- WRITTEN BY Jorge Rojas POSTED ON December 30,2015
It has been said in many different ways, but for many businesses, inefficiency is stealing capital and keeping your organization from producing at the levels you’d almost certainly like to see. One problem is how do you measure your company’s usefulness, as in, it’s propensity to meet or exceed expectations. Does your business have inefficient operations, or are there just several small inefficiencies that produce the same effect? Either way, understanding the concept of deep learning can go a long way toward giving your business the look it needs to sustain growth.
The concept behind these analytics, machine or deep learning, is being deployed throughout the business world by many organizations who, like you, are searching for the most efficient (and profitable) ways to do whatever it is that you do. This practice consists of state of the art hardware, completing complicated algorithms to apply to every part of a process or system. By capturing every variable available in a construct and looking for patterns, this software basically predicts situations and effectively learn as it crawls data. One example of this process is the search results that you get when you type a word into the Google search bar. As you add letters, based on your search history, and the history of other users, Google attempts to predict what term you will search for. By using this technology over time, you will see improved results.
When used by organizations, deep learning can give amazingly accurate representations of complex systems, as well as predictive results that are so specific that they are almost clairvoyant. While data collection and analysis is a formidable way to predict trends and situations, deep learning takes this to a whole new level, especially considering the amount that is “learned.” It is important to state that some of the most successful data mining organizations have invested in the world’s most state-of-the-art deep learning systems. Google, Facebook, and Microsoft are three such organizations. Even Apple, long known for its predominant individual security, has moved forward with deep learning, purchasing the machine learning specialists Vocal IQ and Perceptio recently.
This kind of push in deep learning from the world’s predominant technology companies can make the layman wonder what the endgame is. You don’t have to look too far to find that out. It is Artificial Intelligence, of course. Artificial Intelligence, or AI, has been a favorite of movie makers and science fiction authors for some time. Tales of robots that think they’re alive and benevolent machines that have come to learn just how destructive the human race is and has decided the best thing for us is the complete annihilation of our species. Either way, humans need for drama as caused a fear of the capabilities of AI. Deep learning, as a basic building block of an artificially intelligent computing platform, can produce results in capturing and analyzing small tracks of data and receiving more accurate predictions than you would receive through standard analytical procedures.
For the business owner, deep learning may be something you will need to see in practice before you go out and get yourself an expensive deep learning team. Or you can hitch your curiosity trailer to 24-year-old wonderkid Adam Gibson and his DL4J. Gibson has created the first “commercial-grade, open-source, distributed deep-learning library…,” as well as the company Skymind who works with IBM, Chevron, Booz Allen, Accenture and other organizations. By devoting their resources to promoting the field, they are significantly improving an organization’s ability to make business decisions that are more efficient and work best to serve the organization and its goals.
AI and deep learning are in their infancy, but if organizations begin to utilize this technology to streamline their operations, it’s likely that major progress will come quickly. What are your thoughts of artificial intelligence? Do you think it will benefit society with its unbridled efficiency, or do you think that the threats inherent with a world filled with cognizant machines outweigh the potential benefits? Sound off now in the comments.
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