In this week’s Top 5 #AI stories:
See a new ImageNet speed record, an AI dance app, and a robot that can pick and toss over 500 objects per hour.
5 – Learning Semantic Embedding Spaces for Slicing Vegetables
Researchers from the Intelligent-Autonomous-Manipulation Lab at Carnegie Mellon University developed an AI-based robot that can automatically slice vegetables.
4 – Fujitsu Breaks ImageNet Record with V100 Tensor Core GPUs
Researchers from Fujitsu just announced a new speed record for training ImageNet to 75% accuracy in 74.7 seconds. The new record is faster than the previous test by more than 47 seconds achieved by Sony in November of last year.
3 – AI Helps NBA Players Dance on the Jumbotron
So you think you can dance? Earlier this month, the Dallas Mavericks of the NBA showed off a new deep learning in-game entertainment application that synthesized the dance moves of one of their star players on the team’s jumbotron.
2 – Jetson Nano Brings AI Computing to Everyone
Jetson Nano can run a wide variety of advanced networks, including the full native versions of popular ML frameworks like TensorFlow, PyTorch, Caffe/Caffe2, Keras, MXNet, and others. These networks can be used to build autonomous machines and complex AI systems by implementing robust capabilities such as image recognition, object detection and localization, pose estimation, semantic segmentation, video enhancement, and intelligent analytics.
1 – Google’s Tossingbot Can Toss Over 500 Objects Per Hour Into Target Locations
Researchers from Google, Princeton, Columbia and MIT developed a picking robot using physics and deep learning that can accurately toss random objects into bins two times faster than previous systems.