Google's AI platform has already allowed users to match themselves up with artwork, but the company's latest Move Mirror system does more than just compare faces to priceless pieces of artwork. Release in a blog post on July 19, 2018, this new feature serves as a machine learning experiment that will hopefully inspire coders and makers to use Google tech in interesting ways. To create this AI feature, Google utilized two open-source programs known as PoseNet, which detects body poses, and TensorFlow.js, a library for in-browser machine learning framework.
Like Google Arts and Culture, Move Mirror utilizes a camera to track a user and them taps into a database to pull up an image similar to what the user is doing. None of the user's images are sent to any Google servers, with Move Mirror handling all the image recognition locally within the browser.
Image Credit: Google
What's Driving This Trend
- AI-matching
- Disruptive innovation opportunity: Develop AI platforms that match users' actions or movements with relevant images or content.
- Open-source Pose Detection
- Disruptive innovation opportunity: Create open-source programs for body pose detection that can be integrated into various applications and industries.
- In-browser Machine Learning
- Disruptive innovation opportunity: Explore the potential of in-browser machine learning frameworks to perform complex image recognition tasks without relying on external servers.
Who This Affects Most
- Art and Culture
- Disruptive innovation opportunity: Integrate AI-based image matching technology into art and culture platforms to enhance user engagement and interaction.
- Health and Fitness
- Disruptive innovation opportunity: Develop health and fitness applications that utilize pose detection technology to provide personalized workout recommendations.
- E-commerce
- Disruptive innovation opportunity: Utilize in-browser machine learning frameworks to offer personalized product recommendations based on user's body poses and movements.
