The ability to process data can be separated into two broad categories, linear processing and parallel processing. The human brain is unrivalled in its ability to carry out parallel processing, giving us the unique ability to recognise patterns and compare courses of action in order to reach the most desirable outcome. However, when it comes to linear processing, the ability to rapidly carry out one task at a time, we are vastly out-performed by our technological progeny.
The responsibility of signal transmission within the brain lies with neurons, specialised brain cells that carry electrochemical transmissions. There are 86 billion neurons that make up the brain of an adult human, with approximately 100 trillion interneuron connections. As the brain fires millions of signals at any one time, signals that feed into neighbouring circuits, the human brain is ‘massively parallel’.
Researchers attempting to map the brain and its trillions of connections are now able to use functional magnetic resonance imaging (fMRI) to track the firing of individual neurons through basic circuits. Increasing temporal and spatial resolution of brain imaging platforms, such as fMRI, will allow accurate tracking of concurrent neuronal firing through infinitely complex circuits. Being able to track multiple firing neurons simultaneously will allow us to map the massively parallel nature of the human brain.
Neuroimaging through fMRI enables researchers to map the structural changes within individual neurons, including the formation of new budding connections. Tracking these changes will allow us to further understand the dynamic nature of the brain and its synaptic plasticity, the process by which neurons form new connections, thought to lead to learnt behaviour and the formation of memories.
The evolution of the human brain may be beautiful in its depth of complexity and functionality, however the system is limited by the biochemical restraints of mammalian biology. The maximum speed of neural transmission is approximately 120 metres per second. If the theorised speeds of photon-based processing were realised in the future, neural transmission within the brain could be out-performed by a factor of three million.
The Chinese Tianhe-2 supercomputer is now capable of carrying out 33,860 trillion calculations per second, making it 41% more powerful than its American Titan predecessor. As the processing power of the average computer system increases exponentially every year, we will soon have the tools and processing power to identify every human neural connection and pathway. This will facilitate the creation of a reconstructed neuronal network, forming the basis of an artificial human brain.
Increased processing power, coupled with the development of parallel data processing from neurological research is theorised to lead to a point in which artificial computers will reach our ‘unique’ level of consciousness, and indeed surpass it. This point is referred to in the study of artificial intelligence as the ‘Singularity’.
How will this vast expansion in artificial intelligence influence the world we live in? An entity that is capable of independent self-improvement will only become more intelligent at an exponential rate.
Topics of global importance including clean energy, personalised healthcare and global warming may indeed be resolved as nuclear fusion, nanotechnology and carbon fixing technology are optimised and perfected.
The application of this technology would be revolutionary in the running of our day-to-day lives, but where would it leave us? It has been suggested that the refinement of neuron networking technology in the future will enable us to record and upload our consciousness to online systems. Pre-existing communication networks, forming the basis of the modern day Internet, will allow the sharing and preservation of knowledge and memories. Could this harmony in technological power and biological creativity lead to intelligent transcendence and mental immortality?
Tim Ellis is a first year PhD student in Advanced Characterisation of Materials
Image: tianhe-2 by Sam Churchill (Flickr)