Developing in compliance with GenAI
GPAI rules in practice

This session provides a clear introduction to the GPAI Code of Practice, a guideline  for ensuring compliance with the EU AI Act.
Are you using large language models or AI for image generation? If so, the AI Act requirements for so-called General Purpose AI Models (GPAI) might matter to you. Master the essentials of GPAI compliance under the EU AI Act and learn practical methods to integrate regulatory requirements into your development workflow.

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Description


This session provides engineering teams with an introduction to the AI Act requirements for GPAI Models and their implementation through the GPAI Code of Practice. You will learn to distinguish between the responsibilities of model providers and downstream providers, understand the specific obligations throughout the AI lifecycle, and discover practical tools and methods to seamlessly integrate compliance into your machine learning development workflow. Special emphasis is placed on high-risk AI systems and their regulatory requirements.

Learning Objectives

  • You will analyse the purpose and key principles of the GPAI Code of Practice and evaluate its relevance for ensuring compliance with EU AI Act obligations in your organisation.
  • You will distinguish between the compliance responsibilities of GPAI model providers and downstream providers (modifiers and integrators) and apply appropriate risk mitigation strategies for each role.
  • You will learn about practical methods and tools for data, models, deployment, and system maintenance in GenAI development, with particular focus on high-risk use cases.
     

Target Audience

Technical roles, such as engineering teams, AI developers, machine learning engineers, and other technically-minded professionals working with General Purpose AI models.

Prerequisites

A basic understanding of the EU AI Act is beneficial, but not essential. Some engineering or technical background is beneficial.

Trainer

Ezi Ozoani, GenAI Regulatory Engineer, appliedAI Institute for Europe, and Akhil Ajit Deo, Senior AI Regulatory Expert, appliedAI Institute for Europe.
 

Many thanks to the community partners of the Bavarian AI Innovation Accelerator for their support in communicating and disseminating the project offerings: BIHK - Bayerischer Industrie- und Handelskammertag e.V., vbw – Vereinigung der Bayerischen Wirtschaft e. V., Bayern Innovativ GmbH, UnternehmerTUM GmbH, Munich Innovation Ecosystem GmbH, fortiss GmbH, German Mittelstand e.V., BAIOSPHERE.

 

This training is offered as part of the Bavarian AI Act Accelerator. The project is funded by the Bavarian State Ministry of Digital Affairs. Details: https://innovationsbeschleuniger.bayern/