Technology What Is Deep Learning And How Is It Used
Aug 18, 2022 (SAN DIEGO) — Deep learning tries to solve problems which call for human-like thought.
Deep Learning, like Machine Learning, is a branch of Artificial Intelligence (AI). Although we have made a lot of progress with this technology, we are still only seeing the tip of the iceberg of what Deep Learning (DL) can do.
AI has a plethora of applications. However, the one major issue with AI at the moment is that it cannot live up to the level of human thought. The human brain is a computer more advanced than we can create. Man-made computing power is incredible, but it is not a human brain. DL seeks to challenge this issue.
The basics
Machine Learning (ML) uses fundamental ideas of Artificial Intelligence and DL uses a portion of ML tools to solve problems that call for human-like thought. DL is a unique branch of AI, seeking to create tools that can aid humans in thinking like humans.
Humans grow their computing abilities through learning. We create schemas, or rules for how the world functions, and then we are presented with information to fit into those schemas. Some information fits and the rule stands. Other information does not fit and forces us to rework what we had previously thought. This is the basic process of learning, and this is what DL does.
Analyze lots of data
Deep Learning involves presenting a machine with large amounts of data that can be used to make decisions about other information. Neural networks guide the classification of this data based on true or false questions asked or numerical values extracted.
DL can take a picture and organize it based on what humans would see, after making a series of decisions based on previously learned information and the schemas which result. But this is only the tip of the iceberg of what DL can do.
Learn from mistakes
DL can organize pictures, audio, video, text, machine signals, and any other form of data to a seemingly human standard; and it can do this very quickly. As time goes on and more data is analyzed, the probability of a correct decision is increased as if by learning through mistakes. An incorrect decision made previously would teach the computer to consider variables that before had been overlooked.
Put it to use
DL is currently being used in a variety of important ways. Some of these include self-driving cars, predicting the result of legal proceedings, recommending shows on Netflix, and even playing games. Scientists remain astonished that DL has brought us advancements that we never thought would be available so soon. Read more about these advancements and the Internet of Things here.
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