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Tag: Databooster

Webinar – Generative KI für SPARQL und SQL – Stand der Forschung und Einsatz in der Lehre am Beispiel von QLever

Die generative KI (GenAI) zur Umsetzung natürlich-sprachlicher Fragen in SPARQL- und SQL-Abfragen zeigt bereits erstaunliche Ergebnisse. In der Lehre bietet sie den Studierenden einen niederschwelligen Zugang zu diesen deklarativen Datenbankabfragesprachen. Am Beispiel von QLever und anderen Werkzeugen werden der Stand der Forschung und der Einsatz in der Lehre vorgestellt. Auch Anwendungen wie die Konvertierung und Abfrage von Daten aus OpenStreetMap (OSM) werden behandelt. Dabei werden auch Probleme aufgezeigt. Beispielsweise hat GenAI die Schwäche, dass falsche Entity Identifier generiert werden, was zu unbrauchbaren Abfragen führt. Ein anderes Problem ist das Matching von Entitäten zwischen OSM und anderen Datenquellen. Seien Sie bei diesem Databooster Webinar dabei, wir erwarten eine interessante Diskussion mit einer namhaften Referentin.

Dieses Webinar wird auf Deutsch gehalten.

Prof. Dr. Hannah Bast (Albert-Ludwigs-Universität Freiburg) ist im Bereich der angewandten Algorithmik aktiv und ihre Forschungsinteressen umfassen unter anderem Algorithmen für die Routenplanung, Aspekte des Information Retrieval (Indexerstellung, Abfrageverarbeitung, Benutzerschnittstellen, ganze Informationssysteme) und die Verarbeitung natürlicher Sprache, mit und ohne Deep Learning

Programm

  • 16:00 Begrüssung und Vorstellung der Hauptreferentin
  • 16:10 Inputvortrag (Prof. Dr. Hannah Bast)
  • 16:55 Ergänzende Inputs (Prof. Stefan Keller)
  • 17:05 offene Diskussion und Ausblick
  • 17:30 Schluss des offiziellen Programms

Project Day

The Innovation Booster Databooster is organizing the Project Day, where previously supported innovation teams will present their projects and their developments in previous years to companies and interested partners.

Keep the date open! Additional information will soon follow.

Expert Day

Selected expert groups from the data innovation alliance will present themselves at this half-day event. Current projects, trends and potential collaborations will be presented, discussed and worked on in interactive sessions. 

14:00Welcome
14:15Keynote
14:45Expert Group Break-out (1)
15:30Coffee Break
16:00Expert Group Break-out (2)
17:00Apéro
17:45Closing

Smart Maintenance – Predictive Maintenance @ ABB: A Technology Company’s Point of View

Kai Hencken is Corporate Research Fellow for “Physical and Statistical Modeling” at the ABB Corporate Research Center, Baden-Dättwil, Switzerland. He holds a Ph.D. and a habilitation in theoretical physics from the university of Basel, where he is currently a lecturer. He joined the ABB Corporate Research Center in Baden-Dättwil in 2005 as a member of the theoretical physics group. His research interests are the combination of physical modeling, data analytics, and statistical methods to solve problems related to industrial devices. He works predominantly on developing diagnostics and prognostics approaches for different products, covering the range from sensors and signal processing to mathematical methods in prognostics.

Predictive Maintenance is one of the main application areas of the Industrial Internet of Things. The wide deployment of sensors and their connectivity allows to collect big amounts of data from devices in the field. The exponential increase of computing power and the recent developments in data analytics and machine learning makes the application of advanced algorithms possible. We are also facing changes in the way maintenance work is done and how its importance is seen.

ABB is a technology company providing devices and solutions in the area of electrification and automation. Many of their offerings in the area of digitalization and specifically predictive maintenance are geared towards their own products. This leads to topics that are specific for these cases in addition to the common ones. 

In my talk I will discuss some of these issues and how they can be addressed: The domain knowledge and the simulation capabilities within the company are one of the big assets of any manufacturer. Reusing this for predictive maintenance solutions is an important aspect. For highly reliable products failure data will remain scarce even for a large installed base. This is a major bottleneck for any data-driven approach and needs to be overcome. The focus of many solutions developed is to provide monitoring and diagnostics capabilities. The prognostics aspect and the proposal of actions to be taken to remedy potential problems are often more important for the final customer. Examples are taken predominantly from electrification and motion devices.

AI in Finance and Insurance – The Future of Financial Data Analytics
  • 14:45 – 14:55 – Intro and introductions
  • 14:55 – 15:30 – Presentation: Nicole Königstein, Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG: “Financial Times Series Prediction in the Age of Transformers”+ Open discussion and Q&A
  • 15:30 – 16:00 – Break
  • 16:00 – 16:30 – Presentation: Guillaume Raille, Engagement Director & Data Scientist at Unit8 SA: “LLMs beyond Chatbots: Unveiling the challenges of advanced LLM applications based on a real-world use cases”+ Open discussion and Q&A
  • 16:30 – 17:00 – Discussion on topics that might be relevant for the DIA in the future and how to organize
Big Data & AI Technologies

Coming soon!

Open Innovation & Innovation Booster Webinar

Implementation of open innovation within the framework of the Innovation Booster’s (IB) “Artificial Intelligence” and “Databooster” powered by Innosuisse. Get to know new opportunities followed by a Q&A session.

The challenges of our time need innovative concepts, approaches and solutions. The IBs supports this process – from the identification of challenges and the development of ideas to the initialization of innovation projects. In this webinar, you will learn about the funding opportunities within the framework of the IBs, the application process and further opportunities and services provided by the IBs and the data innovation alliance.

9th R&D Conference Industry 4.0

The “R&D Conference on Industry 4.0” was created in the knowledge that networking and cooperation with universities is an important success factor for companies’ innovation activities. Industrie 2025 is pleased to invite you for the 9th time to get an overview of the diverse activities of universities and universities of applied sciences on Industry 4.0 topics in a compact format. You will be presented with 22 university projects every 5 minutes from the fields of Artificial Intelligence, Smart Factory, Digital Twin and many more. You will get an efficient overview of the topics of the near future and find out what is being researched and developed at universities and universities of applied sciences in the field of Industry 4.0. The data innovation alliance will of course also be there to present the Innosuisse innovation booster Artificial Intelligence and Databooster.

Registration and schedule can be found on the official website!

Service Lunch: „Eating, Learning, Networking“

This talk gives an overview of how MYBLUEPLANET uses the ClimateActionsApp as a tool to ignite and track individual actions for a more sustainable way of living. MYBLUEPLANET is a Swiss NGO with the mission to take individual and collective action against climate change.


Key Speaker

Noah Gunzinger
Managing Director
MYBLUEPLANET

Online by Microsoft Teams, Participants get an access link after registration.
Registration is open until Monday, January 9th, 2024

MYBLUEPLANET: An association for climate protection in Switzerland

Future Lab KI: Studierende und Unternehmen schmieden die Zukunft

🚀 Einladung zum “Future Lab AI” – Gemeinsam KI-Geschichte schreiben! 🤖

Hallo liebe Partner und KI-Begeisterte,

Bereiten Sie sich darauf vor, KI-Geschichte zu schreiben! 🚀 Beim “Future Lab AI” arbeiten Studierende, Unternehmen und Wissenschaftshelden zusammen, um innovative Anwendungen und Visionen im Bereich Künstliche Intelligenz zu entdecken und die digitale Zukunft von Unternehmen zu gestalten.

Wann? 📅 Am 29. November 2023, von 12:00 Uhr bis 15:00 Uhr

Wo? 📍 HSLU Hochschule Luzern, Technikumstrasse 21, 6048 Horw

Registrierungslink: Hier anmelden

Unsere Mission:

🌟Wir haben die klare Mission, den Weg für eine aufregende KI-Zukunft zu ebnen. Hier ist ein kleiner Vorgeschmack auf das, was Sie erwartet:

👋 Willkommen: Ein herzlicher Empfang und Gelegenheit zum Kennenlernen.

🗝️ Keynote 1: “Der Einsatz generativer KI in KMU” – Lernen Sie, welche Einsatzfelder es für künstliche Intelligenz im Unternehmen gibt.

🔍 Keynote 2: “Probleme in KMUs bewerten” – Wir beleuchten, wie man Herausforderungen im Unternehmen hinsichtlich einer die KI-gesteuerten Lösungen untersucht.

💡 Arbeit an Fallbeispielen: Praktische Anwendungen von KI in Unternehmen, damit Sie die Power der KI hautnah erleben können.

💬 Diskussion und Abschluss: Gemeinsam reflektieren wir, was wir heute gelernt haben, und schmieden Pläne für eine aufregende Zukunft.

🤝 Möglichkeit zur Vernetzung: Knüpfen Sie wertvolle Kontakte und erkunden Sie Kooperationsmöglichkeiten.

Registrierung: 🎟️ Die Teilnahme ist kostenlos, aber die Plätze sind begrenzt.

Wir können es kaum erwarten, gemeinsam mit Ihnen an der Zukunft der Künstlichen Intelligenz zu arbeiten und dabei Studierende und Experten zu verknüpfen. Wenn Sie Fragen haben oder weitere Informationen benötigen, stehen wir Ihnen gerne zur Verfügung.

Lassen Sie uns zusammen KI-Geschichte schreiben und die digitale Zukunft von Unternehmen gestalten!

Expert Group Meeting – Smart Maintenance

We would like to invite you to the next Smart Maintenance Expert Group meeting. In this meeting we will host Dr. Gabriel Michau from Stadler Services, who will tell us about

Full Steam Ahead: Unveiling the Future of Railway Rolling Stock Maintenance.

The maintenance regime of rolling stock creates by nature a competition between the reliability of the asset and the availability. Traditional maintenance regimes, mixing preventive and corrective maintenance strategies, look for a cost effective optimum between these metrics and years of optimisations have left little room for further improvements using the traditional optimisation strategies.

To achieve even more efficient maintenance strategies, dynamically scheduled maintenance, based on the real condition of the assets and of its components needs to be introduced, the so-called “Condition Based Maintenance” but this requires the development of three new types of capabilities: collecting and managing the right data, processing this data to assess the health of the monitored components and the ability to change and adapt the maintenance schemes seamlessly. Each aspect brings its own challenges, and many of these challenges are similar to the ones faced by the industry in general. In this presentation, we will draw upon exemplary projects carried out within Stadler Service’s fleet management to delve into the specific challenges encountered and the strategies employed to address them.

Dr. Gabriel Michau leads the New Maintenance Technologies team at Stadler Service AG, where he focuses on pioneering innovative maintenance strategies driven by data insights and cutting-edge technologies within the workshop. Prior to this role, he served as a Senior Scientist at ETH Zurich and at the ZHAW, specializing in the application of Deep Learning to Time Series for unsupervised fault detection and diagnostics in complex industrial systems, with a particular focus on very high frequency data (up to 100s of MHz). There, he led research initiatives aimed at advancing intelligent maintenance practices in collaboration with esteemed industrial partners, including SBB-CFF, Airbus, Stadler AG, GE, Oerlikon-Metco, Bystronic and more.

In 2016, he earned a dual PhD in Physics (Signal Processing over Networks) and Transport Engineering through a joint program between the Queensland University of Technology in Brisbane and ENS de Lyon in France. His research focused on inferring traffic flows in cities using Bluetooth and traffic counts data, and he developed an innovative traffic representation tool with graph theory and advanced convex optimization algorithms. His work earned him the first place in both the National and International Abertis Award in 2016.

The talk will be followed by an active discussion about successes and challenges in implementing and scaling condition-based maintenance in real operational systems.

Expert Group Meeting – Natural Language Processing in Action

Our next Expert Meeting on Thursday, 30 November 2023, 17:00-18:30, will focus on various aspects and applications of NLP & Health

It will take place at the ZHAW premises in Lagerstrasse 45, 8004 Zurich in room ZL O6.12 (6th floor). The meeting will be followed by an apéro.

Online participation is also possible.

Please use the following form to confirm your attendance by October 30https://forms.gle/eEYLWjpGNKLauGmF8
We will then send you a calendar invitation which includes online participation details.

In the form, you also have the opportunity to let us know which topics you are interested in for our meetings in 2024 and to suggest speakers!

The following presentations are confirmed for the meeting on 30 November:

  • Elif Ozkirimli, Head of Computational Science Products at Roche
    Title: Adoption of NLP in Healthcare: a Strategic Perspective Across the Pharma Value Chain.
  • Matteo Manica, Senior Research Scientist at IBM
    Title: Harnessing the Power of Language Models to Accelerate Material Design
  • Ahmad Aghaebrahimian, Associate Researcher at ZHAWTitle: Medical Informatics Powered by Large Language Models and the Semantic Web; A work in progress
  • Nicolas Löffler-Perez, Data Scientist at SwissmedicTitle: Medicrawl: a ML-based Application for Finding Illegal Products in Online Markets.

AI’ll be back – Consequences of AI Regulation for Start-Ups

The use of artificial intelligence in the EU will be regulated by the AI Act, the world’s first comprehen-sive AI law. Its purpose is to legally define artificial intelligence and impose documentation, auditing, and process requirements for AI providers. What does that mean for AI startups in Switzerland? Three speakers will discuss consequences, opportunities and risks of the AI Act. Livia Walpen, Senior Policy Advisor International Relations at BAKOM, outlines the current state of the EU AI act and its possible consequences for Switzerland. Christoph Heitz, Founder and President of the Data Innovation Alliance, discusses how developers of AI applications in companies need to prepare already today, how the AI Act changes the job of developers, and how startups can obtain support for these new challenges. Christoph Bräunlich, Head AI of BSI Software, presents a use case to demonstrate how a “Code of AI conduct” can help to be prepared for compliance for AI regulations. Speakers and audience will deepen questions in a discussion moderated by Markus Christen, managing director of the Digital Society Initiative of the University of Zurich.

Program

16:30 – 16:45     Arrival of speakers
17:00 – 17:05     Markus Christen: Welcome and outline of event
17:05 – 17:25     Livia Walpen: EU AI Act: State of play
17:25 – 17:45     Christoph Heitz: Is it possible to be prepared for the coming AI regulation as a company?
17:45 – 18:05     Christoph Bräunlich: Digital Responsibility as AI provider: Can a “Code of AI conduct” help?
18:05 – 18:30     All: discussion among speakers and with the audience (Moderator: Markus Christen); focus on consequences of AI regulation for startups (opportunities & ethics)
18:30 – 19:00     Apèro