Initiative Concept of Innovative Color Mix and Match Cognitive Approach, to Learning Machine (Robot Cognitive Learning to Advance IEEE and AI Technology)

AI algorithms are inseparable from data mining and precise leakage technology, which inevitably involves transportation capacity and calculation speed. This article hopes to use the help of public data to calculate results so that machines can learn with the help of humans. It is a calculation algorithm that breaks the current general calculation concept. Using color-mix and match calculation algorithms to improve the efficiency of machine learning, reduce reliance on the current one-way calculation method that only improves calculation speed, and use humans as a method of learning to improve reasoning and identification capabilities. This article innovatively proposes a color recognition method. It is called the color discrimination method for short. It uses humans to improve the perception and intellectual abilities of artificial intelligence (robots). From the five senses of color, fragrance, and taste (e.g. warm tone), it first learns the discrimination of colors, thereby establishing the machine's perceptual and intellectual abilities (Color Segment of Mixed and Match Cognitive). Approach uses inference algorithms to improve learning efficiency and reduce reliance on calculation speed alone. It uses cloud storage methods and humans to improve perception and intellectual learning. It also uses cloud storage to collect human color perception and intellectual big data to learn cognitive for robots, thereby establishing a cognitive color discrimination system.