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We are excited to announce the XMANAI Hackathon event, organised with the support of Autofair project!

This event brings together a diverse group of students, data scientists, and experts in the field of AI to explore the growing need for explainability in machine learning systems applied to manufacturing. As AI becomes increasingly ubiquitous in our lives, it’s critical that we understand how these systems make decisions and the reasoning behind those decisions. The XMANAI AI explainability Hackathon provides a platform for participants to test the XMANAI tools and collaborate to create innovative solutions that make AI more transparent, interpretable, and explainable . 

During this hackathon, you’ll have the opportunity to work on real-world problems in the frame of our industrial demonstratorsand explore cutting-edge techniques for model development, interpretation, and explainable AI. We believe that the key to building trust in AI is through transparency and explainability. By participating in this hackathon, you’ll be joining a community of data scientists and data engineers who are committed to advancing the field of AI in manufacturing in a responsible and ethical way.

The hackathon will be both a tutorial and a competition between teams to develop explainable IA solutions. All participants will be organized into teams (working groups with 3 elements) and they will put hands-on to practice XAI models and data. We’re excited to see the creative solutions you’ll come up with during this hackathon. Join us now and let’s make a difference together!

This event will run for 2 days and will take place on 13 and 14th of July in Athens, Greece (venue). Check the agenda of the event here.

Topics

AI models and explainability, the importance and relevance of having transparent and explainable AI models
Applicability on real data of Explainable AI models, using existing XAI platforms.

Challenges

Deal with explainable models, and complex problems to work on
Applicability on real data of Explainable AI models, using existing XAI platforms.

Opportunities

Put in practice for a real case problem what a student learnt and learn more on the explainability topic Applicability on real data of Explainable AI models, using existing XAI platforms.

XAI - What is Explainable AI?

Explainable Artificial Intelligence (XAI) is an emerging field that seeks to make the internal logic and output of AI algorithms transparent and interpretable, addressing how black box decisions of AI systems are made, inspecting and attempting to understand the steps and models involved in decision making. Making these processes humanly understandable greatly increases human trust, especially in situations where AI systems are making decisions that could have significant impacts on individuals or society as a whole. As the goal of AI is to support and optimize processes, people must feel empowered and know how the system works.

AI models often work as black boxes, meaning that they make decisions based on complex computations that are difficult for humans to understand. This lack of transparency can lead to concerns about bias, fairness, and accountability. Hence, whether by pre-emptive design or retrospective analysis, XAI is applying methods to add interpretability to the AI output by mapping outputs with inputs. Simpler forms of machine learning such as decision trees and Bayesian classifiers, that have certain amounts of traceability and transparency in their decision making can provide the visibility needed for critical AI systems. Since more complicated algorithms such as neural networks, sacrifice transparency and explainability for power, performance, and accuracy, interpretation methods are often applied after the model training to interpret results.

XMANAI project is focusing its research activities on XAI for manufacturing in order to make the AI models, step-by-step understandable and actionable at multiple layers (data-model-results).

Agenda

Agenda_Hackahon_day1

Registration

FREE ACCESS ()  – Registration is Mandatory

Limited seats are available! 
Register now to secure your spot. We have awards for the best solutions and the most active group in social media.

Don’t miss your chance to participate in the XMANAI Hackathon. Join us with your team and be part of a collaborative environment of passionate individuals, putting together students, developers, and the XMANAI project team working together. We will be waiting for you in Athens (see venue)!

Hackathon Awards Available

Smartphone_Hackthon
Tablet_hackathon

1st Prize

Smartphone* up to 600€

2nd Prize

Tablet* up to 400€

Social media award

Smartwatch* up to 300€

*The pictures are only Illustrative and the brand/model of the devices will be communicated at the time of the event

Hackathon Regulation

Please check here rules for participation in the hackathon as well as the criteria for attribution of awards.

Venue

ATHENA Research and Innovation Center – Artemidos 6, Marousi 151 25, Greece

Supporting projects

This event is organised by XMANAI project, funded by the EU’s Horizon 2020 research and innovation programme  (GA nr. 957362), and supported by AutoFair, funded by the EU’s Horizon Europe research and innovation programme  (GA nr. 101070568)

Hackathon awards

The Hackathon represented a great opportunity for all participants to face real problems and look for solutions. All groups worked hard, even during the night, to prepare the project that they would present to the jury.

The hackathon was an intense event, thanks to the commitment of all participants. Congratulations to everyone, especially the winners!

first award hackathon
1st Award
second award hackathon
2nd Award
3rd Award - Social media