Big data veracity, M2M learning and artificial intelligence

Big data empowers M2M learning and artificial intelligence so that it can improve the productivity but the veracity efficiency of the big data itself is important to determine the decision make by the AI is accurate due to when collecting and storing vast amounts of data and analyze big data information to consider if the data actually true?

The problem is that data is not only dirty or unreliable, it can be downright false due to if the information feedback by the sensors are not accurate then it will cause the wrong decision.

For simple example, when a Prime Minister surrounded by a groups of ministers who are only a yes men but do not tell the actual situations of the people then the Prime minister will think everyone is satisfied with his leadership but in facts opposites.

Same as the Industry 4.0, the AI is really depend on the hardware such as sensors which inform what is the actual situation otherwise the inability of the hardware to derive the wrong information then wrong decision will be make. Therefore the Virtual physical system need to work as a team to make the goals successful just like the Government.

Note: M2M learning = machine to machine learning.


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