Uncertainty in AI to make decision in situation like,
What to do? when we don't know what to do.
Its kind of tong twister though but its a situation we all came across as a developer, we need to handle the exceptions in the code[but not all developers] in which we don’t know handle some exceptions when it arise but we will just place it in try… catch block as we too lazy to find the root cause. But in AI we need to take the decision to keep the process up and running in situation which occurred by factors like,
- Sensor limitation – limitation when we try to use one sensor for two operation.
- Adversaries – Make hard to understand the environment.
- Stochastic environment – Random outcome of events.
- Laziness – lazy to computing sensor data.
- Ignorance – We fail to handle the situation that may or may not occur.
As the translating engine is trained with different examples of two different language with rater not difference between stokes and letters of two language, it will learn about the related words for each words in the languages so it can match the words on translating process. It’s more like photographically memory in the engine.
Lets break down the process in programming language,
- Array ‘A’ which has words in Hindi.
Array ‘B’ which has related Hindi words in English.
Now all we need to do is match the following words, a simple switch case can do the job.
As we keep adding the words the code need to be refined and handle those situation, this is where AI plays its part by learning the process and make it better by probability of chances the word related to other language.