Machine Learning: Changing the Beauty Industry

Machine Learning: Changing the Beauty Industry

Machine Learning: Changing the Beauty Industry

So, maybe, it is time for machine learning to transform beauty salons where traditional biology and pharmacy fail? BY SCIFORCE, MEDIUM

July 9, 2019

Obviously, machine learning can help the beauty industry in several ways, from providing statistical basis for attractiveness and helping people look more attractive to develop products which would tackle specific needs of customers.

The core of the future technology is, without doubt, computer vision — the part of AI that deals with the theory and technology for building artificial systems that obtain information from images or multi-dimensional data and further process it. In the beauty industry, it is expected that computer vision would help recognize facial features, analyze the data obtained and come up with a prediction or a conclusion about the appearance.

On the one hand, the ability of AI-driven computer vision to properly analyze a human face is incredibly handy for testing purposes and it might help end users choose products and techniques that would be perfect for them. In the past, it was nearly impossible to know how a new eye shadow or a face cream will actually look on the skin without physically testing them. At present, armies of data scientists are working on AI systems that can understand the human face. Once mastered, the ability to test out new looks and products will become exceptionally easy and realistic.

On the other hand, AI can make a breakthrough in the development of new formulas. Data has always been used to create better products and optimize formulas. Traditionally, a perfume is physically tested, reviewed and compared before being released. At present, data can be used to optimize specific scent ratios to create the next hit. Similarly, data analysis will lead to better cosmetics. Leveraging data means better, longer-lasting formulas.

Some businesses go so far as to develop applications to determine your skin needs and come up with personalized products:

A similar idea is central to Atolla Skin Lab solutions. So far, the company uses a specialized database in conjunction with a machine-learning algorithm to connect combinations of ingredients to skin attributes, based on skin hydration, oil content, sun damage, age, and skin concerns and goals. Atolla is working on a smartphone app which would rely on “computer vision” to track results, improving the algorithm and allowing the brand to make adjustments if necessary.

 

Read the full article on Medium.