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Keynote Lectures

Software Development... for all?
Juan de Lara, Computer Science, Universidad Autónoma de Madrid, Spain

It's not Just a Game. It's a Game Changer
Johanna Pirker, LMU Munich, Germany

Past, Present, Future, and Far Future of AI
Jürgen Schmidhuber, KAUST AI Initiative, Kingdom of Saudi Arabia; Swiss AI Lab IDSIA, Switzerland and NNAISENSE, Switzerland

 

Software Development... for all?

Juan de Lara
Computer Science, Universidad Autónoma de Madrid
Spain
http://www.ii.uam.es/~jlara
 

Brief Bio
Juan de Lara is full professor at the computer science department of the Universidad Autónoma of Madrid (Spain), where he leads the modelling and software engineering research (miso) team together with Esther Guerra. His main research interests are in automated software engineering, model-driven development, low-code development, domain-specific languages and language engineering, conversational agents, and augmented reality. This research has led to building many practical tools including Asymob, AToM3, metaDepth, merlin, and alter – and the publication of more than 270 papers in international journals and conferences. He has been the PC co-chair of several conferences within his research areas, like MODELS, SLE, ICGT, ICMT and FASE, and has been involved in the organisation of workshops on topics like flexible modelling, multi-level modelling and low-code development.


Abstract
Our world runs on software. It governs all major aspects of our life. It is an enabler for research and innovation, and is critical for business competitivity. Traditional software engineering techniques have achieved high effectiveness, but still may fall short on delivering software at the accelerated pace and with the increasing quality that future scenarios will require.
To attack this issue, some software paradigms raise the automation of software development via higher levels of abstraction through domain-specific languages (e.g., in model-driven engineering) and empowering non-professional developers with the possibility to build their own software (e.g., in low-code development approaches). In a software-demanding world, this is an attractive possibility, and perhaps -- paraphrasing Andy Warhol -- "in the future, everyone will be a developer for 15 minutes". However, to make this possible, methods are required to tweak languages to their context of use (crucial given the diversity of backgrounds and purposes), and the assistance to developers throughout the development process (especially critical for non-professionals).
In this talk I will present enabling techniques for this vision, supporting the creation of families of domain-specific languages, their adaptation to the usage context; and the augmentation of low-code environments with assistants and recommender systems to guide developers (professional or not) in the development process.



 

 

It's not Just a Game. It's a Game Changer

Johanna Pirker
LMU Munich
Germany
 

Brief Bio
Dr. Johanna Pirker (Dr. tech. Dipl.Ing. BSc in Software Engineering and Economics and Computer Science from Graz University of Technology) is professor for media informatics at the Ludwig Maximilian University of Munich and assistant professor, software engineer, and researcher at the Institute of Interactive Systems and Data Science at Graz University of Technology (TUG). She finished her Master’s Thesis during a research visit at Massachusetts Institute of Technology (MIT) working on collaborative virtual world environments. In 2017, she finished her doctoral dissertation in computer science on motivational environments under the supervision of Christian Gütl (TUG) and John Belcher (MIT). She specialized in games and environments that engage users to learn, train, and work together through motivating tasks. She has long-lasting experience in game design and development, as well as virtual world development and has worked in the video game industry at Electronic Arts. Her research interests include AI, data analysis, immersive environments (VR), games research, gamification strategies, HCI, e-learning, CSE, and IR. She has authored and presented numerous publications in her field and lectured at universitiessuch as Harvard, Berlin Humboldt Universität, or the University of Göttingen. Johanna was listed on the Forbes 30 Under 30 list of science professionals, and was awarded the Futurezone Women in Tech Award(2019), the Käthe Leichter Award (2020), and the Hedy-Lamarr Award(2021).


Abstract
The games industry has long been a driver of technological and creative innovation, continually pushing the boundaries of what is possible. Beyond entertainment, the principles, tools, and environments developed for and within this industry have significant potential applications in various fields outside of classical entertainment such as health, education, or industry applications. In this talk, I will present various concepts from games and game-like technologies that extend beyond entertainment, with a particular focus on their relevance to software development. This exploration encompasses not only innovative development techniques but also communication and educational strategies inspired by the game development industry.



 

 

Past, Present, Future, and Far Future of AI

Jürgen Schmidhuber
KAUST AI Initiative, Kingdom of Saudi Arabia; Swiss AI Lab IDSIA, Switzerland and NNAISENSE
Switzerland
 

Brief Bio
The New York Times headlined: "When A.I. Matures, It May Call Jürgen Schmidhuber 'Dad'." Since age 15, his main goal has been to build a self-improving A.I. smarter than himself, then retire. His lab's deep learning artificial neural networks have revolutionised machine learning and A.I. By 2017, they were on over 3 billion smartphones, and used billions of times per day, for Facebook’s automatic translation, Google’s speech recognition, Google Translate, Apple’s Siri & QuickType, Amazon’s Alexa, etc. He pioneered the principles of artificial curiosity & generative adversarial networks (1990, now widely used), neural network distillation (1991, now widely used), self-supervised pre-training for deep learning (1991, the "P" in "ChatGPT" stands for "pre-trained"), unnormalised linear Transformers (1991, the "T" in "ChatGPT" stands for "Transformer"), and meta-learning machines that learn to learn (since 1987). His lab also produced LSTM, the most cited AI of the 20th century, and the LSTM-inspired Highway Net, the first very deep feedforward net with hundreds of layers (ResNet, the most cited AI of the 21st century, is an open-gated Highway Net). Elon Musk tweeted: "Schmidhuber invented everything." He is recipient of numerous awards, Director of the AI Initiative at KAUST in KSA, Scientific Director of the Swiss AI Lab IDSIA, Adj. Prof. of A.I. at Univ. Lugano, and Co-Founder & Chief Scientist of the company NNAISENSE. He is a frequent keynote speaker at major events, and advising various governments on A.I. strategies.


Abstract
I’ll discuss modern Machine Learning, its historic context, and its expected impact on the future of the universe.



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