Innovative success stories in which the use of AI-based technologies play a central role
The Call for Projects is aimed at organisations that have developed or adopted innovative artificial intelligence-based solutions and can demonstrate their impact.
A committee of experts made up of representatives of CIDAI members will review all the applications received and select those that best fit the themes of the congress, prioritising innovation, novelty and the degree of impact on companies and society.
If you have any questions about this call, you can send an email to events@eurecat.org
This year's program will cover the following subjects.
Which do you think your project fits best?
AGENTIC AI: TOWARDS AUTONOMOUS AND COLLABORATIVE AI?
This session will explore how these agents can transform various sectors and functions. It is essential to understand how this new generation of AI will impact business and society in general.
IS ARTIFICIAL INTELLIGENCE CREATIVE, OR DOES IT ONLY SEEM LIKE IT?
In this session, we will discover projects where AI participates in different creative processes, and we will reflect on the impact of this new algorithmic creativity on business, society and beyond.
WHEN AI TAKES SHAPE IN THE FORM OF INTELLIGENT AND COGNITIVE ROBOTS
WHEN AI BRINGS VALUE: INSPIRING CASES
We will learn about innovative projects that improve processes, boost businesses and provide new creative perspectives. It is a session for inspiration by real solutions that show the transformative potential of AI.
ALGORITHMS AND MOLECULES: HOW AI IS REVOLUTIONISING BIOTECHNOLOGY
This session shows how the combination of algorithms and data is accelerating research and opening up new scientific and industrial possibilities in the life sciences.
THE REAL POTENTIAL OF SYNTHETIC DATA IN AI TODAY
In this session, we will see how it is used in various fields (health, autonomous mobility, finance, generation of surrogate models for simulations and others). We will explore how it is generated, what it contributes and what impact it has on the quality of the models to achieve a more robust, secure and scalable AI.