machine learning and data mining

Machine learning, Edge computing and Serverless: the future of technology

Machine Learning, Edge Computing and Serverless are the three key technologies that will redefine the Cloud Computing platforms.

  • Machine Learning (ML) is becoming an integral part of modern applications. From the web to mobile to IoT, ML is powering the new breed of applications through natural user experiences and inbuilt intelligence.
  • Serverless is emerging as the next wave of compute services. Serverless or Functions as a Service (FaaS) attempts to simplify the developer experience by minimizing the operational overhead in deploying and managing code.
  • Edge Computing takes compute closer to the applications. Each edge location mimics the public cloud by exposing a compatible set of services and endpoints that the applications can consume.

These three emerging technologies – Serverless, Edge Computing and Machine Learning – will be the key technology drivers for the next generation of infrastructure.


Why are these technologies so important?

The availability of data, ample storage capacity, and sufficient computing power are essential for implementing Machine Learning.
Cloud becomes the natural fit for dealing with Machine Learning. Data Scientists are relying on the cloud for ingesting and storing massive datasets.

They are also using pay-as-you-go infrastructure for processing and analyzing the data. With cheaper storage and advanced computing platforms powered by GPUs and FPGAs, the cloud is fast becoming the destination for building complex ML models. In the future, while the heavy lifting for ML will be done in the cloud, the edge layer will simplify the deployment experience and Serverless will streamline the developer experience.