By posing fundamental questions about machine intelligence, Turing believed that human minds could one day be mimicked by electronic circuitry. In a theoretical paper published in 1936, Turing described an imaginary device, which would later become the electronic computer, behaving as if it were a human being and given problems to solve.

The concept of the computer program grew directly out of this research, and the ability of a machine to enact cold, hard logic at high speed is now the reality – able in many ways to outperform humans at many tasks.

This is because there is a natural desire for humans to do two things, create narrative, and create structure. In other words, we see two disconnected events and try and create a story that links them together, quite often inventing causes that are not there – try “googling” “JFK conspiracy theories”! Therefore, when people look at networks, a lot of the issues associated with network management arise when people create narratives for alerts, and see their own “phantom” causes. For example, they see that CPU is high, and memory is low, so the two must lead to an action that actually might not be linked.

Also people will see structure in randomness that is not there. A simple trick to illustrate this is to ask people to bet on the flip of a coin. Often if a sequence of heads or tails occurs (not as uncommon as you might think), the natural tendency is to bet against the sequence; even though, we know that the odds are always still 50/50, we have convinced ourselves that we have seen a pattern in the results.

The reason a network management platform such as RiverMuse exists is to do away with the seemingly random irrelevance and noise – if you will, these systems exist to de-bunk the “conspiracies” that the human mind creates naturally allowing you to see what is actually going on. You do not have to look at the data that pertains to random patterns, but instead you can investigate the information that is more causal.