Brain vs Computer - Speed Duel

With the help of industrial image recognition technology, machines can collect random graphics from groundhog equipment in real time, quickly transmit them back to the background for calculation, image processing, and generate movement instructions to complete the striking action.

The unit is designed for unsupervised public use: controls are recessed or shielded, moving parts are enclosed, and the interface is operable by a child of about six with no instruction. Where a screen is used, the language can be switched without changing the hardware, and the content can be replaced on site.

At present, the intelligent game between humans and computers mainly involves machine learning. In machine learning, algorithms are constantly trained to discover patterns and correlations from large datasets, and then make optimal decisions and predictions based on data analysis results. Machine learning applications have the ability to self evolve, and the more data they obtain, the higher their accuracy. Unlike in biological brains where a single neuron's electrical impulse does not represent valid information, electrical signals in computers have clear physical meanings. With the help of 5G and industrial image recognition technology, machine vision systems can collect real-time images randomly appearing on groundhog equipment, quickly transmit them back to the background for calculation, image processing, and generate movement instructions to complete the striking action. And all of this can only be achieved with the ultra high bandwidth image transmission capability and millisecond level network latency of 5G. After testing, the robot's tapping accuracy can reach 99.9% within 30 seconds, with a maximum of tapping times.