Pre-Cognition

The Triune brain, a visualization of the evolution of the human brain. Illustration by Joe Scordo for Hidden Scents: The Language of Smell in the Age of Approximation

Parts of the primate brain are made to deal with any potential situation. The way these highly adaptive brain parts work are by using recurrent loops that interfere with each other, in what is being called a “reservoir” network.

Perhaps we see headlines written like this because artificial intelligence work is typically performed by first predicting all potential situations (that is, until recently, with the advent of ‘deep learning’ techniques). In other words, the idea that a brain, or part of a brain, is designed to deal not with predictable situations but novel ones, is counter to this prevailing predictive technique.

I’d like to make a link here between this adaptive behavior and the fact that our sense of smell is not pre-coded but a blank slate. We do not have pre-existing preferences for smells, and the pattern of olfactory receptors in the nose seem to have no discernable pattern whatsoever because they're meant to learn anew for every creature and for every situation. This is because the way we interact with our organic environment is so complex, there can’t be a set of rules that work for every potential situation.

Smell is part of the mammal brain, and not rational thinking is part of the human brain. (Note that the mammal brain is not the same as the primate brain, which is only used as a term here to disambiguate it from the human brain…semantics!) Granted, primates have a prefrontal cortex too, and we have learned that there is not as much difference as once thought between humans’ and other animals’ brains. Nonetheless, smell is the animal inside us, and a link to our evolutionary past, and to a world much less predictable than the one we inhabit today.

Post Script

The primate brain is 'pre-adapted' to face potentially any situation

phys.org, Jun 2016

On Randomness and Certainty

Let’s say you read a headline announcing an advance in the way we generate random numbers. You might think to yourself, "First of all, why do we need random numbers in the first place?" Random numbers are important for many science experiments, and the field of statistics is ultimately based on randomness. Scientists and mathematicians need random numbers as a part of their toolbox in order to do good work. Next, you might ask, how do we get random numbers then? Old school methods involve the flipping of a coin, or the rolling of dice. These methods take a lot of time if you’re trying to produce a huge list of random numbers. Nowadays we use computers. The problem is, even computers produce results that are predictable. Hard to predict, but predictable nonetheless.

What are the chances? You mean to tell me that we can’t actually produce randomness? The paradox is that computers generate random numbers based on an algorithm. Everything they do is based on an algorithm, a set of instructions. Yet, nowhere in a set of instructions can it say, “Generate a random number.” Algorithms cannot think for themselves; technically, we the human programmers do the thinking. (And yet even we can’t generate random numbers.) I’m starting to confuse even myself here, so I should cut to the chase.

In a world where information avails itself to us in an ever-accelerating fashion, we might be led to think that one day we will be sure about everything – a  theory of everything, an omniscience of all future events. But if we remember that science – the thing we use to “be certain” about things – needs randomness to work, and yet we don’t really know how to get absolute randomness, then we can temper our visions of a fully programmed world where all existence is automated. Uncertainty will always be with us.

Notes:

Random number generator 'improved'

May 2016, BBC News