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How Self-Learning Software Is Already a Huge Part of Your Life

Artificial intelligence has been a thing of the future for so long that we can easily overlook how important it is now.

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Self-learning, machine learning, and AI are all buzzwords in the tech field today. They all represent the next generation in and management. In this brave new world, programmers will often set up the application -- and the software will do the rest. Driven by , deep learning systems, and consumer demand, you may be investing in self-learning programs sooner than you think.

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Related: The Rise of Artificial Intelligence in Cyber Defense

What is self-learning software?

Self-learning, often referred to as machine learning, is a form of AI. While it doesn’t allow software programs to perfectly mimic the human experience as it would in true artificial intelligence, it does give programs an added layer of sophistication and the ability to recognize patterns, learn from data, and become more intelligent over time.

Self-learning is different than traditional programming. The systems use basic prediction models, a set of parameters that the computer can use to make decisions, and a learning component that allows the system to change the parameters based on experience. Over time, using this cyclical system, a computer can transform its own model and parameters to fit its experience with predictions and real-world outcomes.

Codes and signals behind deep learning technology are remarkably complex, but they give applications the ability to optimize their user experiences. For the end user, the process of using the system can get easier and more helpful with each use.

Related: 5 Ways Artificial Intelligence Is Shaping the Future of Ecommerce

Transforming the world in real time.

Self-learning software is already seeping into daily life. Most smart device users have experience with at least one of the aforementioned self-learning solutions. Here are a few of the self-learning solutions on the market today:

, , Google Assistant, and . These four machine learning solutions provide similar functionality and act as technological assistants in today’s world. Siri is available on devices and has been around since 2011. Cortana is available in products, Google Assistant is Google’s version, and Alexa is ’s version of the assistant. Over time, these products use similar machine learning and language processing programming to engage in more meaningful ways with the end user. Watch these programs over the next few years. While they all serve a basically similar function today, each parent company may take the technology in a different direction. Google and Alexa may compete for in-home services, while Siri and Cortana primarily stay on mobile devices.

IBM Watson. Here's a general review of IBM's question answering computer system that was originally developed to take down human contestants on the TV game show Jeopardy back in 2011. Watson is an integrated platform that uses machine learning and language processing to provide end users with relevant data in any number of areas. Consider Watson the nerdy, workaholic friend of Siri and Cortana. Used primarily in business environments, Watson can uncover and answer customer questions, identify complete answers to questions from stacks of documents, and identify meaningful patterns in big data sets that companies collect and manage today.

TensorFlow. A different type of machine learning solution, this software gives anyone with access to computer software the ability to develop their own self-programmable smart computer. The open source collection of software puts machine learning capabilities in the hands of enterprising developers.

Related: Facebook Developing Artificial Intelligence to Flag Offensive Live Videos

Predicting the future in self-learning software.

Machine learning is already here, and it’s poised to grow. The next generation of tech giants may arise from the shift toward self-learning software. This software will optimize the technology for driverless vehicles. It may also help companies avoid downtime associated with technical errors and transform the way that cybersecurity firms approach the modern threat landscape.

In the future, we may “train” our computers, phones, and wearables instead of downloading applications and changing settings. Smarter systems will impact almost every aspect of the technological experience.

Consider every piece of technology you use today, including your mobile devices, workplace applications, games, and smart wearables. Self-learning software will optimize, streamline, and update the user experience associated with many of these technological assets. Are you ready for smarter programs and machines?

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