See for PRC: The Brain as a Predictor<\/a><\/p>\n\n\n\n See for RL: Why Reinforcement Learning is Special<\/a><\/p>\n\n\n\n Mutually reinforcing<\/strong><\/p>\n\n\n\n PRC shows valid directions and tentatively also realizes them. RL consolidates\/reinforces the best directions and attenuates the lesser ones.<\/p>\n\n\n\n Without RL, PRC may go forward pretty slowly, like a person who can learn only in small steps from what he already knows \u2014 crawling, never jumping.<\/p>\n\n\n\n Without PRC, RL may go forward pretty stochastically, like a person in a dark room searching for the light switch without any guidance. PRC then provides a glow through which the person may guess probable directions at least. He may find the switch after a limited search. Next time and in a different room, he can make use of the glow even better. To an inexperienced observer, he may seem to find the switch miraculously easily.<\/p>\n\n\n\n RL within PRC<\/strong><\/p>\n\n\n\n This may take away some confusion from the reader who is already thinking beyond the above at this point.<\/p>\n\n\n\n Indeed, the recognized and completed pattern may incorporate the reward itself. It\u2019s a semantic choice. However, this shows how things can overlap, and through their overlap may lead to new possibilities.<\/p>\n\n\n\n The lesson from humans<\/strong><\/p>\n\n\n\n The combination enables humans to learn from few examples, as even children do spontaneously. It\u2019s a significant part of the way the brain works.<\/p>\n\n\n\n It can be used for the same in A.I. Through PRC and rewards, the system can learn where to evolve toward in a way similar to humans. This makes the need for many rewards and smooth rewarding less stringent, as this is a substantial bottleneck in present-day A.I.<\/p>\n\n\n\n In humans, PRC is realized in a specifically human way that is intrinsically related to the human medium. Probably most crucial in this are our countless mental-neuronal patterns<\/a>. These enable a flexible and performant kind of PRC, albeit a very fuzzy one.<\/p>\n\n\n\n Probably so fuzzy that we should never indulge this in a non-Compassionate vein of super-A.I. Yet I fear that we are precisely closing into that, unfortunately.<\/p>\n\n\n\n At the same time, a boon for Compassion<\/strong><\/p>\n\n\n\n Broadly overlapping patterns are pointers to Compassion, basically<\/a>. They enable intra-brain intuition and our natural kind of conceptual intelligence. They also enable our natural urge for social thinking. Within us, this goes together to a large degree, making us ‘social animals’ to whom ethics frequently means a big deal. Our intelligence has essentially been developed socially over a very long time.<\/p>\n\n\n\n The same provides hope for a Journey Towards Compassionate A.I.<\/a> if that gets based on likewise principles even when from an utterly different background. An example of this is being realized in Lisa<\/a>.<\/p>\n\n\n\n We may be very optimistic if we don\u2019t blow it.<\/p>\n