Microsoft announced Project Bonsai, the company’s machine teaching service to create and optimize intelligence for industrial control systems. According to the company, ’ Project Bonsai’ will transform industries. An engineer who does not have an AI expertise can build the most dynamic physical systems and processes with the help of this platform.

Control systems form a centre of many machineries across various sectors like manufacturing, chemical processing, construction, energy and mining, and so on. Project Bonsai helps to achieve calibration, and optimization to the control systems of robotic arms, bulldozer blades, forklifts, underground drills, rescue vehicles, wind and solar farms. This is Microsoft’s first service component towards the company’s vision to empower customers to build, operate, and manage autonomous systems.

So what is machine teaching? It is a complementary approach to machine learning says Microsoft. In machine teaching method, the system can derive knowledge from experts rather than gaining information from data alone. With machine teaching, engineers can stipulate the outcomes they need, concepts to be taught and safety criteria that should be adhered to. Thus an engineer without AI expertise can break a complex problem into more simplistic tasks and give the AI model relevant hints to find a fast solution. This helps users to know how the AI agents work and debug when they don’t. These AI agents can be deployed in a manner that best suits the operational needs – to the edge, cloud, or the device. “The Bonsai platform simplifies machine teaching with deep reinforcement learning so you can train and deploy smarter autonomous systems,” says the company.

According to Mark Hammond, Microsoft general manager for autonomous systems, this approach bridges AI science and software to the traditional engineering world, enabling fields such as chemical and mechanical engineering to build smarter, more capable, and more efficient systems by augmenting their own expertise with AI capabilities.