In a multi-fold universe, gravity emerges from Entanglement through the multi-fold mechanisms. As a result, gravity-like effects appear in between entangled particles that they be real or virtual. Long range, massless gravity results from entanglement of massless virtual particles. Entanglement of massive virtual particles leads to massive gravity contributions at very smalls scales. Multi-folds mechanisms also result into a spacetime that is discrete, with a random walk fractal structure and non-commutative geometry that is Lorentz invariant and where spacetime nodes and particles can be modeled with microscopic black holes. All these recover General relativity at large scales and semi-classical model remain valid till smaller scale than usually expected. Gravity can therefore be added to the Standard Model. This can contribute to resolving several open issues with the Standard Model without new Physics other than gravity. These considerations hints at a even stronger relationship between gravity and the Standard Model. Recently a controversial series of papers ended up proposing the possibility that the universe be a neural network. It is the result of observing that with an irreversible thermodynamics model of the learning process of the neural network, it might appear possible to model quantum and classical physics, to observe the emergence of a General Relativistic spacetime with gravity, and plausible to construct a generalized holographic principle beyond the AdS/CFT correspondence conjecture. The approach has been received with some skepticism. In this paper, we do not try to assess the validity of the approach and proposal. We simply assume that the proposal amounts to showing that neural network (NN) learning with a suitable thermodynamically related loss function (aka cost function) optimization, that amounts to extremize the free energy of the system, can model the Physics of the universe. When we add a model of entanglement, we discover that the neural network must allow its involved neurons to pair into pairs (or groups) of (dynamic) Qubits. Non quantum NN neurons cannot be simply grouped this way. Instead one need to add new (external) NN, that themselves emulate Qubit behaviors, between the “entangled” nodes. It amounts to match the multi-folds, including their spacetime extensions, and mechanisms. Furthermore the additional NN, explain the possibility to induce 7D physics in 4D space time to induce the Standard Model with gravity (SMG), encountered with multi-fold universes, while the multi-fold dynamics itself (in AdS(5), does not have necessarily have to be governed by General Relativity. [Truncated by viXra Admin to <400 words]