Riddle of the Sphinx: Improving Machine Learning

Data Correlations Require Perspective

As I was going to St. Ives,

I met a man with seven wives,

Each wife had seven sacks,

Each sack had seven cats,

Each cat had seven kits:

Kits, cats, sacks, and wives,

How many were there going to St. Ives?


This short example may confound man and machine. How does a rules engine work, how does it make correlations to derive an answer to this and other riddles?  If AI, a rules engine is wrong trying to solve this riddle, how does it use machine learning to adjust, and tune its “model” to draw an alternate conclusion to this riddle?

Training rules engines using machine learning and complex riddles may require AI to define relationships not previously considered, analogously to how a boy or man consider solving riddles.  Man has more experiences than a boy, widening their model to increase the possible answer sets. But how to conclude the best answer?  Question sentence fragments may differ over a lifetime, hence the man may have more context as to the number of ways the question sentence fragment may be interpreted.

Adding Context: Historical and Pop Culture

There are some riddles thousands of years old.  They may have spawned from another culture in another time and survived and evolved to take on a whole new meaning.  Understanding the context of the riddle may be the clue to solving it.

Layers of historical culture provide context to the riddle, and the significance of a word or phrase in one period of history may wildly differ.  When you think of “periods of history”, you might think of the pinnacle of the Roman empire, or you may compare the 1960s, the 70s, 80s, etc.

Asking a question of an AI, rules engine, such as a chatbot may need contextual elements, such as geographic location, and “period in history”, additional dimensions to a data model.

Many chatbots have no need for additional context, a referential subtext, they simply are “Expert Systems in a box”.  Now digital assistants may face the need for additional dimensions of context, as a general knowledge digital agent spanning expertise without bounds.

 Sophocles: The Sphinx’s riddle

Written in the fifth century B.C., Oedipus the King is one of the most famous pieces of literature of all time, so it makes sense that it gave us one of the most famous riddles of all time.

What goes on four legs in the morning, on two legs at noon, and on three legs in the evening?

A human.

Humans crawl on hands and knees (“four legs”) as a baby, walk on two legs in mid-life (representing “noon”) and use a walking stick or can (“three legs”) in old age.

A modern interpretation of the riddle may not allow for the correlation and solving the riddle.  As such “three legs”, i.e. a cane, may be elusive, as we think of the elderly on four wheels on a wheelchair.

In all sincerity, this article is not about an AI rules engine “firing rules” using a time dimension, such as:

  • Not letting a person gain entry to a building after a certain period of time, or…
  • Providing a time dimension to “Parental Controls” on a Firewall / Router, the Internet is “cut off” after 11 PM.

Adding a date/time dimension to the question may produce an alternate question. The context of the time changes the “nature” of the question, and therefore the answer as well.

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