Summary
AI has entered the business mainstream, opening opportunities to boost productivity and innovation but suffer limitations hindering wider adoption of model-based or data-driven AI algorithms in industrial settings. Both approaches complement each other and form a critical foundation for the adoption of AI in industry. However, hybrid AI does not fully address the issue of trust (validity, explainability, and ethics). ULTIMATE will pioneer the development of industrial-grade hybrid AI based on three stages to ensure trustworthiness, relying on interdisciplinary data sources and adhering to physical constraints (1st stage), as well as the development of tools for explaining, evaluating and validating hybrid AI algorithms and asserting their adherence to ethical and legal regulations (2nd stage). These will be exemplified using real-world industrial use cases (3rd stage) in the Robotics (collaboration between human and robots for logistics activities) and Space domains (Failure detection for satellites) to promote the widespread adoption of hybrid AI in industry.
The breakthrough generic hybrid AI architectures with improved explainability and interpretability and the predictive model on trustworthiness developed in ULTIMATE will provide industrials with improved shopfloor efficiency (reduction of downtime by 30% and of operational costs) and empower their staff through trustful human/machine cooperation allowing highly skilled jobs and increasing decision power and safety. This will be beneficial to European industry to gain pre-emptive advantage in the market of industrial AI solutions and will eventually increase trustworthiness in the use of hybrid AI components by the wider public.
Extending over 36 months, the ULTIMATE project brings together key industrial stakeholders, with relevant end-users from manufacturing sectors, leading academic and research institutions, and SMEs to collaboratively investigate and lead the development of hybrid AI approaches.
The breakthrough generic hybrid AI architectures with improved explainability and interpretability and the predictive model on trustworthiness developed in ULTIMATE will provide industrials with improved shopfloor efficiency (reduction of downtime by 30% and of operational costs) and empower their staff through trustful human/machine cooperation allowing highly skilled jobs and increasing decision power and safety. This will be beneficial to European industry to gain pre-emptive advantage in the market of industrial AI solutions and will eventually increase trustworthiness in the use of hybrid AI components by the wider public.
Extending over 36 months, the ULTIMATE project brings together key industrial stakeholders, with relevant end-users from manufacturing sectors, leading academic and research institutions, and SMEs to collaboratively investigate and lead the development of hybrid AI approaches.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101070162 |
| Start date: | 01-10-2022 |
| End date: | 30-09-2025 |
| Total budget - Public funding: | 3 529 112,50 Euro - 3 529 112,00 Euro |
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Original description
AI has entered the business mainstream, opening opportunities to boost productivity and innovation but suffer limitations hindering wider adoption of model-based or data-driven AI algorithms in industrial settings. Both approaches complement each other and form a critical foundation for the adoption of AI in industry. However, hybrid AI does not fully address the issue of trust (validity, explainability, and ethics). ULTIMATE will pioneer the development of industrial-grade hybrid AI based on three stages to ensure trustworthiness, relying on interdisciplinary data sources and adhering to physical constraints (1st stage), as well as the development of tools for explaining, evaluating and validating hybrid AI algorithms and asserting their adherence to ethical and legal regulations (2nd stage). These will be exemplified using real-world industrial use cases (3rd stage) in the Robotics (collaboration between human and robots for logistics activities) and Space domains (Failure detection for satellites) to promote the widespread adoption of hybrid AI in industry.The breakthrough generic hybrid AI architectures with improved explainability and interpretability and the predictive model on trustworthiness developed in ULTIMATE will provide industrials with improved shopfloor efficiency (reduction of downtime by 30% and of operational costs) and empower their staff through trustful human/machine cooperation allowing highly skilled jobs and increasing decision power and safety. This will be beneficial to European industry to gain pre-emptive advantage in the market of industrial AI solutions and will eventually increase trustworthiness in the use of hybrid AI components by the wider public.
Extending over 36 months, the ULTIMATE project brings together key industrial stakeholders, with relevant end-users from manufacturing sectors, leading academic and research institutions, and SMEs to collaboratively investigate and lead the development of hybrid AI approaches.
Status
SIGNEDCall topic
HORIZON-CL4-2021-HUMAN-01-01Update Date
09-02-2023
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Organisations
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| THALES SA (Coördinator)
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| CBRNE Ltd
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| FUNDACION TECNALIA RESEARCH & INNOVATION
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| ITTI SP ZOO
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| KUNGLIGA TEKNISKA HOEGSKOLAN
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| LABORATOIRE NATIONAL DE METROLOGIE ET D'ESSAIS
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| ROBOTNIK AUTOMATION SLL
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| SIEC BADAWCZA LUKASIEWICZ - PRZEMYSLOWY INSTYTUT AUTOMATYKI I POMIAROW PIAP (LUKASIEWICZ - INSTYTUT ...
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| THALES ALENIA SPACE FRANCE