Explore the concepts of machine teaching, allowing developers or subject matter experts with little AI expertise to provide abstract concepts to an intelligent system.Learn about machine teaching
Today’s standard approach for machine learning is to provide machines with a lot of data and expect them to learn associations or find patterns on their own. However, the desire to use AI for more scenarios has grown.
For these scenarios, use subject matter experts to break a problem into easier tasks and give machine learning models important clues about how to find a solution faster—similar to the concept of lesson plans.
Microsoft scientists and product developers have pioneered this technique called machine teaching, which seeks to gain knowledge from people rather than extracting knowledge from data alone.
Machine teaching 101
Learn the basics of machine teaching and get details on the demos available in this lab project.
Machine teaching architecture
With machine teaching, systems attain knowledge from people in addition to data. An expert for a specific task provides a limited number of examples for each step in the process. These examples serve as lesson plans to help machine learning algorithms complete the task, adapting their approach as needed. Once trained in the Cloud through simulations and with Inkling – a language that teaches a concept via a State-Action-Rewards cycle-, the brain will be deployed to the edge in order to communicate states and actions on an autonomous device.
Technical details for machine teaching
With machine teaching, systems attain knowledge from people in addition to data. An expert for a specific task provides a limited number of examples for each step in the process. These examples serve as lesson plans to help machine learning algorithms complete the task, adapting their approach as needed.
Check out these interactive demos for a closer look at machine teaching in action:
- Smart Buildings: HVAC systems comprise most of commercial energy consumption. Traditional controls struggle to save energy keep CO2 levels safe while keeping occupants comfortable. This demo is about reducing energy consumption while maintaining occupant comfort and CO2 safety in a conference room.
- Machine Calibration: CNC machines cut metal with spinning tools. Friction reduces precision and periodically demands recalibration. An expert operator must travel to calibrate the machine, repeatedly turn the knobs and take measurements until the machine regains precision. This demo focuses on calibrating a CNC machine faster and more precisely than expert operators.
- Motion Control: Motion control automates machines or parts of machines like oil rigs that drills horizontally underground. An operator controls the drill underground with a joystick to keep the drill inside oil shale while avoiding obstacles. This demo shows how to automate control of a horizontal oil drill according to a predefined drilling plan.
Intelligent robotics uses AI to increase collaboration between people and devices. Microsoft AI enables the next generation of robots to adapt to dynamic situations and communicate naturally with people.
AirSim - Drones
AirSim is a simulation tool that creates a 3D version of a real environment. A simulated drone “flies” to capture images, building a custom vision model. AI uses the vision model to identify objects or people.
Machine Reading Comprehension (MRC) answers questions about written text. Using a neural network, MRC mimics the process of human readers. Ask a question and MRC reads a document until an answer is formed.
Spektacom uses a mini sticker sensor on a cricket bat to gather data on the quality, speed, twist, and swing of the bat. This data is used to analyze the quality of the shot to help professionals, amateurs, and coaches improve their game.
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