  This paper is the final part of the scientific discussion organised by the
Journal "Physics of Life Rviews" about the simplicity revolution in
neuroscience and AI. This discussion was initiated by the review paper "The
unreasonable effectiveness of small neural ensembles in high-dimensional
brain". Phys Life Rev 2019, doi 10.1016/j.plrev.2018.09.005, arXiv:1809.07656.
The topics of the discussion varied from the necessity to take into account the
difference between the theoretical random distributions and "extremely
non-random" real distributions and revise the common machine learning theory,
to different forms of the curse of dimensionality and high-dimensional pitfalls
in neuroscience. V. K{\r{u}}rkov{\'a}, A. Tozzi and J.F. Peters, R. Quian
Quiroga, P. Varona, R. Barrio, G. Kreiman, L. Fortuna, C. van Leeuwen, R. Quian
Quiroga, and V. Kreinovich, A.N. Gorban, V.A. Makarov, and I.Y. Tyukin
participated in the discussion. In this paper we analyse the symphony of
opinions and the possible outcomes of the simplicity revolution for machine
learning and neuroscience.
