Source: TechCrunch.com
If AI is going to work its way out of the chat box and into our living rooms, it will need to understand spaces and objects better. To further that work, the Allen Institute for AI has created a gigantic and diverse database of 3D models of everyday objects, so simulations for AI models can be that much closer to reality.
Simulators are basically 3D environments meant to represent real places that a robot or AI might have to navigate or understand. But unlike, say, a modern console game, training simulators are far from photorealistic and often lack detail, variation or interactivity.
Objaverse, as it is awkwardly yet somehow pleasingly named, aims to improve this with its collection of over 800,000 (and growing) 3D models with all kinds of metadata. The things represented range from types of food to tables and chairs to appliances and gadgets. Any relatively ordinary object you might expect to see in a home, office or restaurant is represented here.
It’s meant to replace aging object libraries like ShapeNet, an old standby database with about 50,000 less detailed models. If the only “lamp” your AI has ever seen is a generic one with no pattern or color, how can you expect it to recognize a funky cut-glass one or one with a totally different shape? Objaverse includes variations on common objects so the model can learn what defines them despite their differences….