The StairwAI project aims to create a bridge between users in a low-tech level to the higher-level AI resources. The project will do this by facilitating low-tech users' engagement on the AI on-demand Platform. This will be achieved through a new service layer enriching the functionalities of the on-demand platform and containing:
(1) a multi-lingual interaction layer enabling conversations with the Platform in the user’s own language,
(2) a horizontal matchmaking service for the automatic discovery of AI assets (tools, data sets, AI experts, consultants, papers, courses etc.) meeting the user requirements and,
(3) a vertical matchmaking service that will dimension and provision hardware resources through a proper hardware provider (HPC, Cloud and Edge infrastructures).
Objectives of the StairwAI project
- To provide a framework compliant with the principles of ethical AI
- To ease the access to the AI-on-demand platform through natural
- To satisfy the end user needs through horizontal matchmaking services
- To dimension the physical resources of the AI on demand platform with
end user requirements
- To contribute to strengthen the European SMEs – including low tech
SMEs – and DIH
- To promote the sustainability of the AI on-demand platform
- To reduce fragmentation of AI research and development
AI techniques in use
- Natural language processing (NLP) in different languages for easing
low-tech users’ interaction
- Knowledge representation for organizing the platform AI assets, reputation and fairness mechanisms
- Constraint solving, optimization and machine learning to satisfy users’ business needs
60 SMEs in low-tech sectors will be funded.
28 low tech SMEs will be selected in two different Open Calls: StaiwAI will support the preparation of the feasibility plan for the adoption of AI solutions by the low-tech sector SMEs and delivering a pilot for the adoption of AI.
Call for adopters:
32 low tech SMEs will be selected in one Open Call: StairwAI will support just the feasibility plan for the adoption of previously piloted AI solutions by low-tech sector SMEs.
(This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 101017142)
|Most suitable track
|Envisioning the future