by Dr. Sam L. Savage
Stochastic Data from Ancient Greek στόχος (stókhos) ‘aim, guess’ means uncertain data. But wait a minute, all data is uncertain.
That’s my point!
AI can make statistical sense out of uncertainty. Visit our webpage Gateway to AI where we have posted 8 short videos on what I call the Stochastic Data Cycle.
Coherent Stochastic Data
AI is trained on Stochastic Data, and AI can produce Stochastic Data. But before that data may be used in subsequent calculations it must be converted to a SIP (Stochastic Information Packet). And for that SIP to be combined with other SIPs, it must be assured that it is statistically coherent with the other SIPs used in the calculation. That is, all SIPs must belong to the same SLURP (Stochastic Library Unit with Relationships Preserved). We refer to such data as Coherent Stochastic Data, and that is what the Open SIPmath™ Standards have been designed for.
You Decide
Imagine that you asked AI to roll a die one million times. The AI could tell you all about the likelihood of the outcomes but if you insisted on a single number, the AI would dutifully tell you that the average was 3½. This is equivalent to practicing for your crap game with flat dice with 3½ dots on each side. So to summarize:
AI is trained on Stochastic Data.
AI can output Stochastic Data if you have a place to store it and a way to use it.
The Open SIPmath Standard offers both.
Copyright © 2024 Sam L. Savage