Convolutional neural networks (CNNs) are a form of deep neural network that uses convolution instead of general matrix multiplication between the network layers. Convolution provides a more effective approach to computing transformations to accomplish image recognition, natural language processing, video recognition, image classification, and anomaly detection.
Convolutional neural networks have become the foundation for image recognition in a wide variety of applications, from recognizing handwritten ZIP codes on mail to identifying cancer in medical images to distinguishing different breeds of dog. CNNs can classify and describe a library of millions of images to enable search and further analysis with other data sources.
C3 AI provides a scalable platform – the C3 AI® Application Platform – that supports the application of convolutional neural networks to enterprise AI and provides a complete, end-to-end platform for designing, developing, deploying, and operating enterprise AI applications at industrial scale. With the C3 AI Application Platform, 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 C3 AI’s revolutionary model-driven architecture, applications developed with the C3 AI Application Platform can run on any cloud with little or no change to the application code.
C3 AI also delivers a portfolio of prebuilt, SaaS enterprise AI applications for a growing number of use cases such as Reliability, C3 AI Inventory Optimization, C3 AI Fraud Detection, and C3 AI Anti-Money Laundering. Some of the world’s largest organizations – including Shell, the US Department of Defense, Enel, and Koch Industries – use C3 AI 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 C3 AI 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.