Human-Machine Collaboration
Stories
Using AWS to analyse Elephant Rumbles
Elephants generate a wide range of vocalisations to communicate with one another, such as snorts, trumpets and infrasonic rumbles. Since these rumbles are so low frequency, they cannot be heard by the human ear, but can be detected either by microphones or seismometers.
New human-machine collaborations unlock society’s big challenges
AWS blog on the Oxford X-Reality Hub Ed Tech project, which set out to investigate how virtual reality (VR) could transform the classroom experience and close the gap between disadvantaged groups of pupils who statistically do less well than their peers.
Towards Efficient and Generalizable Dexterous Manipulation with Reinforcement Learning using AWS
By Zheng Xiong, AIMS CDT Student. Despite that robots driven by hard-coded instructions have achieved great success in the past decades, their applications are still quite limited in highly controlled scenarios due to the lack of adaptability to flexible environments with unforeseen variations. Reinforcement learning (RL) has the potential to tackle these challenges.
Learning How to Learn Where You Are: Meta-Learning for Few-Shot Camera Localization using AWS
By Dominik Kloepher, AIMS CDT Student. In this project, we looked at the task of camera localization: given a number of images of a scene (a room, a street, …) and the positions and viewing directions from which they were taken (together, these are the camera pose), can we determine the camera pose from which a new, unseen image was taken? A method that could do so reliably and quickly would find use in many different fields, from robotics and autonomous driving to augmented reality applications.