ARTIFICIAL INTELLIGENCE STILL ISNT ALL THAT SMART!!
ABOUT:
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
weather a web security image contains a cat, what a Google user wants to search for, or weather 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 vary 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 a healthy levels and there is no
evidence that machines are taking of 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 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 relies on making predictions is 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 judgement on human to focus on the rest of the work. There are two
cognitive tasks in which humans will beat intelligence algorithm fort 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 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.