Machines, brains and science - Random thoughts about random neural interactions (crazy!) - FINAL PART

A forced explanation cornered by neuroscience and Machine Learning

INTRO

"Cybernetics: (Or Control and Communication in the Animal and the Machine)", is an outstanding book where Nobert Wiener gave a name to a discipline by the first half of the 20th century. In it, the charismatic little man expresses that the best science is the reflection of the technological challenges of its contemporary times. His, was an era of information existing by the separation of a signal that controls a mechanism and the power that provides the energy. This is, at the same time the conceptual separation that became usual as a revolutionary technology became available in that time: The Transistor. Today, transistors became infinitely smaller and numerous (there's 2 thousand million in an iPhone 6 chip). We are no longer worried about how to transmit information around the globe, today we worry about how to access that information and get "what we want" from it in an understandable way.



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Machine Learning

1. Other applications for AI leave a trail of similar feelings. A few years ago IBM's Watson defeated human experts at the game "Jeopardy", a true cornerstone at computerized natural language. A sneak peek at the optional responses the computer considered before giving a final answer make us think that its mental Universe is a rather "exotic" one. So, when the question about the protein that gives rigidity to the hedgehog spines (keratin) was made, Watson replied the correct answer... Yet it was also thinking and considering "hedgehog" and "fur" as "secondary thoughts". One does not need to be a genius to know that those answers cannot even be considered as "wrong". They are inadmissible to anyone that speaks a human language.

 

Everyday science is not what it used to be

1. If Machine learning is nothing but the blind processing of several thousand calculation of some glorified abacus following rigid rules, why would it change the way we see what we understand as science? What does an algorithm has to offer to science that a brain cannot? To answer that, we need to consider humankind's largest theories. Since Newton, physics was the absolute queen of modern understanding of the world; we can easily guess why. The taste of victory against the Cosmos that is left behind as we understand the orbits of planetary systems is just, too big. Physics can predict things. Quantitative predictions. Numbers do not rely on adjectives, opinions or feelings. They strip away subjectivity to leave only the hard, solid facts visible: Your gravitational acceleration measurement throws a "9.8 somethings" result? HOLY SHIT! MINE TOO!!! The quantitative predictions, in their best performance, lead into qualitative surprises. Uranus irregular orbit lead Verrier to predict the existence of Neptune, a guy that had the honor of "discovering a planet only with a pencil". Glancing through numerical calculations, displaying his expertise about the Cosmos itself; we can see another attractive in physics, elusive yet fundamental: the promise of conceptual unification. What is the symbolic power Newton's apple has other than "the same rule that govern everyday items also governs the rest of the universe"? I cannot do anything but highlight this first unification, that was followed by others, the notion that thanks to it we've today reached a deeper understanding.

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General rules in a particular world?

1. In today's world part of what is happening is that, we are running out of questions about simple things to learn. Physics, with all its math, is the science of direct questions and answers so rigid they beautify the panorama of this dirty and imperfect reality. Today studying physics implies that pupils will learn nothing that has not happened before their parents were born.
2. The opposite side is Natural Sciences, it looks like, biology, where 1st year students talk about the most recent literature available. Their prime study consists in, of course, life: that random construction where it prevails... what does prevail? is there any theories? It is said that evolution is the only general notion in biology. At first glance, a science that followed a totally different path than Physics did; deepening in specific details, attempting to unmask the way pre-selected models work. Like a linguistics scholar analyzing an antique scroll of his choice, a biologist chooses his favorite system, genetic branch, protein, technique, organism and adores it the rest of his life. A romantic path where an act of faith resides: that the description we make about the topic will eventually shed some light over general principles we only build conjectures about. Biology is the way of alegory. Sometimes it brings health and beautiful stories. Other times, fat and heavy books.

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I am aware that I may have overdone it a bit... Believe me, it is much more enjoyable face to face, where a certain level of interaction is achieved from the "public" (nothing like being able to ask questions, or add information yourself). Sadly Steemit does not encourage this, and 90% of the time the comments section is used by dull responses :(

I seriously expected this to become a "better social network".

Having no point to write any more... I'll just leave this here, in the hope that "someone" will read it in a month, year, or decade... lol

(I'm not even pasting the dumb copyrights footer... welcome to the internet)
(I'm not even adding images... there's nobody looking!)