the engineers embarked on improving the algorithm. To do so, there are two possible approaches. One is to fight complexity with complexity. The idea is: Complex problems need complex solutions, and if a complex algorithm fails, it needs to be made more complex. The second approach follows the stable-world principle (View Highlight)
The idea behind it is that a complex algorithm using big data from the past may not predict the future well in uncertain conditions and it therefore should be simplified (View Highlight)
Blind and rapid search through terabytes of data would be sufficient to predict epidemics. (View Highlight)
just increase volume, velocity, and variety and measure what correlates with what. (View Highlight)
Under uncertainty, keep it simple and don’t bet on the past (View Highlight)
people do not automatically rely on what they recently experienced, but only do so in unstable situations where the distant past is not a reliable guide for the future (View Highlight)
in an unstable world, reducing the amount of data and complexity can lead to more accurate predictions. (View Highlight)