In The Age of Approximation

Please note that this article is one year old…and that in the meantime Microsoft was sued for the way they rolled out their new omniscience machine

Lots of talk about Windows 10; I like this article from Ars Technica about the necessity for (what may seem like) excessive data collection integrated into the platform. But therein, we see the changing face of computing as one leveraging approximation over precision (a la Olfaction).

Olfaction as a model for the future of software development? How about the present.

From the article-

Siri needs to know the names of your contacts to be able to set up calls or send messages. Cortana needs to know when and where your appointments are to tell you when you need to leave the home or office to get to them.

But there's a deeper reason: the software powering these capabilities is fundamentally heuristic, using approximation and guesswork to generate its results. Traditionally this wasn't the case; a hardware keyboard with no autocompletion doesn't need any fancy heuristics, it just needs to directly map key presses to characters. But speech recognition, software keyboards of all kinds, and handwriting recognition don't have this precision. The software driving these things has to construct and evaluate a range of different possible interpretations and then pick a most likely option among those interpretations.

This is the way of olfaction. Within the impossibly complex chemosphere, the nose-brain must approximate in order to make sense. The ultimate need for flexibility is reflected in the design of the receptor patch that receives vaporous molecules - some receptors code for specific odor molecules, some for many, and some for nothing at all. Even at the outset, olfaction is a game of ambiguity.

On Thinking Like a Human

Intuition Algorithm download in progress

The computer processing analogy that we use for describing the way the mind works matches only the more rational side of human thought, and the senses most associated with them (vision and sound). Or at least that’s the way it used to be, before the AlphaGo defeat.

Other ways of thinking are more intuitive, and more in line with the primitive senses (smell). These types of thinking are becoming more important, because they are more analogous to what it means to be human today, as compared to a computer, that is. It turns out that humans are not rational enough to integrate with computers, i.e. robots; the problem with self-driving cars is that they’re too rational; they follow all the rules, all the time, and humans don’t.

What we bring to the table, as humans rather than algorithms, is the ability to make intuitive decisions based on accumulated experience. I’d like to point out that this accumulation is called memory, and although it is “stored” in the brain, it requires a body to get there in the first place. This is one of the main reasons why olfactory perception can be such fertile ground for research.

Basically, humans would rather guess than go through a bunch of bad options. Sometimes we’re wrong, but when we’re right, we just saved a whole lot of processing power.

In this study, a huge group of game players was tasked with solving a very complex problem. Instead of running every possible solution, which would take forever, the players search intuitively. And the study showed that this intuition-searching happened to be similar for each of the individual game players, hinting at a possible “intuition algorithm” for the future of computing. If investigating the artificial unconscious looks like a good bet, then we might see the half-primitive half-cognitive “language of smell” gain some attention soon.

Notes:

Are humans the new supercomputer? Team blurred the boundaries between man and machine

phys.org, May 016