Most people have a tendency to think of artificial intelligence (AI) in the context of science fiction, but it’s become a very real technology that’s having a significant impact on the world. From the chat programs that help us resolve customer service issues to incorporation during on-demand app development to the robots that work on assembly lines, AI is everywhere. Its prevalence is only going to increase as the technology continues to develop.
Deep learning is one of the key factors in the rapid expansion and improvement of AI capabilities. Here are a few ways deep learning is improving AI.
What is Deep Learning?
Deep learning is a subset of machine learning. With machine learning, an algorithm is designed to help a machine learn from data. Deep learning performs a similar task, but on a much larger scale. It works with more data and can also learn with a greater degree of independence.
One of the key features behind deep learning is the application of neural networks. Neural networks are computer system modeled after the human brain; they’re made up of nodes that perform a similar function to that of neurons in the brain. When the system is fed data, it creates networks between the nodes as it learns.
The Impact of Deep Learning
Technologies supported by deep learning are now moving into different areas of the lives of consumers. The following are a few examples of the deep learning technologies that are currently available:
Common household items like thermostats, refrigerators, and lights are now connecting to the internet and using AI to offer increased efficiency and convenience to homeowners. These items can connect to systems that use deep learning to find patterns in human behavior to predict things like the need for heating and lighting.
Natural Language Processing is a field of artificial intelligence that provides machines with the ability to process, understand, and generate human language. When you interact with something like Amazon Alexa or Siri, you are using a system that applies Natural Language Processing that is supported by deep learning algorithms.
Deep learning provides machines with the ability to recognize objects and images in ways that were previously impossible.
A good example of this is the way Facebook can recognize the people in a photo without being told by the user. To do this, it creates templates of the faces and then uses deep learning to compare the templates and find a match. In the future, this deep learning capability could be used to train machines to analyze medical images and diagnose diseases with greater accuracy.
The Future of Deep Learning
Applications that depend on deep learning are going to become more common, and more businesses are going to experiment with this technology in the future. While this future is essentially inevitable, there are still some hurdles that need to be overcome.
The first is a matter of hardware. Neural networks are massive computer systems that are far more powerful and complex than anything most businesses would have access to. Additionally, these systems require incredible amounts of data in order to learn. For a business that is interested in deep learning, being able to provide the necessary hardware and data will be essential.