Expert Day
We invite you to the second iteration of the Expert Day. Join us in an exchange of expertise and find inspiration. These following groups will participate:
- Natural Language Processing & Big Data Technologies
- Smart Maintenance
- Smart Services
- Spatial Data Analytics
Detailed Program:
15:00 – Welcome
15:30 – Keynote by Prof. Pierre Dersin
16:10 – Expert Group Meetings in breakout rooms (see below)
17:40 – Apéro
Data-driven Value Added for Words, Images and Things
Digital transformation is a defining feature of our epoch.
Abundance of data, immense increase in hardware processing capabilities and breakthroughs in analytics algorithms have made practical some of the visions put forward about three quarters of a century ago. The branch of Artificial Intelligence called Machine Learning, and in particular Deep Learning, permeates image processing, natural language processing ( “ words”) and smart maintenance (‘things’), and furthermore enables rich synergies between those three fields, which span a great deal of human activity, with profound potential impacts—some already visible, on industry, science, the arts and social life.
Natural Language Processing & Big Data Technologies
Everyone is talking about ChatGPT these days and some of its output is truly impressive! We will discuss how the most recent wave of text generation algorithms can transform business, science and teaching. The meeting will feature the following expert talks:
Grounded Copywriting with ChatGPT & Co
by Michael Wechner (Wyona AG) + Colin Carter (Coop Rechtsschutz)
Everyone talks about the pros and cons of ChatGPT, its competitors and how to combine the generated text with grounded knowledge. We will demonstrate how ChatGPT & Co can be applied in insurance and discuss the future of retrieval augmented language models.
Can we Identify Machine-Generated Text? An Overview of Current Approaches
by Anastassia Shaitarova (UZH Institute for Computational Linguistics)
The detection of machine-generated text has become increasingly important due to the prevalence of automated content generation and its potential for misuse. In this talk, we will discuss the motivation for automatic detection of generated text. We will present the currently available methods, including feature-based classification as a “first line-of-defense.” We will provide an overview of the detection tools that have been made available so far and discuss their limitations. Finally, we will reflect on some open problems associated with the automatic discrimination of generated texts.
Using AI to Query the Football World Cup Database in Natural Language
by Kurt Stockinger (ZHAW Institute for Applied Information Technology)
Football is one of the most popular sports on earth with millions of people watching the FIFA world cup. In this talk, we describe how we built a system to query the world cup database in natural language. We explain how we translate natural language into the database query language SQL using modern transformer architecture. We also demonstrate how we have used large language models such as Open AI’s GPT-3 and Google’s T5 to explain how the system interprets users’ questions.
We are looking forward to exchanging opinions, experiences and questions, and to exploring this exciting field together!
Smart Maintenance
The value of condition monitoring data: 5 use cases.
In this meeting of the Smart Maintenance Expert Group we will hear about successful student projects conducted together with industry partners from various fields. The focus points of the projects are very diverse, ranging from prediction of energy losses, through anomaly detection, fault diagnostics, prediction of the remaining useful life and optimal maintenance scheduling. We will have 5 short pitch presentations, followed by an interactive discussion of future interest topics of our expert group, including active feedback of all participants.
- Anomaly Detection in Marine Engines with Convolutional Neural Networks (Company: WinGD)
- Aircraft Scheduling Optimization based on Prognostics Degradation Models (Company: Swiss International Airlines)
- Modeling Wake Energy Losses in Wind Farms using Graph Neural Networks (Company: Fluence Energy)
- Using Error Code Patterns to Predict Service Requests on Production Machines with Machine Learning (Company: Zünd Systemtechnik).
- Fault Detection in Solar Power Plants using Physics Informed Deep Learning (Company: Fluence Energy)
Smart services for sustainability – circular servitization
With data-driven services, industrial companies can create quantifiable value for their customers, partners and themselves. At the same time, these services also have the potential for ecological benefits, e.g., through optimized processes in operations or logistics. To make this possible, economic and ecological goals must be captured in a targeted and combined manner when designing the services.
The 1.5-hour workshop will discuss how specific problems from everyday business can be systematically addressed to create relevant added value for business and ecology. Participants will bring their own business issue and leave the workshop with a first approach on how to create economic and environmental value through smart services. The workshop will run through typical phases of a project in a compressed time format to give an impression of what such a project might look like on a larger scale.
Spatial Data Analytics
High-quality spatial data is increasingly available for free use. However, with the large amount of data and the sometimes very specific data types and formats, it is challenging to find the appropriate data sources. In addition, some of the data access platforms are only partially intuitive and can be used without expert knowledge. Accordingly, the question arises whether the full potential of the available data base could not be better exploited if data access and data sharing were simplified. In this co-creation workshop, concepts and approaches will be reflected and discussed with representatives from research and industry as well as from cantonal and federal agencies, with the aim of developing possible approaches for joint implementation.
