Inefficiencies can often keep operations from producing a satisfactory return. It might be time to start measuring your company’s ability to meet expectations. With the use of state-of-the-art computing programs, you can locate the problems your organizations is having and work toward patching the process any way you can. While data-collection was once a difficult system to implement, new computer-driven, business-intelligence software can provide you with the vital answers you need to make the changes required for profitability.
At the core of these analytics is a computer that’s outfitted with the latest in deep learning software. If you haven’t heard of deep learning before, it is technology using advanced algorithms that are run by advanced computing constructs to provide sound predictions for professionals to use in order to build efficient systems. By being able to capture and analyze everything your company does, you can come up with the solutions you need to take the organization to the next level.
One example of this in practice is how the Google Search attempts to guess what word or words you are going to type into the bar. As each new letter is added, Google, using your profile’s search history, and the frequency of searches conducted by other users gives the user as relevant of a search result as possible.
When these systems are used by businesses, this deep (or machine) learning provides incredibly accurate predictions on how the complex systems that a business depends on will fare over a certain amount of time. This happens by mining the data for actionable information and is often remarkably precise. Typically, organizations conduct data analytics for the purpose of streamlining aspects of your business that they have had trouble controlling costs for in the past.
Some of the most important names in computing are at the forefront of this new and “deeply” interesting technology. Industry giants such as Google, Facebook, and Microsoft have begun creating large deep learning systems. Even Apple, known the world over for its proprietary access to improved individual cyber security, has recently purchased deep learning specialists Vocal IQ and Perceptio to enhance their ability to collect and decipher informational trends.
With the world’s most predominant software companies taking on the exorbitant cost to push in deep learning forward, it seemingly presents a situation where these companies are all after the same thing. That thing is Artificial Intelligence.
Artificial Intelligence, or AI, has been a favorite of dystopian fiction writers for decades. The idea that a computer could ultimately be sentient is one that is hotly debated on forums and among technology aficionados. One element of AI is certain; in order to meet the lofty criteria, these systems need to be able to compute elements the way a human mind does. This is where deep learning comes in. Deep learning platforms use complex algorithms to simulate critical thought. The more these systems can compute, the more advanced they become. In order for there to be AI, however, the computing platform would have to write the algorithms while they are computing them, which hasn’t been possible yet.
In regards to the small business owner, and like many other cutting-edge technologies, deep learning may be a concept that you will need to experience firsthand before you believe the benefits. There are resources available that can sate your curiosity. Adam Gibson, a self-taught millennial has created what he calls the “DL4J”; the first “commercial-grade, open-source, distributed deep learning library…,” and has started the company Skymind to advance deep learning integrations. Skymind’s current client list includes IBM, Chevron, Booz Allen, Accenture, and more. By promoting this technology in this way, they are giving organizations an ability to make informed and efficient business decisions
AI is a frightening concept, (especially when considering filmmaker James Cameron’s view of it) but the building blocks of AI can present quite a windfall for your business’s operational efficiency. Do you think AI should be allowed to progress at the rate it is going? Share your thoughts in the comments.
