Event Month: January

  • AI House Davos: From lab to market

    AI House Davos: From lab to market

     

    The roundtable will center on the transition of AI from scientific discovery to economic implementation. We'll dissect the mechanisms that enable scientific AI innovations to be adapted for economic use, including intellectual property, licensing, and market strategy. The conversation will highlight collaborative models between research institutions and industry partners that facilitate the transfer of AI technologies into commercial ventures.

     

    When?

    Thursday January 18, 2024, 10:00-10:55 CET

     

    Where?

    Partner Room 2, AI House Davos, Promenade 68, 7270 Davos Platz

     

    Format

    • Round table
    • Open to the press

     

    Speakers

    • Evan Sparks, Vice President of AI and High Performance Computing at HP

    • Max-Frederik Gerken, CEO of Optocycle

    • Alexander Diehl, Investor & Entrepreneur, Cyber Valley

     

    Moderator

    • Julian Enz, Chief Innovation Office, Cyber Valley


    Further information

    Register

  • AI House Davos: AI & Sustainability

    AI House Davos: AI & Sustainability

     

    This roundtable will explore how AI technologies are being applied to tackle critical sustainability challenges. Discussions will examine real-world AI innovations in areas such as renewable energy, resource conservation, and climate change mitigation. Emphasizing actionable solutions, we'll consider the role of AI in driving environmental progress, enhancing global sustainability efforts, and the partnerships propelling this mission forward.

     

    When?

    Wednesday, January 17 2024, 11:30-12:00 CET

     

    Where?

    Partner Room 2, AI House Davos, Promenade 68, 7270 Davos Platz

     

    Format

    • Roundtable
    • Open to the press
    • Interactive panel discussion
    • Audience Q&A

     

    Speakers

    • Christoph Kellenberger, Sustainable Architect
    • Max Gercken, CEO Optocycle
    • Dieter Gerdemann, MD & Partner Sustainability, A.T. Kearney
    • Samuel Widmann, Entrepreneur and ex-Google Maps CEO
       

    Moderators

    • Julian Enz, Director Innovation & Economy (CIO), Cyber Valley
    • Rebecca Beiter, Director Communications & Society (CCO), Cyber Valley


    Further information

    Register

     

  • AI House Davos: Frontiers of AI & ML

    AI House Davos: Frontiers of AI & ML

     

    Exploring cutting-edge developments in machine learning and AI, this discussion delves into recent research breakthroughs including related fields like computational neuroscience. Focused on advanced algorithms, neural network innovations, and deep learning techniques, we'll address challenges and future directions in AI, with insights from leading European AI researchers. Emphasis will be on scientific depth, practical applications, and ethical considerations. 

     

    When?

    Wednesday, January 17, 2024, 16:15-16:45

     

    Where?

    Partner Room 3, AI House Davos, Promenade 68, 7270 Davos Platz

     

    Format

    • Round table
    • Open to the press

     

    Speakers

    • Bernhard Schölkopf, Director of the ELLIS-Institute, Director Max Planck Institute for Intelligent Systems & Cyber Valley Speaker
    • Tobias Bonhoeffer, Director of the Max Planck Institute for Biological Intelligence
    • Auguste von Bayern, Group Leader Max Planck Institute for Biological Intelligence
    • Evan Sparks, Vice President of AI and High Performance Computing at HPI

     

    Moderator

    • Alexander Diehl, Investor & Entrepreneur, Cyber Valley 


    Further information

    Register

  • Hype oder Hoffnung?

    Hype oder Hoffnung?

     

    Maschinelles Lernen ist nicht das Wundermittel, mit dem wir unseren Planeten retten können. Keine einzelne Lösung wird den Klimawandel "reparieren". Aber viele Anwendungen, die auf maschinellem Lernen basieren, haben großes Potenzial. Manchmal wird Künstliche Intelligenz bereits eingesetzt. Oft sind die Anwendungen noch Ideen. Wie kann man über die faszinierenden Lösungen berichten ohne falsche Erwartungen zu wecken?
     

    Wann?

    25. Januar, 2024, 12:00-13:00 Uhr

     

    Wie?

    Zur Anmeldung via zoom: Registrierung zum Event

     

    Was?

    Tobias Asmuth, “Journalist-in-Residence" im Cyber Valley, spricht mit Prof. Dr. Lynn Kaack (Assistenzprofessorin für Informatik und öffentliche Ordnung an der Hertie School) und Wieland Brendel, der am Max-Planck-Institut für Intelligente Systeme die unabhängige Forschungsgruppe „Robust Machine Learning“ leitet.

    Um an dieser Veranstaltung teilzunehmen, registrieren Sie sich bitte hier und wir senden Ihnen einen Link zur Online-Veranstaltung.
    Die Veranstaltung wird aufgezeichnet. Die Veranstaltung findet auf Deutsch statt. 


    Über Cyber Valley Journalist-in-Residence 

    In einem drei- bis sechsmonatigen Aufenthalt erforschen ein oder zwei Journalisten, wie KI-Anwendungen für guten Journalismus genutzt werden können und wie Journalist*innen sicherstellen können, dass ihre Berichterstattung über die Technologien hinter dem Schlagwort "künstliche Intelligenz" angemessen und evidenzbasiert ist. Die Journalist*innen werden von einer unabhängigen Jury ausgewählt. In dieser Zeit kann der oder die Journalist-in-Residence zu einer selbst gewählten Fragestellung im Austausch mit KI-Forschenden unterschiedlicher Disziplinen recherchieren – absolut unabhängig. Cyber Valley erwartet in dieser Zeit ausdrücklich keine Berichterstattung über KI-Themen oder über Cyber Valley. Das Programm findet zweimal jährlich in einer Kooperation zwischen Cyber Valley und dem Zentrum für Rhetorische Wissenschaftskommunikation – Forschung zur Künstlichen Intelligenz (RHET AI Center) statt. Es wird von der Volkswagen Stiftung gefördert.

  • Research Talk: Semantic Probabilistic Layers for Neuro-Symbolic Learning

    Extending current deep learning architectures to correctly conform to prior knowledge and capture symbolic constraints while guaranteeing their satisfaction is a big open problem. Doing so would benefit many structured-output prediction (SOP) tasks in machine learning such as predicting rankings, hierarchies and other structured objects. In this talk, I will discuss how we can design a predictive layer for SOP that guarantees its predictions to be consistent with a set of predefined symbolic constraints. This Semantic Probabilistic Layer (SPL) can act as a drop-in replacement of existing predictive layers while still being amenable to end-to-end learning via exact maximum likelihood. SPLs combine exact probabilistic inference with logical reasoning in a clean and modular way via probabilistic circuits. We empirically demonstrate that SPLs outperform other neuro-symbolic approaches in terms of accuracy on challenging SOP tasks including hierarchical multi-label classification, pathfinding and preference learning, while retaining perfect constraint satisfaction.

     

    Antonio Vergari is a Lecturer (Assistant Professor) in Machine Learning at the University of Edinburgh. His research focuses on efficient and reliable machine learning in the wild; tractable probabilistic modeling and combining learning with complex reasoning. He recently was awarded an ERC Starting Grant on automating probabilistic reasoning for trustworthy ML. Previously he was postdoc in the StarAI Lab lead by Guy Van den Broeck at UCLA. Before that he did a postdoc at the Max Planck Institute for Intelligent Systems in Tuebingen in the Empirical Inference Department of Bernhard Schoelkopf. He obtained a PhD in Computer Science and Mathematics at the University of Bari, Italy. He likes to tease and challenge the probabilistic ML community at large on how we desperately need reliable ML an AI models nowadays. To this extent, he organized a series of tutorials, workshops, seminars and events at top ML and AI venues such as UAI, ICML, AAAI, IJCAI and NeurIPS and last year a Dagstuhl Seminar.