Artificial Intelligence (A.I.) is a hot topic these days. Microsoft, Google and Amazon have invested heavily in this technology and continues with efforts to democratise it. This would make A.I. accessible to small businesses who don’t have funding for data scientists, or the computing power needed for intensive algorithmic processes.
As a technology A.I. requires large amounts of data to provide real value; the storage of which these technology giants have made available through its cloud datacentres. This cloud infrastructure is what provides the scale, security and computing power on a relatively inexpensive platform we as consumers need to run A.I. algorithms.
We’re seeing businesses make smarter decisions faster and increasing their profitability as a result. A.I. has also made incredible leaps in the healthcare industry, environmental sciences and anti-terrorism initiatives.
Is it intelligent enough?
Unfortunately, not yet! A.I. currently lacks contextual empathy and this makes it hard to compare to Human Intelligence (H.I.). If we want to achieve this, the focus needs to shift from ‘decoding’ to ‘understanding’. Professor Douglas Hofstadter described this very well in his article on language translation using A.I. We put this into practise and ran a similar test using Google translate.
Give it a try
Using English to Italian translation, we entered the following sentence: “In their house, everything comes in pairs. There’s his car and her car, his towels and her towels, and his library and hers.” This seems like a simple task for ‘deep learning’ A.I. to process. The results proved to be rather disappointing.