Published on February 28, 2018 by

Artificial intelligence could be the powerful tool we need to solve some of the biggest problems facing our world, argues Raia Hadsell. In this talk, she offers an insight into how she and her colleagues are developing robots with the capacity to learn. Their superhuman ability to play video games is just the start.

Raia is a senior research scientist on the Deep Learning team at DeepMind, with a particular focus on solving robotics and navigation using deep neural networks.

TEDxExeterSalon: From driverless cars to diagnosis of medical imaging, artificial intelligence is being heralded as the next industrial revolution. But how does AI relate to us in all our glorious complex humanity? Our first TEDxExeterSalon explored the ways in which we’ll interact with algorithmic intelligence in the near future.

TEDxExeter: Now in our 7th year, TEDxExeter is Exeter’s Ideas Festival with global reach, licensed by TED and organised by volunteers who are passionate about spreading great ideas in our community.

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Filming: Raia Hadsell is a research scientist on the Deep Learning team at DeepMind. She moved to London to join DeepMind in early 2014, feeling that her fundamental research interests in robotics, neural networks, and real world learning systems were well-aligned with the agenda of Demis, Shane, Koray, and other members of the original team. Raia’s research at DeepMind focuses on a number of fundamental challenges in AGI, including continual and transfer learning, deep reinforcement learning, and neural models of navigation. Raia came to AI research obliquely. After an undergraduate degree in religion and philosophy from Reed College, she veered off-course (on-course?) and became a computer scientist. Raia’s PhD with Yann LeCun, at NYU, focused on machine learning using Siamese neural nets (often called a ‘triplet loss’ today) and on deep learning for mobile robots in the wild. Her thesis, ‘Learning Long-range vision for offroad robots’, was awarded the Outstanding Dissertation award in 2009. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

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