TinyML is the latest from the world of deep learning and artificial intelligence. It brings the capability to run machine learning models in a ubiquitous microcontroller – the smallest electronic chip present almost everywhere. Microcontrollers are the brain for many devices that we use almost every day. From a TV remote controller to the elevator to the smart speaker, they are everywhere. Multiple sensors that can emit telemetry data are connected to a microcontroller.

Intel announced Nauta, an open source deep learning project based on Kubernetes. The project comes with select open source components and Intel-developed custom applications, tools, and scripts for building deep learning models. According to Intel, Nauta provides a multi-user, distributed computing environment for running deep learning model training experiments on systems based on Intel Xeon processor. The software foundation for the distributed platform is built on Kubernetes – industry's leading container orchestration engine. Mainstream deep learning tools and frameworks such as TensorFlow, TensorBoard and Jupyter Hub are tightly integrated with the platform.

Computers are getting to be more intelligent, although machine intelligence involves more than a single concept. It's common to hear "AI," "cognitive computing," "machine learning" and "deep learning" used in everyday conversation, although the terms are often misused. Whether you're a practitioner, IT leader, or business leader, you should understand the differences. Following are some basic explanations that explain the value of each. Even if you feel you understand these terms, use this article to help your bosses understand what they want when they are clamoring for "some of that AI." Cognitive computing is the sensory branch of machine intelligence.