings aimed to implement human personality by means of computer program, started in 2008 as independent research.
Blue Brain Project, an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level.
HNeT (Holographic Neural Technology), a technology by AND Corporation (Artificial Neural Devices) based on non linear phase coherence/decoherence principles.
Hierarchical Temporal Memory, a technology by Numenta to capture and replicate the properties of the neocortex.
Visual Hierarchical Modular Neural Network, a software technology by TinMan Systems to visually construct a flow of human thought and logic to produce autonomous artificial intelligence.
A.I.L.E.E.N.N. Artificial Intelligence Logic Electronic Emulation Neural Network, an entire new Cloud based PaaS platform as a service and IaaS Infrastructure for AI represented as a ubiquitous entity based on Neural Networks and Fuzzy Logic with universal inputs, outputs and actuators aiming to the democratization and human-like interaction as the ultimate resource planner, decision making process and actuator. By the founders of TDVision

Approaches to brain simulation[]

File:Estimations of Human Brain Emulation Required Performance.svg

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

Although direct brain emulation using artificial neural networks on a high-performance computing engine is a common approach,^[5] 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 QM wave equation.

EvBrain^[6] is a form of evolutionary software that can evolve "brainlike" neural networks, such as the network immediately behind the retina.

Since November 2008, IBM received a $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.^[7] 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.

In March 2008, Blue Brain project was progressing faster than expected: "Consciousness is just a massive amount of information being exchanged by trillions of brain cells.^[8]" Some proponents of strong AI speculate 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.^[9]

There are good reasons to believe that, regardless of implementation strategy, the predictions of realising artificial brains in the near future are optimistic. In particular brains (including the human brain) and cognition are not currently well understood, and the scale of computation required is unknown. Template:Citation needed span The brain consumes about 20W of power whereas supercomputers may use as much as 1MW or an order of 100,000 more (note: Landauer limit is 3.5x10²⁰ op/sec/watt at room temperature).