Artificial Intelligence is no longer just hype: it is a reality. Artificial Intelligence-based approaches, such as Natural Language Processing (NLP), Machine Learning (ML) and Deep Learning, are becoming more realistic within the technology industry. We have today very efficient NLP engines as well as powerful ML and deep learning algorithms available. In a recent article on WIRED, I remember reading about the death of code (programs and programming) and how we will soon be training systems like we train our pets.
Machine Learning involves learning from examples and experiences: it’s all about digesting huge volumes of data. IBM and Memorial Sloan Kettering are training Watson in Oncology using the massive amount of patient medical records across the world. Watson learns from how doctors treat cancer patients worldwide, similar to how a medical student learns but on a larger scale.
Another example of machine learning can be found in Japan: here, farmers cultivate fresh and crispy cucumbers, with many prickles on them. Straight and thick cucumbers with a vivid color and a lots of prickles are considered to be of premium grade. Each cucumber has a different color, shape, quality, and freshness. Cucumbers are sorted into nine different classes based on size, thickness, color, texture, small scratches, whether or not it is crooked, and the number of prickles on it. There is no well-defined instruction set for classification of cucumbers.
Makoto Koike studied this problem while helping his parents to classify the cucumber on their farm.