Artificial Intelligence is among the fastest growing areas of computer science, with a large array of applications. Just a couple of years prior, it would be challenging to imagine exactly how significant artificial intelligence would be for our day-to-day lives.
Artificial intelligence includes various technologies like natural language processing, quarrying, deep learning etc that can be implemented in a variety of applications. Let's first be clear that artificial intelligence can be done without machine learning for a means to a conclusion.
It is important to understand that AI is not the future - it's already being put to practical use. Today's AI tends to concentrate on very specific issues and knowledge places.
The significant part quantum computing is the fact that it replaces the standard method of thinking of computing. However, even today the most effective computers of earth can't have even the intelligence of a kid.
In other words, AI still has a ways to go.
This being said, as AI develops, our world will grow more synchronistic. Much like the Internet, Artificial Intelligence is likely to become a part of human life in addition to a critical portion of business.
Some examples: In retail sector, AI is used in the region of theft detection. In the banking sector, AI can be utilized to detect patterns that are associated with money laundering.
The following are 10 companies leading the way in advancing AI for everyday solutions:
- John Paul
Artificial Intelligence makes it possible for machines to perform human-resembling employment. AI and automation has already started replacing jobs, causing even business leaders like Elon Musk to call for universal income. However, mass unemployment caused solely by AI technologies is still a ways off.
For now, applications of AI are primarily used to add functionality or optimize data processing - not replace human labor. The employment group most likely to be affected by artificial intelligence in the short term will be professional drivers. However, recent prototype tests of automated vehicles suggests that there is still much work to be done on that front as well.