When IBM’s Watson computer beat the highest-rated game show contestants in 2011 on Jeopardy, it was a sign of what was to come. After that, in the same year, the A.I. assistant Siri was unveiled for the Apple iPhone. As always, similar kinds of products have been developed and marketed by other companies. Google Assistant is the preferred substitute for Siri that Android users adopt. Most people in the developed world interact with A.I. regularly, but might not see it that way. Today, unless you’re tech-savvy, you might not notice just how much A.I. has become a part of our everyday lives.
An AI Winter?
There was a lot of hype surrounding what would be possible with artificial intelligence leading up to 2020. Billions have been invested in researching and creating new functions for A.I., but some experts feel like A.I. doesn’t have much more to offer. This is what is called an A.I. winter; a period when there might be a lack of new ideas and financing, leading to a lack of progress in this field.
Making AGI a Reality
Other experts feel like A.I. technology has gone as far as it can go in this phase, and is, therefore, shifting into another phase. It seems like the next phase is what is known as artificial general intelligence (AGI) by leading authorities in A.I. technology. AGI is the ability of artificial intelligence to be just as smart as a human being. It would mean increasing learning capacity to a level in which A.I. could take more firm control in manufacturing and medicine.
Although this won’t happen any time soon, progress is being made, and innovative companies like ALPHABOT Labs are leading the way. They aim to help doctors enhance the care they give their patients with the help of A.I. Companies like these develop A.I. applications to speed up diagnoses, prevent mistakes in prescribing medications and help make treatment more personalized overall. The accurate use of a multitude of data is what makes this possible.
In the past decade, the field of A.I. has come a very long way, but there is still a long way to go before AGI becomes a reality, the way A.I. has been. For A.I. to take on more complex behaviors, it will take more sophisticated data processing and the right hardware and software platforms to support this level of computing.