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Power Of Machine Learning Innovation – Since Electrons Have Mass. Adapt A CPU model() network So It Takes Advantage Of The Forces In Rotation // Per Lindholm

November 15, 2018 Per Lindholm

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Previous PostMachine Learning – Could a model() simulate many more layers than it can calculate due to technical problems or numerical difficulties? Also would it be possible to simulate a different kind of network with an ordinary fast network? A Simulating Kind Of Neural Network?Next PostMachine Learning – Towards Generalizing ?Simple Way. Use a low unit model and a high unit model. Add The Loss. Dual Same Time Updating.

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By Far The Smartest Idea - Hot Milk With Cooked Rice In A Cup

If free will can be recognized in the machine learning sense then it could probably also be optimized with max as the target. // Per Lindholm

Is a proof some knowledge of the probability of the network.

The Universe Is A Compression Decompression Model() // Per Lindholm 2018

Peace Idea - Any Type Of Probability Can Move Us Forward. Peace Will Do It 100% // Per Lindholm 2018

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  • Machine Learning Guess – Over Problemsolvning – Label simulations that are related to the specific problem. Instead of direct transformation learning. Then ?fit the parameters of the simulation so it becomes more relevant to the problem.
  • Machine Learning Math Guess – Invent any imaginary Problem and solve them and you get a more complete Mathematical Framework. For example. Math Forces are ?objects that move problems out of deep layer models()?
  • Machine Learning Physics – Black Hole Network. When in doubt assume a network. Gives a black hole is a network that stops harmful things coming out. Black holes ?are not new physics but new intelligence due a lot of added problems.
  • Machine Learning Math – Thought Math – Draw a bubble around a number or variable in an equation and imagine what this could mean. Then try to program solve a problem like this in machine learning.
  • Machine Learning Paradigm Thought – If You Cant Split The Problem In Part Truths You Can ?Always Split It Into Many Guesses // Per Lindholm 2019-jan-27 Guess Mathematics
  • Idea – Could a cause of a vulcano eruption be that not wanted material got under into the lava? CO2? So a the eruption has some meaning and is not just a physical effect.
  • Machine Learning Idea – Using GAN asking to solve an equation. Showing x,y,z as the iterate towards the answer // Per
  • Machine Learning Guess – As a possibility you can wait for some of equations in the system. Why solve all at the same time. Could produce more complex paths otherwise. Here I waited for y1-y2 -> 0
  • Machine Learning Innovation Idea – Generalisation by same language model0(). y1 = model1(model0(X1)), y2 = model2(model0(X2)),y3 = model3(model0(X3)),… Where X1 = MNIST sample and X2 = Cifar10 sample And X3 = something else in image format. Image showing most linear recognition //Per
  • Towards a Machine Learning Super Battery – Are different laser printed hole patterns different in their ion properties like capacity and transport? Laser aided CD printed like battery// Per
  • Machine Learning Innovation – Air Condition Device – If There is a need of a compressor. I wonder if you can alter the surface function with a cylinder. Or better yet use a peltier element connected to the front end of the piston. So it cools the hot gas. //Per
  • Blender 3D Innovation Idea – What if you take three render models() and iterate until you have enough intersecting pixel color values. Could this set be the inital value basis of a differential equation that solves the overall image with super high resolution? Venn Diagram Usage
  • Towards A Super Battery – Inspired by ?saltpaper. Could sandpaper or paper with crystals be a no brainer thing of a super battery?

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