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Mazovia EDIH is one of the 11 European Digital Innovation Hubs (EDIH) in Poland. Its mission is to support micro, small, and medium-sized enterprises (SMEs) in strengthening their competitive position in the market through digital transformation. Collaboration with Mazovia EDIH brings a range of benefits:

  1. Support in adopting digital technologies – Through Mazovia EDIH, businesses can access the latest digital solutions, positively impacting the efficiency of their operations.
  2. Opportunity to test new solutions before investment – Before full implementation, businesses can test and verify planned investments or projects, enabling informed investment decisions and minimizing the risk of loss.
  3. Employee skills development – Mazovia EDIH offers training in digital technologies, thereby increasing the qualifications of employees and the innovation capacity of the enterprise.
  4. Encouragement for continuous improvement – Companies are motivated to continuously improve their business and technological practices, leading to increased competitiveness in the market.

As a Partner, IDEAS NCBR’s task is to support SMEs in the areas of artificial intelligence and digital economics.

Description of services offered within MAZOVIA EDIH:

1.Sustainable development in machine learning: Consultation, assessment, optimization, and implementation support for zero-waste techniques for companies.

IDEAS NCBR offers services related to creating efficient machine learning models based on “zero-waste” techniques and sustainable development. Through our consultations, assessment, and optimization of machine learning models, companies can achieve higher performance and minimize resource consumption. Additionally, we provide training and workshops for companies, universities, and other organizations interested in machine learning based on “zero-waste” techniques.

Business benefits for entrepreneurs primarily include improved performance of machine learning models, cost reduction associated with resource consumption, and minimizing environmental impact through the use of “zero-waste” techniques.

2. Training: Increasing the efficiency of neural networks

The training is aimed at individuals involved in deep learning daily who want to stay up-to-date with the latest trends. In particular, the training is intended for programmers implementing neural networks in environments with limited computational resources, such as microcontrollers or mobile devices. The training covers various topics related to increasing the efficiency of artificial neural networks, especially those addressed within the Zero Waste Machine Learning project.

During the training, participants will learn algorithms for increasing the efficiency of neural networks and gain practical skills.

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