TWIML AI
Waves may become a new computational primitive for neural networks
Better training objectives can improve controllability in image generation
Weight space learning could dramatically reduce the cost of developing specialized models
AI has advanced for more than a decade by training ever-larger models on ever-larger datasets
Future AI systems may be trained on collections of existing models instead of raw data
Waves may become a new computational primitive for neural networks
Weight space learning could dramatically reduce the cost of developing specialized models
Future AI systems may be trained on collections of existing models instead of raw data
Olfactory intelligence could eventually power applications including disease detection, emotion sensing, and consumer devices beyond fragrance