Memory & Matching Game

Turn over the cards and memorize their locations. You have to find all the pairs.




The Matching Game, also known as Match a Pair (or Google Matching Game), is a small, casual game developed by Google, often used to train and test the capabilities of neural networks in the field of visual recognition and machine learning. This game is also loved by children and adults, because you can have fun and have a good time with it.

The essence of the game

The goal. Find pairs of identical images among the many inverted cards.

Mechanics. The player turns over two cards at a time. If the images on the cards match, the pair remains open. If not, both cards are turned back over. The game ends when all the pairs are found.

What is Google used for?

Machine learning model training. Google uses this game to collect data on associations between images and to train neural networks to recognize similar objects. Each time a player finds a pair, it provides data to improve image recognition algorithms.

CAPTCHA verification. In some cases, the elements of the "Matching Game" can be used as a CAPTCHA (a Completely Automated Public Turing test to tell Computers and Humans Apart). It is assumed that it is easy for people to match images, but this can be difficult for computers.

Demonstration of AI capabilities. Google can use the Match game to demonstrate progress in computer vision and machine learning to the general public.

Features and Options

Different topics. The Matching Game can use different sets of images with different themes (animals, food, sights, etc.). This allows you to test algorithms on different types of visual data.

Different difficulty levels. The number of cards (and therefore the number of pairs) can vary, determining the difficulty level of the game.

Interactivity. The game often involves interaction with the user in real time, which allows you to collect data on user behavior and their strategies.

How it works

Data collection. Google collects huge amounts of data about how people compare images. Which images they consider similar, how fast they do it, etc.

Neural network training. This data is used to train a neural network that learns to extract features from images and determine which images are most similar to each other.

Improvement of algorithms. As the neural network learns from more data, its image recognition ability improves, leading to more accurate results in other Google applications (for example, image search, Google Lens, etc.).

Where to find the game

Depending on the purpose of Google, the game may appear in different places.

Embedded CAPTCHAS: Sometimes embedded in authentication processes.

Online Experiments: Google can create online experiments or demo versions of the game for research or demonstrations.

Educational resources: Can be used in educational materials dedicated to AI and machine learning.

Conclusions about the Matching Game

Google's "Matching Game" or "Match a Pair" is a simple but effective way to collect data and train neural networks for visual recognition. The game also allows users to pass the time, simultaneously developing memory and spatial thinking. The online game is an example of how even simple games can be used to solve complex artificial intelligence problems.