An icon for a calendar

Published December 14, 2020

How PRML changed the world as we know it

How PRML changed the world as we know it

PRML – Do you remember how unreliable analog cell-phones were in the 80’s? You would be on a call and you would here static and distortion. Then all of a sudden we got into the digital signal era, and the quality of calls went to a new level. Sure you could still lose a call, but it was either a great connection or no connection.

This was in a large part due to an amazing little formula called “partial response, maximum likelihood” or PRML that pretty much changed the world.

PRML is a technique for allowing the most outcome of a signal to be calculated, and this meant that much lower power levels were needed to transmit data, for it to be reliably received. By extension this allowed lower levels of the signal to be stored on magnetic devices like tapes and disks. This meant a lot more information could be stored in the same space. All of a sudden, disks went from megabytes to gigabytes and now terabytes.

The same thing happened to transmission of data, lower quality signals became usable, so much faster signals could be transmitted over the same medium, be it in wires, fiberoptic or through the air. The same techniques allowed faster circuitry.

More, faster, more reliable!

One little algorithm created an explosion in communications, computing power and touched just about every part of society.

Whenever you half listen to your spouse and believe you go the whole story, I’d suggest you don’t tell them that you are using a version of brain based PRML. I’ve tried it, and believe me when I tell you it doesn’t end well.

Today we all rely on math and algorithms with the power to identify signals within a mass of data. It’s become second nature, but it’s still a relatively new science. There is still an amazing amount of innovation going on. Take for example Nastel Xray, a platform used by many enterprises to predict future events, it uses a wide array of machine learning techniques to find useful patterns in the data and present this data in ways that allow you to make decisions.