I can name 3 for ya.
1. Roger Penrose. Oxford, right?
2. Christianne Mornais Smith
Christiane de Morais Smith Lehner is a Brazilian theoretical physicist and professor at the Institute for Theoretical Physics at the University of Utrecht, where she leads a research group studying condensed matter physics, cold atoms and strongly-correlated systems.
3. Henry Stapp of course.
For Carroll and the Multiverse? I am ok with materialism or dualism as long as it works well?
The only appeal of the Multiverse is more fun for everyone. Good science fiction tales, perhaps a place to have an afterlife?
Of course if you really want to define consciousness, you were claiming pantheism as ChatGpt4 being conscious, correct? Like in April, remember? For me, I was demanding that such a mind be based on the mammalian brain. So, I could be way wrong. Now, here was a physics team (with 1 comsci guy, Lanier) promoting consciousness as primo to the universe.
"We present an approach to cosmology in which the Universe learns its own physical laws. It does so by exploring a landscape of possible laws, which we express as a certain class of matrix models. We discover maps that put each of these matrix models in correspondence with both a gauge/gravity theory and a mathematical model of a learning machine, such as a deep recurrent, cyclic neural network. This establishes a correspondence between each solution of the physical theory and a run of a neural network. This correspondence is not an equivalence, partly because gauge theories emerge from N→∞ limits of the matrix models, whereas the same limits of the neural networks used here are not well-defined. We discuss in detail what it means to say that learning takes place in autodidactic systems, where there is no supervision. We propose that if the neural network model can be said to learn without supervision, the same can be said for the corresponding physical theory. We consider other protocols for autodidactic physical systems, such as optimization of graph variety, subset-replication using self-attention and look-ahead, geometrogenesis guided by reinforcement learning, structural learning using renormalization group techniques, and extensions. These protocols together provide a number of directions in which to explore the origin of physical laws based on putting machine learning architectures in correspondence with physical theories."
If quantum woo is wrong, I don't wanna be right!