Virtual Internet explained

Virtual Internet explained.


How Known (can) become Unknown Through Artificial Intelligence


We have been talking about big data and artificial intelligence for a while and it is obvious to discuss their usage in airline industry. According to M. Porter, it is the least profitable business known. Right to security, maintenance, operational cost and so on, it is such a challenging business to consider. Thinking about 9/11 when 4 airplanes were hijacked is another drawback with this industry. Governments have adopted strict regulations at airport and checks have been strengthened in the past and becoming more sophisticated today but there is less attention given to the airplanes, what if there is such situation again? Are those airplanes intelligent enough to tackle these issues themselves, thinking about machine learning, is there any possibility to develop a self defense mechanism inside the airplane which no one knows. It is highly important to understand the security of information when talking about information security. The idea behind this is to make this defense mechanism completely uncertain to the people working for it, and this can build more uncertainty in the minds of terrorists. What if the mechanism starts itself to knock down the terrorists, and there is less possibility to stop it because machines are not emotional and are not to negotiate. When there is such defense mechanism available at numerous points, and when machine learns itself every now and then in a controlled manner but a human friendly defense mechanism which no one knows how it will defend but capable of finding who is the defaulter with the sophisticated programs to get triggered for a genuine reason can help organizations to build a hijack free airplanes. There should be a proper test for these defense mechanisms to be triggered and should be completely silent and there will be less information about its existence on the flight. The reason for not disclosing this information to anyone is the ‘security’. Although there will be questions arising, how can we check/test something which can act on its own? It will create confusion on the whole system which should be managed collectively with highly confidential people in the organizations. The less data we share, the more secure the environment is. Also, leveraging this machine learning’s at the time of crash also can bring some interests in the organizations designing the airplanes. What if the planes repair itself for some minor failures happening in the engine and bring some ideas to avert the crash before it’s too late.

Can Artificial intelligence be used to don’t know what we can know?

Upcoming article –
Object recognition/Image recognition

What is special about the data? why we cherish moments in Sports?

Asking people who are related to these data, asking questions to them about its usages such as if someone has just scored a goal today, but it might be his special football goal when his team won, the player could remember a record build for his team winning the game whenever he scored or eventually from penalty will add more sense on how we extract the data. Likewise asking questions to the people related with the data can give insight for running those queries and harness the data in a relevant manner. This is just an example, there could be people applying for many jobs, and if he is interested in a particular job but due to market conditions, he is looking for other subsidiary jobs available in the market could tell organizations where he really fits? Asking people about the data generated by them can give an idea of how to use those data and for what reason? It is difficult to implement but this could lead to some desired results if done appropriately.