We are looking forward to welcoming Nando de Freitas, Principal Scientist at DeepMind.
About the event
Training a large neural network with lots of data and subsequently deploying this model to carry out specific tasks, such as speech recognition, machine translation, game playing, image recognition, image and text generation, text-to-speech, and lipreading has been incredibly fruitful.
Instead of focusing on few tasks with massive amounts of data, this talk will focus on training neural networks to solve many tasks with few data each. The objective is not to learn a fixed-parameter classifier, but rather to learn a “prior” neural network that can be adapted rapidly to solve new tasks with few data. The output of training is no longer a fixed model, but rather a fast learner. That is, the goal is to build tools that learn.
18:00-18:30 - Registration
18:30-18:35 - Welcome and introduction - Mark Briers (The Alan Turing Institute, UK)
18:35-19:25 - Learning how to learn efficiently - Nando de Freitas (Google DeepMind, UK)
19:25-19:40 - Q&A - Nando de Freitas and Mark Briers
19:40-20:30 - Drinks reception
Some technical knowledge required