Claire:  Whatever thing you need to regulate, whether it’s how much energy you have or how much energy you need or it’s how much temperature you have or how much temperature you need, there is going to be a threshold around which you regulate something and you can actually continuously have a learning system that responds to that or a changing threshold, then you have to have a learning system that changes. You don’t always have the temperature of a house at the same temperature all the time. It changes with your needs and requirements and that’s the idea, is how do you adapt to being in tune and responsive to that change and then as the change repeats, how do you integrate that.

What if one of your distributed feedback loops are running your smart grid were intelligent like that too. So they start to learn. “Oh that solar panel in that area of the suburbs seems to catch a lot of sunlight and these ones not so much, but when its windy those wind turbines tend to do that, so it seems to be repeating on this cycle, and these people need the most energy at this time of the week and these people need less, imagine how easy it is to manage and distribute the grid when you have artificial intelligence, and the reason why most governments don’t do distributed systems because it is so difficult to manage and all of their systems are set around centralised management. A fascinating realisation that the exponential technologies of AI and digitalisation are actually enabling us to have this massive evolution of what we actually need.

Student: We really so heavily on communications that actually it means that we are really dampening down on other abilities to communicate, so we think we are so great at communication…

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