1.  Can we reconstruct images that a person saw, directly from his/her fMRI brain recordings?  2.  Can we reconstruct the training data that a deep-network trained on, directly from the parameters of the network?   The answer to both of these intriguing questions is “Yes!”  In this talk I will show how these can be done. I will then show how exploring the two domains in tandem can potentially lead to significant breakthroughs in both fields. More specifically: (i)  I will show how combining the power of Brains & Machines can potentially be used to bridge the gap between those two domains. (ii) Combining the power of Multiple Brains (scanned on different fMRI scanners with NO shared stimuli) can lead to new breakthroughs and discoveries in Brain-Science. We refer to this as “the Wisdom of a Crowd of Brains”. In particular, we show that a Universal Encoder can be trained on multiple brains with no shared data,  and that information can be functionally mapped between different brains.