Google has launched the second iteration of its no-code Teachable Machine so that inexperienced users can take their bespoke machine learning (ML) models and apply them to projects such as classroom activities. Teachable Machine 2.0 carries over the features from the original, allowing users to record images and video from a webcam and use them to train ML models for tasks like pattern recognition. Now, these same models can be taken and exported to websites, apps and physical machines. Open source curriculums are making use of the tool to give children their first taste of ML, without the intimidating aspect of learning to code. One such example is a programme run out of MIT's Media Lab by education researcher Blakeley H. Payne for six to 10-year olds.

Google has launched the second iteration of its no-code Teachable Machine so that inexperienced users can take their bespoke machine learning (ML) models and apply them to projects such as classroom activities. Teachable Machine 2.0 carries over the features from the original, allowing users to record images and video from a webcam and use them to train ML models for tasks like pattern recognition. Now, these same models can be taken and exported to websites, apps and physical machines. Open source curriculums are making use of the tool to give children their first taste of ML, without the intimidating aspect of learning to code. One such example is a program run out of MIT's Media Lab by education researcher Blakeley H. Payne for 6 to 10 year olds.

Google has upgraded its Teachable Machine, an in-browser web experiment it originally released in 2017 to teach people some basic principles of machine learning. The original version of the app was really just a fun little experiment that could be used to classify visual data from your webcam. But Google has added new modes to the system along with the option to export trained models, making Teachable Machine 2.0 a more functional system for building actual AI tools. Along with image data, Teachable Machine now works with audio and body pose input. Users can upload their own pre-collected datasets, sort data into more than three categories, and download and deploy their models locally or host them in the cloud.

Google two years ago launched Teachable Machine, a web experiment intended to elucidate machine learning concepts. It let any user with a webcam train an AI model to output specific media -- an image, sound, speech, or GIF -- corresponding with a hand gesture, object, or activity. Now Teachable Machine is expanding to incorporate inputs beyond those it initially supported, including audio. Additionally, it will allow folks to export their trained models to websites, apps, devices, and more. Google says it worked with people across industries with different needs -- like architect Steve Saling, who has amyotrophic lateral sclerosis (ALS) -- to test and shape the new Teachable Machine.

Sign in to report inappropriate content. Teachable Machine 2.0 makes it fast and easy to create machine learning models for your projects, no coding required. Train a computer to recognize your images, sounds, & poses, then export your model for your sites, apps, and more https://g.co/teachablemachine