A Complex AI: The Smart Coffee Machine
Let's add some complexity to the system, and see what starts happening.
This time, we're building a smart coffee machine, and we're asking a different question - we want to know how the user wants their coffee.
There are many more inputs to the machine.
| Input | Meaning |
|---|---|
| Hour | The hour of the day, in 24-hour time |
| Temperature | The outside temperature |
| Time Since Last Brew | The time since the user last had a coffee |
| User A | If this is Jenny using the machine |
| User B | If this is Carl using the machine |
| User C | If this is Amanda using the machine |
And our outputs are…
| Output | Meaning |
|---|---|
| Milk | If there should be milk in the coffee |
| Temperature | The temperature of the final coffee |
| Foam | The amount of foam to produce |
| Strength | The strength of the final coffee |
| Decaf | If it should be decaffinated coffee |
| Sugars | If the coffee should include sugar |
This example is used in the complex example of machine learning.