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machine learning

Futuremakers

Is AI good for our health?

Join our host, philosopher Peter Millican, as he explores the topic "Is AI good for our health?"
Textual Therapies

Computational Literary Studies and Mental Health

A project combining English literature, experimental psychology, and computational linguistics, with a focus on entropy, abstraction, and mental health.
Oxford Physics Public Lectures
Captioned

How do we find planets around other stars?

The 3rd Wetton lecture, 19th June 2018 delivered by Professor David W. Hogg, Center for Cosmology and Particle Physics, New York University
Big Questions - with Oxford Sparks

How do you teach a robot social cues?

As robots are increasingly deployed in settings requiring social interaction we asked the Big Question: How do you teach a robot social cues? To find out we visited Shimon Whiteson, Associate Professor at the Department of Computer Science
Big Questions - with Oxford Sparks

How do you teach a machine to a drive a car?

Autonomous cars have been a staple of science fiction for years featuring in films like Minority Report and I Robot. But how far away are we really from enjoying a hassle-free driving journey? To find out the answer we visited Dr Ingmar Posner, Associate
Strachey Lectures

Strachey Lecture: Probabilistic machine learning: foundations and frontiers

Professor Zoubin Ghahramani gives a talk on probabilistic modelling from it's foundations to current areas of research at the frontiers of machine learning.
Oxford Physics Public Lectures
Captioned

At a Physics Info/Sci Intersection

Physics Colloquium 30th October 2015 delivered by Professer Paul Ginsparg
Big Questions - with Oxford Sparks

'Artificial Intelligence' part 2 - How to create machines that learn

Professor Nando de Freitas explains that understanding how our brains work has helped us create machines that learn, and how these learning machines can be put to completing different tasks.
Big Questions - with Oxford Sparks

'Artificial Intelligence' part 1 - Using artificial intelligence to spot patterns

Professor Stephen Roberts explains how machines, whose job it is simply to learn, can help researchers spot scientific needles in data haystacks, which will help us solve some grand challenges.

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