Timothy Busbice
2 min readJan 25, 2017

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This article is shedding light in the right direction. In simple terms, mathematics is the language we use to describe what we theorize and observe. Deep Learning suffers from the point of view in that it uses mathematics to create its paradigm which limits its capabilities. Anyone that thinks Deep Learning is the answer to advanced robotics, and certainly AGI, is going to be really disappointed. Not that DL is bad in any way, just limited.

With my work in Biologic Intelligence (https://humanizing.tech/biologic-intelligence-is-not-artificial-intelligence-8f77e195d256#.i39hn5g0b), an identical system can start over and over again and the end result (motor/muscle output) is different each and every time. Results can be related but are never the same, and sometimes very different. Sounds just like how our brains are different than everyone else, but we can still identify the same objects and experience the same qualia. I cannot say for certain that if I could observe your brain’s perception for a short period, that what you perceive as Red might look like Purple to my brain but to you it is Red and through our plasticity, we can both label Red as red. It is obvious that any two people will perceive the world in different shades and through our learning process, we each learn the labels associated to a particular object no matter how actually perceived. This is what makes emulating brains so difficult and why it is more in the realm of Physics than Mathematics. We both may have a Jennifer Aniston neuron but I can guarantee that if you look at thousands of brains, it won’t be the same neuron in the same place. It may be close, it may not, and it will always be different. And I think more importantly, how we recall Jennifer Aniston through our brains network dynamics is also very different. This is what makes the emulation of intelligence so very difficult. I am beginning to think the Deep Learning camps are either made up of lazy people, or as you stated, intelligently ignorant, because they can’t and do not seem to want to break out of their comfort zone of mathematics?

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