Artificial intelligence Still is Not All That Smart!!

In the general business world, machine learning often goes by the most known name by everyone which is artificial intelligence. Machine learning is all about the using of algorithms to predict things whether a web security image contains a cat, what a Google user wants to search for, or whether a self-driving car should brake to avoid a crash. No one yet knows how to give a single computer system the mental flexible to reason and learn like a human being. But the buzzwords or no, the field is hot. Artificial intelligence start-ups have been getting more and more funding in recent years.

Big tech companies such as alphabet Inc. that is Google, Apple Inc. and amazon.com Inc. are investing huge on the technology now. Starting salaries for the specialists in that field can be very high as a half million dollars. Artificial intelligence start-ups are being acquired at a high rate. Corporate sectors are often wary of creating the technologies that are sure to disrupt their existing business models, but these giant techs are throwing caution to the wind. It is important to note that machine learning has not yet made its mark on the economy. You can see machine learning using everywhere in the world but that is in the economic statistics. Employment levels have returned to healthy levels and there is no evidence that machines are taking people’s job yet.

The machines have not replaced the human yet because the employment-population ratio age is 25-54 which is been increasing every year and productivity is only rising at a slow. Nor is the artificial investment boom yet big enough to cause a general investment boom. But like the computer revolution three decades ago, machine learning revolution will eventually make an impact on the economy. Since the technology is both so enormously broad and so new to many economists also their answer about this technology is inevitably highly speculative and general. Consider in trying to predict the engine in 18 century and the internet in 1992. But by considering the scope of their task Agarwal et al. do an excellent job.

The technology in business represents an increase in the supply of predictive power any task that any decisions that rely on making predictions are now going to be easier and cheaper. Authors generally do not envision a world full of automation, with machines replacing humans at every step of the production process. They see machine learning being deployed selectively at some nodes of the value chain where data is huge, leaving judgment on a human to focus on the rest of the work.

There are two cognitive tasks in which humans will beat intelligence algorithm for the foreseeable future is making predictions based on the small data samples and identifying what decides success or failure. Machine learning will revolutionize white collar jobs in the same way as that like engines, electricity revolutionized blue collar jobs. Machine learning could also accelerate the trend towards the elimination of routine jobs. And acts as a tool which will allow workers to skip some mental tasks and apply their brain power to only a select few things, which results in the big increase in productivity.

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