holographic technology and neural networks

The capacity of holographic data systems to read an entire (million bit) page concurrently opens up fundamentally different means of data access and searching. With holotechnology data systems, one can contrast configurations of information using parallel processes and associative extraction properties -- exploring massive amounts of data to find relationships. The boundary between holography and automation may form "holobots" that learn by means of creative identification of believable patterns in large quantities of information. Some day, optical neural networks may be possible using holotechnology technology. Link to Silver Holographic provides more insights.

Among the most prominent challenges in the consumer market progress of holotechnology applied science is the development of optimal materials and configurations for high-volume, rapid-access, safe optical storage media. Candidate materials range from: highly-sensitive photo-chromic and photo-chemical polymers; optically sensitive crystals such as lithium niobate; organic photopolymers; and glasses. See also: Robotic Simulation for more detailed info.

For unique discussion, see Holographic Disks .