'Life Tags' Makes Millions of Photos From 'Life' Searchable
References: engadget & artsexperiments.withgoogle
Machine-learning algorithms are getting increasingly sophisticated in what they can recognize, and Google is demonstrating just how powerful its artificial intelligence can be with a new tool called 'Life Tags'. The system sorts through a database of over 4 million images, classifying them based on keywords and making that massive trove of photography easily searchable.
Life Tags gets its name from Life magazine, the famous publication that ran for over 70 years. During that time, the magazine commissioned millions of photos (although the majority of those never ended up in print). Life Tags pulls from the archives of Life, giving it an ample and varied pool of source images to categorize.
For those without inspiration, the homepage of the tool categorizes every keyword that the algorithm came up with into a sort of machine dictionary. Those looking for something specific can use the search bar at the top.
Life Tags gets its name from Life magazine, the famous publication that ran for over 70 years. During that time, the magazine commissioned millions of photos (although the majority of those never ended up in print). Life Tags pulls from the archives of Life, giving it an ample and varied pool of source images to categorize.
For those without inspiration, the homepage of the tool categorizes every keyword that the algorithm came up with into a sort of machine dictionary. Those looking for something specific can use the search bar at the top.
Trend Themes
1. Machine-learning Photo Sorting - Developing machine-learning algorithms to classify and sort through large archives of images for easy searching and categorization.
2. Automated Photo Tagging - Developing software tools to automatically tag photos with relevant keywords and categories, making them easily searchable and sortable.
3. Artificial Intelligence for Photo Management - Using artificial intelligence and deep learning algorithms to help manage, categorize, and search through large collections of photos and other digital media assets.
Industry Implications
1. Digital Asset Management - Developing new software applications and platforms for managing and organizing large collections of digital media assets, including photos, videos, and audio files.
2. Stock Photography - Developing new tools and applications for stock photo agencies to better manage and categorize their collections, making them more easily searchable and accessible for customers.
3. Marketing and Advertising - Using machine-learning algorithms and artificial intelligence to help marketers and advertisers better manage their digital media assets, improve content targeting, and increase engagement with audiences.
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