According to researchers, babies have the ability to unlock the next generation of artificial intelligence (AI). The research paper by neuroscientists at Trinity College, Dublin, was published in the journal Nature Machine Intelligence.
The study examines the psychology and neuroscience of infant learning and distills the principles to direct the next generation of AI. This approach can help overcome the most prevalent limitations of machine learning.
Dr. Zaadnoordijk and Prof. Cusack of Trinity College Institute of Neuroscience, and Dr. Besold of TU Eindhoven, in their article ‘Lessons from infant learning for unsupervised machine learning’, discuss that better ways to learn from unstructured data are required.
They also make solid proposals about the fact that certain insights from infant learning can be efficiently applied in machine learning and how exactly to apply them.
Machines will require in-built preferences for their learning from the beginning. They will also need to learn from richer datasets that capture how the real world looks and feels, the researchers added. Like infants, the machines will require a developmental trajectory where experiences and networks change as they grow up.
According to Dr. Besold, AI researchers often draw metaphorical parallels between ML systems and the mental development of human babies. The researchers are adamant about looking at the knowledge of infant development from the perspective of psychology and neuroscience, as it may help overcome the limitations of machine learning.