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Stairway to AI: Ease the Engagement of Low-Tech users to the AI-on-Demand platform through AI

Periodic Reporting for period 1 - StairwAI (Stairway to AI: Ease the Engagement of Low-Tech users to the AI-on-Demand platform through AI)

Berichtszeitraum: 2021-01-01 bis 2022-06-30

The StairwAI project aims at supporting companies, and SMEs in particular, in their adoption and uptake of AI technology. For this purpose, three services for the low-tech SMEs are developed for providing (1) natural-language, multi-lingual interaction, (2) AI asset (experts, courses, documents, tools, success stories) discovery, and (3) hardware resource dimensioning.

For this aim, the project will use NLP to facilitate its use for companies describing case studies in different languages and will address the solutions using advanced algorithms on matchmaking, ontologies and knowledge graphs to structure the information adequately, and reputation and fairness to improve the quality of results.

Specifics objectives are:

- to lower the barriers to AI accessibility for SMEs and low-tech SMEs;

- to provide efficient mechanisms for matchmaking;

- to provide mechanisms for the dimension of the hardware resources for AI software assets;

- to integrate these services on the European AI-on-demand platform;

- to validate the tools and services through a subset of participants on the open calls

- to structure the information efficiently in a flexible manner to enlarge it if needed under different contributors
During this period, the requirements and architecture of the StairwAI service have been developed through a series of workshops and surveys to the main stakeholders (SMEs) within WP2.

The design of the architecture has been developed with the contribution of all WP leaders.

A knowledge graph using graph databases has been developed (WP3) together with an ontology of terms in cooperation with the Ontologies WG initiated in AI4EU project and is currently active for supporting the AI on-demand platform.

The NLP service is under testing and provides an architecture to automatic label terms from voice or written inputs from the stakeholders using the services (WP4).

The main algorithms for matchmaking and the core of the service are already developed and tested in the internal environment (WP5) and will be made operational soon.

The vertical matchmaking (WP6) engine is already operational and the benchmarks are implemented using the Bonseyes marketplace and platform.

The open calls - the first round – have already been completed and are working, (WP7).

The positioning of the project in the community through the WP8 has been achieved, synchronizing the effort through a WP led by StairwAI with the other ICT 49. In addition, engagement with the NoEs, and the DIHs is currently a work in progress and fruitful through multiple channels.

Dissemination has been done through several publications and the engagement with different stakeholder groups on a series of events, for example, Digital SMEs, ICT-49 clusters, Network of excellence, etc.
The progress beyond the state of the art is mainly related to original horizontal and vertical matchmaking approaches.

In particular, the state of the art has been advanced on the dimensioning of hardware, as the algorithms have been proven to successfully address the problem.

The expected results are the StairwAI service integrated with the AI on demand to become a key referent in the European AI community. This service can be split into other 5 key subsystems that can be reused independently: NLP, vertical matchmaking, horizontal matchmaking, benchmarking and the knowledge and data model.

Other results are aligned with the applicants to StairwAI as the project contributes to low-tech SMEs growing and evolving on their uptake of AI technology systems.

Finally, the impact expected is mainly devoted to (1) contribute to the sustainability and the enrichment of the AI-on-demand platform and (2) accelerate the adoption of AI for SMEs and low-tech SMEs uptake of AI through the connection with AI assets and AI experts. The use of the service will facilitate personnel upskilling on AI in those companies. Finally, an improved competition with non-EU providers on cloud and edge computing using European hardware resources through vertical matchmaking is envisioned.

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