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Nello Cristianini - January 24, 2020
Is our autonomy affected by interacting with intelligent machines designed to persuade us? That’s what researchers at the University of Bristol attempted to find out through an analysis of the interaction between intelligent software agents and human users.
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The Conversation - January 23, 2020
By Ara Darzi, Imperial College London
It is not often that one witnesses a transformational advance in medicine. But the application of artificial intelligence (AI) to improve the early detection of disease is exactly that.
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Computing Up - January 22, 2020
Michael Carbin, Assistant Professor of Electrical Engineering and Computer Science at MIT, joins Michael Littman and Dave Ackley to discuss neural net lottery tickets, computing with uncertainty and more.
AI Education Matters: A first introduction to modelling and learning using the data science workflow
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AI Matters and Marion Neumann - January 21, 2020
AI Education Matters is a regular feature in the AI Matters newsletter. Here, Marion Neumann explains the teaching methods she uses to expose students to the ideas and working principles of AI technology.
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Lucy Smith - January 20, 2020
The United States Office of Science and Technology Policy has released draft guidance for regulation that it proposes agencies must adhere to when drawing up new AI regulations for the private sector. The document includes 10 “Principles for the Stewardship of AI Applications”.
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Michael Littman - January 20, 2020
The NeurIPS outstanding paper awards highlight some of the most notable papers at the conference. Find out who won the awards and read summaries of their work below.
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Lucy Smith - January 17, 2020
It has been reported that Sweden is extending its investment in AI. An extra SEK 1.3 billion has been pledged that will extend the current programme by another three years, until 2029.
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BAIR blog - January 16, 2020
By Aviral Kumar
One of the primary factors behind the success of machine learning approaches in open world settings, such as image recognition and natural language processing, has been the ability of high-capacity deep neural network function approximators to learn generalizable models from large amounts of data. Deep reinforcement learning methods, however, require active online data collection, where the model actively interacts with its environment.
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Lucy Smith - January 14, 2020
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Nedjma Ousidhoum - January 10, 2020
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Lucy Smith - January 8, 2020
Climate change was one of the many topics covered at NeurIPS 2019 (the Thirty-third Annual Conference on Neural Information Processing Systems), with a day-long workshop dedicated to the theme. The session was organised by Climate Change AI, a group of volunteers from academia and industry that seeks to facilitate work in climate change and machine learning.
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Sabine Hauert - December 24, 2019
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Sabine Hauert - December 13, 2019
Couldn’t make it to NeurIPS this week in Vancouver? Or simply unable to make your way to every exciting talk through the maze of 16k participants? Luckily, many of the sessions are available online.
To get started, we’ve embedded the invited talks below.
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Sabine Hauert - December 8, 2019
The 33rd annual Conference on Neural Information Processing Systems (NeurIPS), happening this week in Vancouver, brings together more than 10k researchers and practitioners from all fields engaged in fundamental work in Machine Learning and Artificial Intelligence.
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AIhub Editor - December 7, 2019
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