Artificial intelligence has emerged as a transformative force with the potential to drive significant advances for humanity, from curing diseases to improving fraud detection to increasing operational efficiency. However, access to private data is one of the biggest obstacles to the development of AI-based solutions, either because of regulations that do not allow sharing or because of concerns related to the privacy of the subjects.
In this context, the Spanish company Sherpa.ai, a pioneer in AI development, has developed a federated learning platform that addresses these concerns, putting data privacy at the heart of its solution. The platform allows AI models to be trained using different data sources, but always maintaining data privacy (data is never shared or exposed). This enables the training of AI models with data that was previously not accessible for privacy or regulatory reasons.
‘The main motivation is to promote the use of artificial intelligence, and that through it we can achieve great advances that benefit humanity, such as curing diseases that so far have not been cured,’ the company says.
It is precisely this focus on data privacy and alignment with regulatory requirements that is the key differentiator of Sherpa.ai’s Federated Learning (FL) platform. Thus, they have developed a solution with ‘data privacy as a cornerstone’, which allows the use of data that until now was not accessible for regulatory or privacy reasons without the need to share it, thus guaranteeing privacy.
