Strelka Institute for Media, Architecture and Design(https://strelka.com/en/) is a non-profit international educational project, founded in 2009 and located in Moscow. Strelka incorporates an education programme on urbanism and urban development aimed at professionals with a higher education, a public summer programme, the Strelka Press publishing house, and KB Strelka, the consulting arm of the Institute. Strelka has been listed among the top-100 best architecture schools in 2014, according to Domus magazine.^[1]

The Institute has been directed since 2013 by Varvara Melnikova.

Education programme

The Institute aims to educate the next generation of architects, designers and media professionals, enabling them to shape the 21st century world.^[2] Each year, Strelka welcomes young professionals and gives them the opportunity to work together with experts in the fields of urbanism, architecture and communications from all over the world. During this nine-month post-graduate programme, the researchers explore the issues related to Russia’s urban development through a multidisciplinary method conducted in English. Experimental methods, a holistic approach to architecture, media and design, and an emphasis on research are the main characteristics of the programme. The prominent architect and architecture theorist, Rem Koolhaas (AMO/OMA), contributed to the designing of the Institute’s education programme.^[3]

Since 2010, Yuri Grigoryan, architect and head of the Meganom architectural bureau], has served as director of the education programme.

Since 2012, the curriculum has been designed by two programming directors: Anastassia Smirnova – partner in the Rotterdam-based architecture and research bureau SVESMI, and David Erixon – founder of the Hyper Island school, and member of the Megafon board of directors.

The theme, programme structure and list of lecturers are updated every year. The 2013/14 programme includes a three-month introductory course composed of discussions, lectures and seminars, an urban development contest, work in one of four research studios, and a final exhibition of student projects.

Since 2016, Benjamin H. Bratton, design theorist and author of The Stack: On Software and Sovereignty, is programme director. The program theme, The New Normal, focuses on long-term urban futures in relation to technological, geographic and ecological complexities.

Some notable faculty at the Strelka Institute has been : Keller Easterling, Benjamin H. Bratton, Winy Maas, Brendan McGetrick, Anastassia Smirnova, Felix Madrazo, METASITU (Eduardo Cassina and Liva Dudareva), Joseph Grima, Laura Baird, metahaven (Vinca Kruk and Daniel van der Velden), Reinier De Graaf, Carlo Ratti, and Rem Koolhaas.

Summer at Strelka

From the end of May until mid September, Strelka’s courtyard hosts a public programme that is open to all. Its programme includes: lectures by prominent architects, urbanists, designers, social activists and scholars; discussions on topical urban issues; workshops; film screenings; theatre performances; concerts and fairs.

Strelka Press

Strelka Press publishes books and essays on modern issues of architecture, design and urban development in both English and Russian. The publishing house releases both printed and digital books.^[10] Strelka Press is based in London and Moscow. Senior editors of the publishing programme – Justin McGuirk and Andrey Kurilkin. Strelka Press has published books by Rem Koolhaas, Boris Groys, William Mitchell, Donald Norman, Keller Easterling, Vladimir Paperny, and others.

Microsoft’s Future Social Experiences(FUSE) Labs https://www.microsoft.com/en-us/research/ was started by Ray Ozzie and is run by Lili Cheng. The group focuses on real-time and media-rich experiences and is located in Bellevue, WA. It used to have offices in Cambridge, Massachusetts, and Cambridge, UK. A similar, earlier initiative was Microsoft Live Labs, a collaboration between Microsoft Research and MSN which ended in 2010.

Selected Projects

• Microsoft Bot Framework & Conversational AI tools for developers.
• Bing Twitter – Find out what topics are hottest on Twitter.
• Docs.com – Discover, create and share Office docs with your Facebook friends
• So.cl ([2]) – Social search service
• Kodu Game Lab – Kodu Game Lab.

https://ainowinstitute.org/

Artificial Intelligence systems are being applied to many arenas of human life – across major sectors such as education, health care, criminal justice, housing, and employment – influencing significant decisions that impact individuals, populations, and national agendas.

But the vast majority of AI systems and related technologies are being put in place with minimal oversight, few accountability mechanisms, and little information about their broader implications. Those developing these systems are generally private companies, whose incentives do not always align with those of the populations on whom they are used, even as these systems are rapidly integrated into core social domains.

To ensure that all AI is sensitive and responsive to the people who bear the highest risk of bias, error, or exploitation, we will need to develop new ways to identify, understand, analyze, and ensure these systems –– and those developing and deploying them –– are accountable.

The AI Now Institute at NYU produces interdisciplinary research and public engagement on the social implications of artificial intelligence. We aim to:

• Measure and understand the effects of AI in society.
• Work with those directly impacted by the use of AI to shape standards and practices that mitigate harm and inform just AI deployment.
• Help shape a rigorous and inclusive field focused on these issues.

Currently, our research focuses on four key domains: rights and liberties, labor and automation, bias and inclusion, and safety and critical infrastructure.

Founded in 2017, AI Now is housed at New York University’s Tandon School of Engineering, where it fosters vibrant intellectual engagement and collaboration across the University and beyond.

François Chollet is a French software engineer and artificial intelligence researcher currently working at Google. Chollet is the creator of the Keras deep-learning library, released in 2015, and a main contributor to the TensorFlow machine learning framework. His research focuses on computer vision, the application of machine learning to formal reasoning, abstraction, and how to achieve greater generality in artificial intelligence.

Chollet graduated with a Master of Engineering from the ENSTA Paris school in 2012 and started working at Google in 2015. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Learning Representations (ICLR). He is the author of Xception: Deep Learning with Depthwise Separable Convolutions, which is among the top ten most cited papers in CVPR proceedings.

Chollet is the author of Deep Learning with Python, the co-author with Joseph J. Allaire of Deep Learning With R, and the creator of the Abstraction and Reasoning Corpus (ARC) Challenge

Publication

On the Measurement of Intelligence by François Chollet, a widely influential paper on prevailing models of computational learning and intelligence.

To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans. Over the past hundred years, there has been an abundance of attempts to define and measure intelligence, across both the fields of psychology and AI. We summarize and critically assess these definitions and evaluation approaches, while making apparent the two historical conceptions of intelligence that have implicitly guided them. We note that in practice, the contemporary AI community still gravitates towards benchmarking intelligence by comparing the skill exhibited by AIs and humans at specific tasks such as board games and video games. We argue that solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience: unlimited priors or unlimited training data allow experimenters to “buy” arbitrary levels of skills for a system, in a way that masks the system’s own generalization power. We then articulate a new formal definition of intelligence based on Algorithmic Information Theory, describing intelligence as skill-acquisition efficiency and highlighting the concepts of scope, generalization difficulty, priors, and experience. Using this definition, we propose a set of guidelines for what a general AI benchmark should look like. Finally, we present a benchmark closely following these guidelines, the Abstraction and Reasoning Corpus (ARC), built upon an explicit set of priors designed to be as close as possible to innate human priors. We argue that ARC can be used to measure a human-like form of general fluid intelligence and that it enables fair general intelligence comparisons between AI systems and humans.

Podcast

François Chollet: Measures of Intelligence | Lex Fridman Podcast #120