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#NeurIPS2020 invited talks round-up: part two – the real AI revolution, and the future for the invisible workers in AI

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In this post we continue our summaries of the NeurIPS invited talks from the 2020 meeting. Here, we cover the talks by Chris Bishop (Microsoft Research) and Saiph Savage (Carnegie Mellon University). Chris began his talk by suggesting that now is a particularly exciting time to be involved in AI. What he termed "the real AI revolution" has nothing to do with artificial general intelligence (AGI), but is driven by the way we create software, and hence new technology. Machine learning is becoming ubiquitous and can be used to solve many problems that cannot, yet, be solved using other methods.


Webinar on "Macro dynamics predictions in COVID-19 crisis, explained by micro intentions"

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On 3 June 2020, the VUB AI Experience Centre published a webinar on the topic of the role of AI in the COVID-19 crisis, focused on macro dynamics predictions in the COVID-19 crisis, explained by micro intentions. This webinar focused on AI reinforcement learning techniques and predictive modelling, decision making in defining prevention, and exit strategies. It was led by Prof. dr. Ann Nowé from the Artificial Intelligence Lab together with Prof. dr Kurt Barbé, member of the Digital Mathematics research group and the cross-faculty Artificial Intelligence Lab, and Prof. dr Tom Lenaerts who is a member of the VUB Artificial Intelligence Lab and the Machine Learning Group of the ULB. The AI Experience Centre is a joint project of 4 VUB research groups: the Artificial Intelligence Lab, Brubotics, SMIT and ETRO, and is located on the VUB campus Etterbeek.


EvolveGraph: dynamic neural relational reasoning for interacting systems

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Multi-agent interacting systems are prevalent in the world, from purely physical systems to complicated social dynamic systems. The interactions between entities / components can give rise to very complex behavior patterns at the level of both individuals and the multi-agent system as a whole. Since usually only the trajectories of individual entities are observed without any knowledge of the underlying interaction patterns, and there are usually multiple possible modalities for each agent with uncertainty, it is challenging to model their dynamics and forecast their future behaviors. We introduce a generic trajectory forecasting framework (named EvolveGraph) with explicit relational structure recognition and prediction via latent interaction graphs among multiple heterogeneous, interactive agents. Considering the uncertainty of future behaviors, the model is designed to provide multi-modal prediction hypotheses.


One Hundred Year Study on Artificial Intelligence (AI100) – a panel discussion at #IJCAI-PRICAI 2020

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The mission of AI100 is to launch a study every five years, over the course of a century, to better track and anticipate how artificial intelligence propagates through society, and how it shapes different aspects of our lives. This IJCAI session brought together some of the people involved in the AI100 initiative to discuss their efforts and the direction of the project. The goals of the AI100 are "to support a longitudinal study of AI advances on people and society, centering on periodic studies of developments, trends, futures, and potential disruptions associated with the developments in machine intelligence, and formulating assessments, recommendations and guidance on proactive efforts". Working on the AI100 project are a standing committee and a study panel. The first study panel report, released in 2016, can be read in full here.


Radical AI podcast: featuring Moses Namara

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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 Moses Namara about the new Black in AI academic program. In this episode, we interview Moses Namara of Black in AI about the new Black in AI academic program, a program that serves as a resource to support black junior researchers as they apply to graduate programs, navigate graduate school, and enter the postgraduate job market. Moses Namara is a Facebook Research Fellow and Ph.D. candidate in Human-Centered Computing (HCC) at Clemson University. He uses interdisciplinary research methods from computer science, psychology, and the social sciences to understand the principles behind users' adoption and use of technology, decision-making, and privacy attitudes and behaviors.


CLAIRE COVID-19 Initiative Video Series: Meet the Team Leaders – Emanuela Girardi

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CLAIRE, the Confederation of Laboratories for AI Research in Europe, launched its COVID-19 Initiative in March 2020 as the first wave of the pandemic hit the continent. Its objective was to coordinate volunteer efforts from its members to contribute to tackling the effects of the disease. The taskforce was able to quickly gather a group of about 150 researchers, scientists and experts in AI organized into seven topic groups: epidemiological data analysis, mobility data analysis, bioinformatics, medical imaging, social dynamics monitoring, robotics, and scheduling and resource management. We brought you a comprehensive article about the activities of this initiative in one of last month's AI for Good series posts. You can read more about the outcomes and experience of this bottom-up approach in the article: The CLAIRE COVID-19 Initiative: a bottom-up effort from the European AI community.


Recent and forthcoming machine learning and AI seminars: January 2021 edition

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This post contains a list of the AI-related seminars that are scheduled to take place between now and the end of February 2021. We've also listed recent past seminars that are available for you to watch. All events detailed here are free and open for anyone to attend virtually. This list includes forthcoming seminars scheduled to take place between 15 January and 28 February. Zero-shot (human-AI) coordination (in Hanabi) and ridge rider Speaker: Jakob Foerster (Facebook, University of Toronto & Vector Institute) Organised by: University College London Zoom link is here.


Interview with Guillem Alenyà – discussing assistive robotics, human-robot interaction, and more

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His research activities include assistive robotics, robot adaptation, human-robot interactions and grasping of deformables. We spoke about some of the projects he is involved in and his plans for future work. The SOCRATES project is about quality of interaction between robots and users, and our role is focussed on adapting the robot behaviour to user needs. We have concentrated on a very nice use case: cognitive training of mild dementia patients. We are working with a day-care facility in Barcelona and asked if we could provide some technological help for the caregiver.


Tweet round-up from #IJCAI-PRICAI 2020

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The 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020) is in full swing. The event started on 7 January and will run until 15 January. Here, we capture the first few days of the conference through tweets from attendees. Wandering around the #IJCAI2020 venue is fun! It's basically equipped with most of what's in the physical venue -- coffee, pub, beach (when you are tired), and the gate to hyperspace! pic.twitter.com/dIzwn2MZmu


High-performance computing and AI team up for COVID-19 diagnostic imaging

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The Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE) taskforce on AI & COVID-19 supported the creation of a research group focused on AI-assisted diagnosis of COVID-19 pneumonia. The first results demonstrate the great potential of AI-assisted diagnostic imaging. Furthermore, the impact of the taskforce work is much larger, and it embraces the cross-fertilisation of artificial intelligence (AI) and high-performance computing (HPC): a partnership with rocketing potential for many scientific domains. Through several initiatives aimed at improving the knowledge of COVID-19, containing its diffusion, and limiting its effects, CLAIRE's COVID-19 taskforce was able to organise 150 volunteer scientists, divided into seven groups covering different aspects of how AI could be used to tackle the pandemic. Emanuela Girardi, the co-coordinator of the CLAIRE taskforce on AI & COVID-19, supported the setup of a novel European group to study the diagnosis of COVID-19 pneumonia assisted by artificial intelligence.