Machine learning is capable of doing amazing things. But can it create new information, outside of the environment it is operating on?
Month: October 2016
Adequacy
Don’t start too big. Start small and prove the point.
Optimization
Optimize the underlay as well. Don’t just focus on the overlay.
Scaling
Use tools appropriate to your scale.
Suitability
Using the right tool for the right job, requires a lot of knowledge.
Autonomy
Autonomy leads to greater certainty, and if there’s one attribute you want inherent in your networks, it’s certainty.
Redistribution
Redistribution is done to those who are able to adapt and adjust.
Transparency
Things are well done, when you don’t need to worry if they exist or not.
Indecisiveness
Too much data available is disabling decision making.