With technology booms that are expected every year along with the best tech to keep companies and their clients happy, digital optimization and efficiency has been slower than expected in its assistance.
Digital spaces as well as physical spaces are joining with research companies and AI optimization companies for the ability to provide better customer input and recognition. The ability to find what the customer wants or needs as the fastest, readily available and minimal-effort option is part of ecommerce recommendation engines.
The technology has long been found to have gaps, however, in limiting the diverse choices and options that each individual customer or business may need. Algorithms and codes are often the first thing that latches onto a user, and only provides shopping options that are commonly used in online shops and retail. These algorithms, while a base for the next steps to advance functions, are going through new changes by companies like Sentient AI to provide a custom and overall efficient option.
Moving forward from the keywords to visual images and user history, as well as current activities that they may be doing allows the AI interfaces to build a network or profile for the individual users. It also stores the data and user ratings, comments and questions that can be answered by the software or by humans behind it. This building up of and onto the older AI options that only used words instead of visual databases being tested today is what changes the whole operation.
The integration of ecommerce recommendation engines by businesses and consumers is backed by the need to share a larger part of consumers; when you allow each customization to be optimized for variety, locations and making it a standard part of every business, the tech age is advanced even more. The success without the competition decreases, and further changes to a business that now has the information on what the consumers want rather than what the business is limited to understood.
Our world has gone through many advances in computer AI, and image recognition is no exception. Image recognition, also called computer vision, is a special kind of AI technology that allows computers to identify objects in images. Image recognition has helped greatly in identifying faces, text, and even general patterns.
Image recognition for faces, or face recognition, have been used for digital cameras and devices with a built-in digital camera to tag pictures. Certain websites that allow you to upload and tag pictures, like Facebook, also use face recognition technology. After taking a photo or uploading it, then little rectangles and squares start appearing on the faces of the people in it. Sometimes, you are even asked to tag these photos based off of the face recognition technology.
Optical character recognition, also known as OCR, is designed specifically to recognize text. Essentially, this is how a computer can learn how to read human written language: by recognizing the characters of letters and being able to understand the combinations of those characters in words and sentences. Multiple banks nowadays have used this technology, as has been advertised on television and the internet. People can deposit checks into their bank accounts, depending on the bank, by taking a picture of it and sending it to their bank. The optical character recognition technology used by banks can recognize the bank account number, signature, the amount you want to deposit, and other details on the check.
Of all of the three different types of image recognition, pattern recognition has to be the most complex and advanced. Pattern recognition can be used to learn what an object is based on a photo of that object. Imagine searching using an image instead of words. In fact, the Google search for images actually uses pattern recognition technology for their image searches now. All you would have to do is either upload a picture, copy and paste the URL of a picture, right-click a picture or click and drag a picture. The images you can use to search can range from pictures of handbags and locations to logos and cartoon characters.
Image recognition today is becoming more and more prominent for consumer use and convenience. That’s why certain companies, like Slyce, specialize in providing image recognition software and technology to other companies. Slyce is, in fact, one of the leading companies in providing image recognition software. So far, Slyce has provided their services to six out of 20 of the big name retailers here in North America, including Neiman Marcus and Tilly’s. They provide their technology to these retailers so that people would be able to take pictures of the products provided by these retailers and link them to information about those products. It is both convenient and efficient for shoppers and retailers alike. This is also one of the many different reasons why image recognition can prove to be a major tool in today’s world.