Deep Learning (DL) has been around for a very long time, almost the little brother to Machine Learning. However, with the increased amounts of data available (2.5 Quintilian bytes produced per day) and a new generation of powerful computer platforms all based around cutting edge GPU processors, Deep Learning has grown to become an indispensable, intelligent utility for every industry in working with artificial intelligence.

Deep Learning is currently the quickest way to develop systems that can, in certain areas, have better accuracy rates than humans, as well as an obviously swifter speed of processing data that gives superior decision-making results. And it is this reason that is driving the investment levels we are seeing globally. By 2024 it generally agreed that invest levels will hit between $600B and $900B as companies race to maximise on this new area of possibility.

Deep Learning involves training a computational model with massive amounts of data so that the model can learn and adapt to the data that is being supplied. The model is then quizzed on this information and learns from experience. If the model gives an incorrect output, you retrain the model until it learns from the mistake. Ultimately, you are looking for the model to give you a very high accuracy rate in the answers to questions you are asking.

In the past, these systems were less efficient than humans (error rate was higher), however that is no longer the case, with some models having better accuracy rates than their human designers. This is possibly the singular reason why investment levels into Deep Learning technologies are exploding. Big business now has the possibility to replace parts of the human workforce with intelligent programmes that can offer far higher levels of efficiency with equal or superior error rates to humans. 

Imagine a situation where two companies have equally good products or services to offer: One invests in Deep Learning and the other does not. One stays with traditional methods of doing business and does not see the future, or is simply slow to react (Blockbuster video). The other, however, see’s these future technological prospects and embraces that technology (Netflix). The outcome is obvious. Companies who do not look to the future will find themselves being forever squeezed and under constant pressure, with no way of adapting. Don’t let yourself be left behind.

The path to AI or Deep Learning is not an easy one. It takes time to develop in-house skill sets, an understanding of the technology to create application benefits, and, of course, investment. As with all things, the benefits that DL can offer are constantly evolving; the limits of what is possible are being pushed to new levels. What we can do today will be obsolete with what we can do in just a few years from now. Therefore, the early adopters will have significant advantages in the market.

Novatech are perfectly positioned to help you adapt your business; we have dedicated in-house professionals (Linux development teams, Deep Learning Architects, support services,) and a full consultancy approach to providing you with the best hardware and software and ecosystem solutions to help assist in your efforts.

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