A post from our partners at Numenta, demystifying AI vs. ML vs. MI and so on.
We are frequently asked how we distinguish our technology from others. This task is made difficult by the fact that there is not an agreed vocabulary; everybody uses the above terms (and other associated terms) differently. In addition, the commonly understood meaning of some of these terms has evolved over time. What was meant by AI in 1960 is very different than what is meant today.
In our view, there are three major approaches to building smart machines. Let’s call these approaches Classic AI, Simple Neural Networks, and Biological Neural Networks. The rest of this blog post will describe and differentiate these approaches. At the end, we’ll include an example as to how each approach might address the same problem. This analysis is intended for a business rather than technical audience, so we simplify somewhat and thus beg the indulgence of technical experts who might quibble with the details.