How are the final MVP features contributing to the X-By-Design Concept? Introduction to the Final MVP As already discussed in a previous
The Power of X-by-design: Pioneering Transparency and Explainability through Design In recent years, artificial intelligence (AI) has rapidly transformed various industries, revolutionizing
The XMANAI Hackathon, held in Athens, Greece on the 13th and 14th of July, provided a unique platform for students, data scientists, and industry experts to explore the critical need for explainability in AI applied to manufacturing.
Data is a driving factor when it comes to the growing impact of AI across all domains. As more and more industries want to benefit from the current development and adopt AI-products in order to accelerate their businesses, intelligent solutions for the processing and transportation of data, also referred to as ETL (Extract Transform Load) become increasingly relevant.
XAI models are essential in enabling businesses to make data-driven decisions more efficiently and effectively.
- Explaining Transformers
- How are the final MVP features contributing to the X-By-Design Concept?
- The Power of X-by-design: Pioneering Transparency and Explainability through Design
- Hackathon Event: Paving the Way to Transparent AI in Manufacturing with XMANAI
- Intelligent ETL Solutions for XMANAI: API- and File Data Harvester
- XMANAI Centralized Models Execution and Visualization Environment
- Industrialization Approaches to Explainability and the XMANAI Cases
- Ethics considerations for manufacturing XAI: the XMANAI Ethical Evaluation Framework
- Partner Spotlight – Ford Motor Company
- XAI Model Guard: The XMANAI AI Models Security Framework
- Explainable AI: a key to trust and acceptance of AI-based decision support systems
- Partner Spotlight – CNH Industrial
- Industrial Asset Graph Modelling in XMANAI
- XMANAI Validation Environment for AI Models
- zExplAIn, Improving Manufacturing Processes with Explainable AI
- XMANAI partner spotlight – Deep Blue
- Technical and Socio-Business assessments of AI Maturity in pilots of Explainable AI
- XMANAI partner spotlight – UNIMETRIK
- AI Algorithms Lifecycle Management and Collaboration
- XMANAI partner spotlight – Knowledgebiz
- XMANAI partner spotlight – UBITECH
- A First Glimpse into the XMANAI platform
- XMANAI partner spotlight – Whirlpool
- Overview requirements
- XMANAI partner spotlight – Athena Research Center
- Industrial Assets Provenance in XMANAI
- XMANAI partner spotlight – Innovalia Association
- The Draft Catalogue of XMANAI XAI Models
- XMANAI´s Evaluation Framework
- XMANAI partner spotlight – Suite5
- XMANAI Reference Architecture: Perspectives
- Security Aspects of Industrial Data Management
- XMANAI partner spotlight – AiDEAS
- What is the XMANAI Minimum Viable Product (MVP)?
- XAI in Manufacturing
- Data Asset Management in XMANAI
- XMANAI partner spotlight – Tyris AI
- XMANAI partner spotlight – Politecnico di Milano
- Education role in AI technology implementation in industry
- XMANAI partner spotlight – Fraunhofer FOKUS
- AI Requirements for Manufacturing in the XMANAI Project
- Have you ever heard about Graphical Neural Networks?
- A brief overview of XAI Landscape
- XMANAI partner spotlight – TXT e-solutions
- Outlook on the XMANAI industrial demonstration cases
- Why we should make use of AI in the manufacturing industry?
- Human Aspects in Decision making and AI
- Moving from “black box” to “glass box” Artificial Intelligence in Manufacturing, with XMANAI