Computer vision has significantly advanced over the past decade thanks to large-scale benchmarks. More recent computer vision research has tackled active tasks, which require both perception and action. The First Embodied AI Workshop, co-organized by Google at CVPR 2020, hosted several benchmark challenges for active tasks. This year, Stanford and Google are proud to announce a new version of the iGibson Challenge on Interactive and Social Navigation. The challenge explores how robots can learn to interact with people and objects in their environments.
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Open AI, founded by Elon Musk, has discovered that their artificial neural network CLIP shows behavior strikingly similar to a human brain. This find make scientists hopeful for the future of AI networks' ability to identify images in a symbolic, conceptual and literal capacity. The first biological neuron recorded to operate in a similar fashion was the "Halle Berry" neuron. Open AI's multi-modal vision system continues to outperfom existing systems.
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Facebook has developed SEER (Self-Supervised) - a Deep learning solution able to register images on the Internet independent of categorised and labeled data sets. SEER performed better than the most advanced self-supervised systems. It has a 60.5 percent accuracy rate when trained on only 1 percent of the same data set.
Read more at ai.facebook.com