The IndesIA consortium has been formed by six Spanish companies to develop AI and machine learning.
Automotive firm Gestamp, ship builder Navantia, engineering firm Técnicas Reunidas and telecoms giant Telefónica have partnered with Microsoft and energy firm Repsol on the development of AI in Spain with a European outlook. The project aims to attract small and medium sized companies as well as early research labs such as the Basque Artificial Intelligence Centre (BAIC).
This follows a similar project by German car makers to establish a common data platform.
The Spanish industrial sector sees the need for more automation and optimization of industrial processes as well as improving sustainability through energy efficiency, developing new materials with lower environmental impact and boosting recycling.
At the heart of the project is the creation of a large-scale interoperable industrial data platform for the development and consumption of artificial intelligence and data analytics solutions. The platform will accelerate data ingestion by working with the leading suppliers of industrial hardware and software to develop connectors that will guarantee real-time data capture of the activities of the various companies involved.
The aim is that this will lead to the creation of open ‘data lakes’ with aggregate and reliable data, ready for a wide array of applications in developing artificial intelligence solutions. The platform will also serve to encourage the design and creation of models of data and universal semantic layers that foster the interoperability of data among industry sector companies.
Data processing will be carried out in strict adherence with EU data protection and sovereignty principles. This includes facilitating mechanisms for data owners to control where data is stored, who has access, and what type of processing can be performed. All these mechanisms will ensure secure processing of data (anonymization, etc.). Security and privacy of industrial and personal data will be the basic principle of design for the technology, platforms, and use cases developed and promoted by the consortium.
This will use cutting-edge industrial AI technologies across the Internet of Things (IoT), 5G, edge computing, the cloud, supercomputing and quantum computing.
The consortium will also work to bridge the training gap in STEM disciplines (science, technology, engineering, and mathematics) to create new high-skill jobs, while also mobilizing the attraction and retention of tech talent in Spain. Data scientists are the highest paid engineering jobs in Europe. It aims to open Opening a Data & Artificial Intelligence School to involve and train industrial sector professionals in data and analytics through training programs that also focus on promoting diversity, gender equality, and dedication to drawing on STEM profiles.
The consortium aims to make the process of developing big data and artificial intelligence solutions more agile. This can be achieved by facilitating access to the technical and economic resources needed for their implementation, as well as cultivating start-ups, technological centres and universities with industrial AI
Over 60 applications of industrial AI have been identified, and the consortium aims to create a library of industrial cases, all documented and with access to the data that enabled their resolution. In addition to being a source of reference material, such a library can stimulate and facilitate the adoption of artificial intelligence technology for companies, including the more than 100 small and mid-sized businesses that have already signed on to the consortium.
The consortium is also working with public and private universities to strengthen employability through upskilling and reskilling for employees in STEM disciplines, with a special focus on artificial intelligence. For this, a variety of training programs will be developed, ranging from general courses (offering the general knowledge that industrial sector employees will require to better understand how these solutions can benefit them in their everyday work) to specialized courses focused on reskilling. Training will also be designed for internal use to develop new profiles, such as data scientists and data engineers.
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