ServiceUpdated on 14 July 2025

Solving The Black-Box: ETR 0.5 - XAI, a Fully Traceable and Explainable Machine-learning technology

Mario Garcés

CEO at THE MINDKIND (Algorithmic Artificial GENERAL Intelligence A-AGI) & XAI

Castejón de Sos, Spain

About

The Black Box is one of the most significant open problems in the field of AI. It refers to the opacity of certain machine learning models, especially deep neural networks. In these, decisions and predictions are made through complex internal processes that are difficult to interpret, making it hard to understand how and why a model reaches a specific conclusion. This presents challenges for adoption in critical systems.

Our ETR 0.5 technology offers a solution to the Black Box problem by providing fully traceable and explainable machine learning capabilities. This enables integration into decision-critical systems or systems requiring full explainability, especially in applications such as medicine, finance, industry, or justice.

Type

  • Development
  • Research
  • Other

Similar opportunities

  • Project cooperation

    Partnership Opportunity: AI, Digital Twin, and Cloud Solutions

    • Partner seeks consortium
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    Süleyman Altınışık

    Expert R&D Engineer at OBSS Technology

    İstanbul, Türkiye

  • Expertise

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    • Health
    • Standardisation
    • Big data & analytics
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    • Responsible research and innovation

    Jakub Hejc

    AI/ML Researcher at International Clinical Research Center, St. Anne's University Hospital

    Brno, Czech Republic

  • Project cooperation

    EIC Pathfinder DeepRAP - Trustworthy, Neuro-symbolic, Cognitive, Agentic AI Applications

    Dr Sandhya Patidar

    Associate Professor at Heriot Watt University

    Edinburgh, United Kingdom