Non-Markovian systems, phenomenology, and the challenges of capturing meaning and context – comment on Parr, Pezzulo, and Friston (2025)

Parr, et al., explore the problem of non-Markovian pro cesses, in which the future state of a system depends not only on its present state but also on its past states. The authors suggest that the success of transformer networks in dealing with sequential data, such as language, stems from their ability to address this non-Markovian nature through the use of attention mechanisms. This commentary builds on their discussion, aiming to link it to some notions in Husserlian phenomenology and explore the implications for understanding meaning, context, and the nature of knowledge.