Tag: Big Data & Ai Technologies

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:

  • Big Data & AI Technologies
  • Data Sharing & Visualisation
  • Digital Health
  • Natural Language Processing
  • Smart Maintenance

Detailed Program:

Big Data & AI Technologies
More information will follow soon!

Data Sharing & Visualisation
More information will follow soon!

Digital Health
More information will follow soon!

Natural Language Processing
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.
What new opportunities are there? What limitations and pitfalls should we be aware of?
We are looking forward to exchanging opinions, experiences and questions, and to exploring this exciting field together!

Smart Maintenance
More information will follow soon

Expert Group Meeting – Big Data & AI Tech

The Expert Group will come together in September at the following location:
Trivadis AG, room Zuse, Sägereistrasse 29, 8152 Glattbrugg

The topics of discussion are as follows:

Methods of Statistical Disclosure Control applied on Microdata
Simon Würsten, SBB

Simon will talk about how he applied methods of anonymization on microdata, his experiences and possible complications regarding big data.

Big Data and AI Technologies on Microsoft Azure Cloud
Gerald Reif, IPT

Modern cloud providers enable powerful AI and Big Data technologies, platforms and tools. We will have a look at the underlying concepts and specific implementations and services on Microsoft’s Azure Cloud.

Reproducible Data Science
Luca Furrer, Trivadis

Luca will discuss the different aspects of a reproducible data science process and explain why he thinks the question of reproducibility should be considered for every AI project. Furthermore, he will present a set of open source tools which can be useful achieve reproducibility.

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