news    articles    opinions    tutorials    concepts    |    about    contribute     republish
by   -   September 30, 2020


This month saw the European Conference on AI (ECAI 2020) go digital. Included in the programme were five plenary talks. In this article we summarise the talk by Professor Carme Torras who gave an overview of her group’s work on assistive AI, and talked about the ethics of this field.

by   -   September 29, 2020
A “high quality” 3D-printed bioscaffold as designed with help from a machine learning algorithm developed at Rice University. Scale bar equals 1 millimetre. (Credit: Mikos Research Group/Rice University)

By Mike Williams

A team led by computer scientist Lydia Kavraki used a machine learning approach to predict the quality of scaffold materials produced by 3D-printing, given the printing parameters. The work also found that controlling print speed is critical in making high-quality implants.

by   -   September 28, 2020


Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Veena Dubal about the ethical crisis of the gig economy.

by   -   September 25, 2020

By Atia Cortés and Francesca Foffano, AI4EU Observatory

During this period of progressive development and deployment of artificial intelligence, discussions around the ethical, legal, socio-economic and cultural implications of its use are increasing. What are the challenges and the strategy, and what are the values that Europe can bring to this domain?

by   -   September 24, 2020

MIT professor announced as award’s first recipient for work in cancer diagnosis and drug synthesis.

by   -   September 23, 2020

By Rianne Lindhout

Apps that can precisely identify shards, coins or heel bones: archaeology has embraced artificial intelligence. Alex Brandsen is working on a search engine that scans vast quantities of text from an archaeological viewpoint.

by   -   September 22, 2020

By Eliza Kosoy, Jasmine Collins and David Chan

Despite recent advances in artificial intelligence (AI) research, human children are still by far the best learners we know of, learning impressive skills like language and high-level reasoning from very little data. Children’s learning is supported by highly efficient, hypothesis-driven exploration: in fact, they explore so well that many machine learning researchers have been inspired to put videos like the one below in their talks to motivate research into exploration methods.

by   -   September 21, 2020

Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to John Havens about “Ethically aligned design & applied AI ethics”.

by   -   September 18, 2020

In this series of educational blog posts, we highlight components of data analysis by focusing on 7 topics. Each topic is based on key papers, book chapters or blog posts that we have discussed in class. For each topic, we highlight pitfalls to watch out for and propose solutions when possible, some inspired by the literature and others by class discussion. We invite the readers to share their comments with us to help us improve the posts.

by   -   September 17, 2020

With this year’s International Conference on Machine Learning (ICML) being over, it is time to have another instalment of this series. Similar to last year’s post, I shall cover several papers that caught my attention because of their use of topological concepts—however, unlike last year, I shall not restrict the selection to papers using topological data analysis (TDA).

by   -   September 16, 2020
©University of Cambridge

Researchers have used a combination of AI and quantum mechanics to reveal how hydrogen gradually turns into a metal in giant planets.

Dense metallic hydrogen – a phase of hydrogen which behaves like an electrical conductor – makes up the interior of giant planets, but it is difficult to study and poorly understood. By combining artificial intelligence and quantum mechanics, researchers have found how hydrogen becomes a metal under the extreme pressure conditions of these planets.

by   -   September 15, 2020


Building the New Economy is a work in progress book edited (and in large part authored) by Alex Pentland, Alexander Lipton, and Thomas Hardjono. It lays out a vision for a new economy, with data and AI at its heart, that is more resilient to crises.

by   -   September 14, 2020


By Misha Laskin, Aravind Srinivas, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel

A remarkable characteristic of human intelligence is our ability to learn tasks quickly. Most humans can learn reasonably complex skills like tool-use and gameplay within just a few hours, and understand the basics after only a few attempts. This suggests that data-efficient learning may be a meaningful part of developing broader intelligence.

by   -   September 11, 2020

Mary Gray

Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Mary Gray about “Ghost work and the role of compassion in tech ethics”.

by   -   September 10, 2020


Recent advances in computer vision have revolutionized many areas of research including robotics, automation, and self-driving vehicles. The self-driving car industry has grown markedly in recent years, in no small part enabled by use of state-of-the-art computer vision techniques. However, there remain many challenges in the field. One of the most difficult problems in autonomous driving is perception. Once autonomous vehicles have an accurate perception of the world around them, planning and control become easier. This article primarily focuses on perception with computer vision and capabilities of computer vision and neural networks for use in fully autonomous self-driving vehicles.


supported by: