news    articles    opinions    tutorials    concepts    |    about    contribute     republish
by   -   October 3, 2019

Every month, we gather some of the most interesting tweets capturing latest results, debates, and events.

by   -   October 3, 2019

Inspired by a WIRED profile of Karl Friston, Michael Littman and Dave Ackley talk about theories of everything, and theories thereof.

by   -   October 3, 2019

By Anusha Nagabandi

Dexterous manipulation with multi-fingered hands is a grand challenge in robotics: the versatility of the human hand is as yet unrivaled by the capabilities of robotic systems, and bridging this gap will enable more general and capable robots. Although some real-world tasks (like picking up a television remote or a screwdriver) can be accomplished with simple parallel jaw grippers, there are countless tasks (like functionally using the remote to change the channel or using the screwdriver to screw in a nail) in which dexterity enabled by redundant degrees of freedom is critical. In fact, dexterous manipulation is defined as being object-centric, with the goal of controlling object movement through precise control of forces and motions — something that is not possible without the ability to simultaneously impact the object from multiple directions. For example, using only two fingers to attempt common tasks such as opening the lid of a jar or hitting a nail with a hammer would quickly encounter the challenges of slippage, complex contact forces, and underactuation. Although dexterous multi-fingered hands can indeed enable flexibility and success of a wide range of manipulation skills, many of these more complex behaviors are also notoriously difficult to control: They require finely balancing contact forces, breaking and reestablishing contacts repeatedly, and maintaining control of unactuated objects. Success in such settings requires a sufficiently dexterous hand, as well as an intelligent policy that can endow such a hand with the appropriate control strategy. We study precisely this in our work on Deep Dynamics Models for Learning Dexterous Manipulation.

by   -   August 16, 2019


#IJCAI2019 ended today. Besides talks, panel discussions, and presentations; the winners of this year’s prestigious IJCAI awards shared their opinions about relevant future directions in the field.

by   -   August 14, 2019

By Nicholas Carlini

It is important whenever designing new technologies to ask “how will this affect people’s privacy?” This topic is especially important with regard to machine learning, where machine learning models are often trained on sensitive user data and then released to the public. For example, in the last few years we have seen models trained on users’ private emails, text messages, and medical records.

This article covers two aspects of our upcoming USENIX Security paper that investigates to what extent neural networks memorize rare and unique aspects of their training data.

Specifically, we quantitatively study to what extent following problem actually occurs in practice:

by   -   August 14, 2019

Meet Claus Aranha, Assistant Professor at the University of Tsukuba, Center of Artificial Intelligence Research (C-AIR).

by   -   August 14, 2019

Like yesterday, we bring you the best tweets covering major talks and events at IJCAI 2019.

by   -   August 13, 2019

The team behind the Libratus program were today announced as the latest recipients of the Marvin Minsky Medal, given by the IJCAI organisation for Outstanding Achievements in AI. Libratus made headlines in January 2017 when it beat a team of champion human poker players in a 20-day no-limit tournament.

by   -   August 13, 2019


The main IJCAI2019 conference started on August 13th. The organizers gave the opening remarks and statistics, and announced the award winners for this year.

by   -   August 13, 2019

Robots are helping conference-goers at IJCAI 2019 this week.

You can get a souvenir from “Dorabot” by showing your badge, or get rid of your glass at the welcome reception.

by   -   August 12, 2019

Meet Dimmy Wang who presented his work at the Deep Learning Workshop at IJCAI 2019. He graduated with a Masters from Tshinghua University and currently works as a researcher at Tencent Cloud AI.

by   -   August 12, 2019

Here’s our daily update in tweets, live from IJCAI (International Joint Conference on Artificial Intelligence) in Macau. Like yesterday, we’ll be covering tutorials and workshops.

by   -   August 11, 2019

By Jessica Montgomery, Senior Policy Adviser

As concerns about the impact of climate change (PDF) grow, so too is the debate about the environmental impact of artificial intelligence (AI) technologies.

by   -   August 11, 2019


The first two days at IJCAI (International Joint Conference on Artificial Intelligence) in Macau were focussed on workshops and tutorials. Here’s an overview in tweets.

Allen School professor Pedro Domingos has been selected as the 2019 recipient of the John McCarthy Award from the International Joint Conference on Artificial Intelligence (IJCAI). The award, which is named for one of the founders of the field of AI, recognizes established, mid-career researchers who have amassed a track record of significant research contributions that have been influential in advancing the field. Domingos is being honored by the IJCAI for his multiple contributions in machine learning and data science and for advancements in unifying logic and probability.


supported by: