Artificial intelligence (AI) is becoming increasingly pervasive in our world, and with it comes a growing need for sustainable AI infrastructure. AI models can be computationally expensive to train and run, and the associated energy consumption and carbon emissions can be significant.
The Need for Green AI Infrastructure
There are several reasons why sustainability is a crucial consideration when choosing your AI infrastructure:
Environmental Impact: AI infrastructure can have a significant environmental impact, both in terms of energy consumption and carbon emissions. A 2019 research paper estimated the CO2 emissions from training common NLP models to be equivalent to the lifetime emissions of 5 cars. A more recent study by the Allen Institute calculates that for a large model with 6B parameters full training would have the approximate carbon footprint of a rail car of coal. Whichever way you look at it that is significant!
Cost: The cost of running AI infrastructure can be high, and energy costs are a major component of this. By choosing a sustainable AI infrastructure solution, you can reduce your energy costs, providing long-term savings.
Reputation: The global market is evolving, and consumers and investors are increasingly demanding that companies operate in a sustainable manner. By adopting a green AI infrastructure solution, you can demonstrate your commitment to sustainability and improve your reputation.
Steps Towards a Sustainable AI Ecosystem
There are several things you can do to choose a more sustainable AI infrastructure:
Choose Renewable Energy: Power your AI infrastructure with renewable energy sources such as solar, wind, or hydroelectric power to reduce your carbon emissions.
Use Energy-Efficient Hardware: Choose energy-efficient hardware components for your AI infrastructure. Seems obvious but this can help to reduce your energy consumption. For example, running on GPUs rather than CPUs as this can be far more efficient.
Cooling Techniques: AI systems generate heat and an often overlooked solution to sustainable AI infrastructure is cooling. Air cooling can be inefficient and modern techniques such as immersion cooling be used to reduce the energy cost of a data centre by 35%. It boosts system performance by preventing frequency clocking, which not only enhances performance but also cuts down on runtimes, overall costs, and power usage. It significantly reduces the Mean Time Between Failures (MTBF), ensuring that systems remain online longer, which is crucial for minimising disruptions, especially for long-running workloads. Additionally, did you know the heat can be re-used offering further sustainability benefits?
Optimise your Software: Streamline your AI software to reduce its energy consumption. This can be done by using more efficient algorithms, pruning unused code, and using quantization techniques.
Leverage Cloud-Based AI Services: Consider using cloud-based AI services instead of building and maintaining your own AI infrastructure. But remember not all clouds are built equal! Consider how energy efficient your chosen cloud is and where its energy comes from.
By following these tips, you can choose a more sustainable AI infrastructure solution that will help reduce your environmental impact, save you money, and improve your reputation.
Beyond The Basics: Additional Benefits of Sustainable AI
Here are some additional benefits of choosing a sustainable AI infrastructure:
Increased Resilience: Sustainable AI infrastructure is often more resilient to disruptions such as power outages and extreme weather events. This is due to sustainable infrastructure often being designed to be more efficient and use less energy.
Improved Innovation: Companies that invest in sustainable AI infrastructure are often more innovative. This is because they are forced to think creatively about how to reduce their environmental impact.
Attracting and Retaining Top Talent: Employees are increasingly looking to work for companies that are committed to sustainability. By choosing a sustainable AI infrastructure solution, you can attract and retain top talent.
To conclude, sustainability is not just an ethical choice; it’s a strategic one when choosing your AI infrastructure. By choosing a sustainable solution, you can reduce your environmental impact, save money, improve your reputation, and increase your resilience, innovation, and ability to attract and retain top talent.
Join the Green AI Revolution!
The future of AI is not just about being smarter; it's about being sustainable. If you're passionate about reducing your carbon footprint while harnessing the power of AI, now is the time to take action. EscherCloudAI is committed to providing Europe’s most Sustainable AI infrastructure, utilising 100% renewable energy coupled with immersion cooling and heat reclamation.
A special thanks to Chris Hingley for shedding light and insights into the environmental impact of AI and the importance of sustainable infrastructure.