Deep Learning

What is Deep Learning?

Deep learning is the use of multi-layered neural networks to transform input data into successively higher-level values to produce results similar to human experts. “Deep” refers to the number of layers of transformation between input and output, while “learning” refers to the ability to adjust transformations to improve the accuracy of the output according to some defined metrics. Deep learning techniques can be applied to a variety of use cases such as image recognition, speech recognition, natural language processing, and pattern recognition.


Why is Deep Learning Important?

Deep Learning can produce results that are comparable to and sometimes surpass human expert performance and can do so at a scale no human can match. For example, deep learning systems have advanced to the point of matching the accuracy of human experts at identifying cancer in medical images.


How Enables Organizations to Leverage Deep Learning provides a scalable platform – the C3 AI® Suite – that supports the application of deep learning to enterprise AI. This complete, end-to-end platform enables designing, developing, deploying, and operating enterprise AI applications at industrial scale. With the C3 AI Suite, organizations can accelerate development of enterprise AI applications on cloud platforms including AWS and Azure 25-fold and deploy in one-tenth the time of other approaches. Because of’s revolutionary model-driven architecture, applications developed with the C3 AI Suite can run on any cloud with little or no change to the application code. also delivers a portfolio of prebuilt, SaaS enterprise AI applications for a growing number of use cases such as predictive maintenance, inventory optimization, fraud detection, and anti-money laundering. Some of the world’s largest organizations – including Shell, the US Department of Defense, Enel, and Koch Industries – use technology to drive digital transformation initiatives that significantly reduce costs, increase asset availability and reliability, improve human safety, and enhance customer satisfaction. These applications run out of the box on the leading cloud platforms. A application can be configured to take advantage of microservices available from different cloud providers – for example, AWS’s image recognition can be combined with Google’s natural language processing in the same application.