Binz et al. highlight the potential of meta-learning to greatly enhance the flexibility of AI algorithms, as well as to approximate human behavior more accurately than traditional learning methods. We wish to emphasize a basic problem that lies underneath these two objectives, and in turn suggest another perspective of the required notion of “meta” in meta-learning: knowing what to learn.

The article seeks to elucidate the status of transcendence in the historiography of secularization through the perspective of collective memory. It discusses two typological models dealing with the basic metaphysical problem concerned with the presence and meaning of transcendence in real human existence. According to the first, the historical reality of secularization causes a break from the collective memory whose roots are in religion. In contrast, the second model considers that despite the deep transformations in the status of religion in (...) a reality of secularization, an experience of historical continuity may also occur there. These models denote the two poles in the argument about the meaning and value of history for modern people. The article suggests a phenomenological analysis of the two models and criticizes their deficiencies. Finally, the “tension model” is outlined as a third alternative that aims at overcoming the binary situation created by the first two in favor of a perspective that necessitates and contains both immanence and transcendence. (shrink)