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Startup claims storage breakthrough

by John Geralds in Silicon Valley

11 Jan 2002

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A scientific research startup claims to have developed a technique to compress "practically random" data by a factor of hundreds to one, with no data loss.

Although Florida-based ZeoSync is currently demonstrating its technology on very small bit strings, the company expects to optimise its algorithms which it claims will lead to significant changes in how data is stored and transmitted.

According to ZeoSync, the discovery could overturn half a century of thinking in the field of 'lossless' data compression, a process by which computer data can be compacted, stored and then restored with no loss of information.

ZeoSync said that the discovery would have widespread applications in data storage and telecoms, and claimed that it could greatly enhance the ability of computer disks to store text, music and video.

Founder and chief executive Peter St. George said that the company had developed a new plateau in communications theory.

"Through the manipulation of binary information and translation to complex multidimensional mathematical entities, we are expecting to produce the enormous capacity of analogue signalling, with the benefit of the noise free integrity of digital communications," he explained.

ZeoSync intentionally randomises naturally occurring patterns to form entropy-like random sequences through its patent-pending technology known as Zero Space Tuner.

Once randomised, the company's Binary Accelerator encodes these singular-bit-variance strings within complex combinations to result in massively reduced BitPerfect equivalents. The combined Turner Accelerator is expected to be commercially available next year.

Current technologies that enable the compression of data for transmission and storage are typically limited to ratios of 10:1.

ZeoSync said that its Zero Space Tuner and Binary Accelerator, when fully developed, will offer compression ratios that will approach the hundreds to one range.

The company has worked with mathematicians at MIT, Harvard University, Stanford University, Moscow State University and Peking and Nankin Universities in China, among others.

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