Ai - Artificial Intelligence vs. Human Intelligence
Closer than you think.
Learned (Memory) vs. Reasoning
The first concept that needs to be understood when determining the level of knowledge within a system is that of Learned Knowledge vs. Reason (Logic).
Quite often people consider a system "Smart" or "Intelligent" by the amount of information contained therein. However, memorization really does not account for ones power of reasoning. A system can easily be programmed to learn (aquire and memorize) knowledge, but may have a far more difficult task (for computers and humans alike) utilizing that knowledge.
Example of Learned(memorized) vs. Logic in Reasoning:
We will try to answer the question: "What is bigger a dog or a car ?"
Table 1: (Answer Generated from Memory)
| | User_Input | Learned_Output |
| 1 | What is bigger a dog or a car | A car is bigger |
| 2 | What's bigger a dog or a car | A car is bigger |
find Learned_Output where User_Input = "What is bigger a dog or a car"
Table 2: Logic (Reasoning):
| | Average_Volume | UoM |
| Car | 150 | cu_ft |
| Dog | 6 | cu_ft |
get object1[dog], get object2[dog]
if object1[dog].average_volume = object2[car].average_volume then "They are the same."
if object1[dog].average_volume > object2[car].average_volume then "Object1[dog] is bigger."
else "Object2[car] is bigger."
This is how both machine and human would address the question.
Often humans just memorize the answer (i.e. read it in a book, figured it out in the past then memorized, someone told them).
However, if the answer not known, then logic must be applied (for machine or human).
A human might take a generalized guess from memory.
A machine would require a data store of relative sizes.