Deep Learning

Many companies have adopted catch phrases such as artificial intelligence, machine learning, and deep learning. Given the complexity of some of these methods and associated jargon, it can be hard for the consumer or company to wrap their heads around what exactly is meant by some of these terms.

Artificial intelligence encompasses a broad range of techniques that range in complexity from simple probabilistic reasoning to highly complex algorithms. Machine learning is often used interchangeably with artificial intelligence. Conventional machine learning uses statistical or correlational methods to make decisions.

Recently, a subcategory of artificial intelligence called deep learning has achieved record-breaking performance in natural language processing, image recognition, and audio classification. Unlike conventional machine learning, deep learning does not assume any understanding of the underlying problem. Instead, deep learning algorithms are designed to create their own set of features that best describe the nature of the problem.

Humans are very good at facial recognition but scientists have not been able to reduce our understanding of facial recognition to a set of geometric relationships. Deep learning excels at these types of problems by letting a neural network find sets of edges, textures and shapes that are good descriptors of a face.

Similarly, semantics of text has been difficult to categorize using a set of strict logical rules. Deep learning addresses this problem by dynamically creating an understanding of how each word within a sentence interplays and influences every other word within the sentence. By pushing the envelope of deep learning innovation, Soteria Intelligence continues to be the most technologically advanced social medial analytics company in the world.

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