Acceleration through AI

Artificial Intelligence (AI) systems require considerable amount of energy due to their need for complex computations and the processing of large datasets. Deep learning models, which are at the forefront of current AI, involve processor-intensive mathematical operations across vast networks of parameters. Training these models is not only computationally intensive but also iterative, requiring multiple passes over the data to refine the algorithms. Additionally, handling high-dimensional data like images and videos further compounds the energy consumption.

On top of that, the training and operation of AI typically necessitate the use of parallel processing with multiple CPUs or GPUs, which, while efficient in terms of speed, significantly increase energy use. Moreover, the infrastructural needs to support AI—such as data storage and transfer, and the continuous operation of services—contribute to its high energy demands. The specialized hardware like GPUs, although designed for efficiency, still consumes substantial energy, particularly in large data centers.

“Data centers, the beating heart of our digital age and the backbone of AI operations, are estimated to account for about 2% of the world’s electricity use – comparable to the energy use of a large country.”

Today, Robovision empowers more than 1000 robots in 40 different countries. These machines perform tens of millions of visual inspections every week with powerful Vision AI algorithms. As a consequence, the amount of computing power to run those inspections and refine the algorithms is substantial. Some of Robovision’s clients run these on their own hardware or dedicated data centers. Others rely on Robovision to run the inferences. For these clients, computations happen at the data centers from Bytesnet in the Netherlands. Here’s why we chose to work with Bytesnet.

Green Data Centers

Bytesnet isn’t just another data center provider; it’s a beacon of sustainability in the digital realm. This is how they are making a difference:

1. Innovative Cooling Techniques

Traditional data centers rely heavily on energy-consuming cooling systems. Bytesnet, however, does things a little differently. By immersing their IT equipment in a special oil, they’ve pioneered a method that’s not only more efficient but also extends the lifespan of the equipment. This technique also produces residual heat at higher temperatures, making it more valuable for secondary uses.

2. Harnessing Residual Heat

This cooling technique allows for another groundbreaking initiative. Bytesnet is redirecting the residual heat from its d’ROOT data center to heat homes in the city of Groningen. Thanks to the elevated temperatures achieved through oil cooling, this heat is of superior quality. The result? A staggering CO2 saving of at least 55% compared to traditional heating methods.

3. Green Data Centers

Bytesnet’s commitment to sustainability doesn’t end at efficient cooling. They’ve taken a holistic approach to green operations. Concerns have arisen over the years about the environmental impact of electricity from biomass and hydropower. Bytesnet has addressed these concerns by purchasing Guarantees of Origin (GoOs) from European Wind, ensuring their energy sources are as green as their operations.

Why Sustainable AI Matters

As AI becomes more ingrained in our daily lives and industries, its energy consumption will only rise. It’s essential to address this now, laying the groundwork for sustainable growth. Robovision and Bytesnet’s partnership is a shining example of how businesses can lead the charge, proving that innovation and sustainability aren’t mutually exclusive but can, in fact, complement each other.

The collaboration between Robovision and Bytesnet is more than just a business partnership; it’s a commitment to a greener future. AI has the potential to shape our world in ways we can’t even imagine yet. But with this potential comes the responsibility to ensure that our advancements don’t come at the planet’s expense.

In conclusion, as we stand on the cusp of an AI-driven era, it’s partnerships like these that give us hope. Hope that our technological advancements will be matched by our commitment to sustainability. Hope that the future of AI is not just smart but also green.