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The Cube (design notes, patents pending)

"Stem-Cell research has led to a breakthrough using new processes that couple advanced computer technologies with Stem-Cell powered bio-structures."

Stem-Cell DNA has been re-engineered to create new type of cell structure incorporating silicon and phosphorous to provide ‘synapse’ and memory cells with transistors type sensitivity and speed but at a cell density not less than three times the normal biological scale. 

These cells are grown around a base structure of cell nano-tubes (NCC derived) that are sensitive to electrical charge.  These are themselves grown as a larger structure that is simply sliced up (by laser) to form many units for Cube production.

Each Cube is grown in a vat and the input & output links are derived by the addition of growth hormone along the sides.  These create the growth of filaments that conduct and link (similar to nerves endings) between Cubes. These in turn link to standard silicon circuits that link to specific input/output sub-systems.

When complete, The Cubes can be linked together to form larger arrays for massive computational power and memory management.  Their working environment is simply a vat of nutrients that provide ATP power for the cells and cooling.  Each Cube maintains its own throughput of nutrient using simple expansion and contraction of the nano tubes.  Initial training of each Cube allows it to quickly adapt its own control system for this basic functioning.  The nutrient ATP is maintained using an adapted fuel-cell sub-system that allows for hydrogen fuel or direct electrical connection.

As the silicon cells run at five thousand times faster than biological cells, the time required for them to be trained for advanced tasks is short.  So that a year of standard training is reduced to less than two hours, and ten years of training takes less than a day.  This paves the way for semi-sentient processing in short timescales.

Having developed these re-engineered stem-cells the resultant growth production system is straightforward, as is the nutrient environment.  This provides for rapid production of Cube systems that can operate under many diverse operational conditions.  The ability to use the Cubes as basic processors and memory systems or to ramp up the processing power by linking many Cubes via their filaments means that they can be utilised for both simple and very complex processing and control tasks. 

Initial pre-learning environments have been developed to provide basic operating processes such as the control of nutrients and cooling but also include a basic communication syntax with operational input and output strategies and thresholds.  This creates a more standardised environment and allows implementation of standard input and output technologies for the control sub-systems.

http://www.artificialbrains.com/darpa-synapse-program

 

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