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Other Cambridge events

I think, therefore AI

Please note this venue is mostly accessible but has one step when first entering.
Past event - 2018
15 May Doors open at 18:30
Start time 19:00
End time 21:30
Panton Arms, 43 Panton Street,
Cambridge CB2 1HL
Sold Out!
Can machines think? What does it really mean to be intelligent? From the nitty-gritty of neural networks, to the big questions surrounding cognitive computing, experts in the field will lead you through the key concepts so you can start thinking about these questions, before machines do first! Please note that although this event takes place on the ground floor, there is no step-free access or disabled toilet at the venue.

AI: Generative Adversarial Networks

Petar Veličković (Research Assistant in Computational Biology, University of Cambridge)
Machine learning is, in essence, about understanding the world
through data. And as Richard Feynman once said: "What I cannot create, I
do not understand". This leads us to generative modelling: being able
to generate new, synthetic data that in some way captures the features
of real data. I will present a high-level overview of generative
adversarial networks (GANs), one of the most popular ideas to hit
machine learning in the past decade and show, among other things, how
they allow us to generate fake celebrities and turn horses into zebras
(and vice-versa).

AI: Not as scary as you might think

Steve Steele (Product Marketer in the Machine Learning Group at ARM)
The media often talks about Artificial Intelligence (AI) in quite
negative terms; from ‘AI will destroy your job’ to ‘killer robots on
the prowl’. The truth is that AI techniques such as Machine Learning
(ML) can offer many positive benefits to individuals and society as a
whole. But good news will never grab the headlines! This talk looks at
how consumer devices will soon support levels of AI and ML performance
that can make many of those benefits a reality in our everyday lives.

Insightful AI

Marta Halina (University Lecturer at Cambridge University)
In March 2016, Google DeepMind’s computer programme AlphaGo defeated the world-champion Go player. AlphaGo’s moves were surprising, original, “beautiful”, and extremely effective. Should we understand AlphaGo as exhibiting human-like insight? In this talk, I draw on research in cognitive psychology to evaluate contemporary progress in AI and examine how tests for identifying mental models in nonhuman organisms may help us interpret Deep Neural Networks.
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