Abstract
Artificial intelligence (AI) tools are transforming scientific research by enabling the analysis of large volumes of data and the generation of new hypotheses and theoretical models. In 2024, there is an expected proliferation of smaller and more efficient AI models that can run on accessible hardware, facilitating the democratization of access to this technology. This will allow academic institutions and small businesses to implement and optimize AI models without the need for expensive infrastructures. The ability of AI to handle and analyze large datasets has been particularly useful in fields such as biomedicine, where it has accelerated the discovery of new treatments and therapies. Furthermore, the integration of AI models into local devices addresses critical concerns regarding data privacy and security, enabling the secure processing of sensitive information. These tools not only enhance the efficiency and accuracy of research but also foster innovation by expanding the frontiers of knowledge in diverse disciplines.