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GAIMIN has launched video rendering into the services provided by gaimin.cloud, GAIMIN’s decentralised, distributed data processing network.
GAIMIN’s video rendering service is a lower cost service providing a faster turnaround time whilst spreading the data processing energy consumption footprint globally using PCs already running other applications and services and solving one of the world’s biggest digital problems today..
“The World is Running out of Data Processing Power”
Satya Nadella, CEO Microsoft
In 2020, it was estimated that 1.145 trillion Mb of data was created every day; every human created approximately 1.7Mb of data per second. In 2022, 91% of Instagram users engage with brand videos, users send 650 million Tweets per day, 333 billion emails per day are sent, 42 million WhatsApp messages are sent per day, Google handles 6 billion searches per day, and there are 4.95 billion active social media users (62% of the global population). A lower definition 480p video streamed on YouTube uses 8.3Mb of data per minute, 500Mb per hour. A higher-quality 1080p video uses more data! One SnapChat uses 1Mb of data. The world is running out of data processing power!
With video consumption expected to grow, more video producers will create higher quality, longer video content which needs to be converted (rendered) into the output video. Creating the video is a data processing-intensive activity, further increasing the requirement for data processing in this already competitive market for data processing service availability.
Centralised versus decentralised data process services
Centralised data processing farms are well established but are not the most appropriate solution. They are costly to set up and maintain, they draw significant amounts of electricity from the local distribution network for both running the data processing devices and also running the infrastructure, such as air conditioning and hardware cooling, impacting supply in the locality. Centralised data processing farms are costly to set up and maintain and can also be limited on physical growth, which is all reflected in their cost to provide a service!
A cheaper, more efficient and environmentally friendly approach is to decentralise data processing, spreading service delivery world-wide and using devices that are already running and doing “something else”, thereby spreading energy consumption and usage across the globe, across different timezones and…
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