Artificial intelligence keeps expanding throughout all kinds of sectors and industries, from health care to transportation and from education to e-commerce. The quick growth of AI-systems, especially large language models (LLM’s) and generative AI, also comes at a cost. It has a significant impact on the environment.
The debate about sustainable development, climate action and AI’s carbon footprint gets more lively by the day. We explore the carbon footprint of AI, explain why people are often unaware of the impact of AI on the environment and present a sustainable alternative to the big and popular models.
Table of contents
What is the carbon footprint of AI?
When we talk about the carbon footprint of AI, we refer to the total of greenhouse gas emissions generated across the lifecycle of AI systems. We are talking about the manufacturing of the computer chips, the electricity consumed during training of models and daily usage across the globe.
Artificial intelligence keeps becoming more complex, which makes it a more demanding process for computers and chips to keep up. It also causes a rise in energy use and emissions. For a sustainable future for our planet, governments and businesses should take action and make more conscious decisions regarding their use of AI.
The energy needed for the training process
Training large language models, generative AI-models and other deep learning systems requires massive computational resources. These processes are driven by graphics processing units (GPU’s), tensor processing units or specialized chips in data centers.
The environmental costs are also related to the construction of data centers, supply chains and water usage for cooling. With older data centers running on fossil fuels, we should also add up power plants generating more electricity than ever.
Training powerful models can generate carbon emissions that are comparable to those of entire towns. This begs the question: how much power do we think is okay to use for the training and daily usage of these increasingly larger AI-systems? Or should we rethink those systems?
Emissions from everyday use of AI-models
Once they are trained, AI-models continue to consume energy during inference. This is the process of generating an immediate response to user prompts in the forms of natural language processing, image generation or coding tasks. Each interaction requires electricity.
Inference happens millions of times per day across global data centers. Each request may seem small, but the cumulative impact is large. The energy usage of AI in consumer tools, enterprise systems and government services might even exceed the impact of training the models.
Why AI’s environmental cost is often overlooked
For everyday users, the environmental costs of AI remain largely invisible. People interact with the interfaces and can’t see the computing machinery behind the scenes. This makes them unaware of the consumed electricity, the greenhouse gases emitted and the water used for cooling hardware.
There are many numbers and statistics out there about the energy use of AI, but big players like OpenAI are not fully transparent about energy and emissions. Therefore, it is impossible to exactly calculate the emissions of AI. But with millions of users worldwide, it sure is significant.
GreenPT’s approach to low-impact AI
At GreenPT, we believe AI can be used in a way that’s sustainable and friendly for the environment. We designed our models from the ground up to reduce the carbon footprint of AI and focused on issues like privacy and efficiency as well.
With our model you can perform complex cognitive tasks, transcribe and analyze virtually any static image, generate code, translate in real-time, gain intelligent insights by scanning documents and convert speech to text in multiple languages. Basically, everything you expect from a LLM.
What makes our model special, is that we deliver all of this sustainably. We are fully powered by renewable energy, reduce computing power by 20 to 30 percent without quality loss and are ISO-certified for energy management and information security.
Let’s delve deeper into those benefits with regard to energy consumption, global greenhouse gas emissions and energy efficient AI. Our goal is to bring a halt to AI’s growing carbon footprint with smart computer science.
Fully powered by renewable energy
The servers of GreenPT are running solely on renewable energy, so that’s a 100 percent. The industry standard is 60 percent. That is a significant gap, which makes us an environmentally friendly choice. We ensure zero carbon emissions from our operations.
Our models are smaller and more efficient
We use smaller, more efficient models and specialized lightweights agents to minimize computational requirements. Efficient model selection means that we need a lot less computer power, while the output remains of the quality that you expect.
Our data centers are ISO-certified
Our data center maintain ISO-50001 and ISO-27001 certifications for energy management and information security. This ensures that we use energy responsibly and protect data how it should be protected.
Your data is protected under EU laws
All data processing from GreenPT happens exclusively in the European Union. This means that your data will never cross EU borders. Your data is protected by strict European laws, such as the GDPR.
Your data is not used for training
We store your chat only for your personal history. You can manage all your own conversations and we will never use your data to train our AI-models. Furthermore, your prompts are encrypted in transit and at rest using AES-256 encryption.
The performance metrics of GreenPT
GreenPT outperforms the industry average across all indicators for sustainability.
First, we use power more efficiently. Our Power Usage Effectiveness (PUE) delivers a score of 1.37. This is far below the industry average of 1.57, which means that we have a significantly higher efficiency when it comes to energy use.
When it comes to Water Usage Effectiveness (WUE), our data centres score 0.067. This is way lower compared to the industry average of 1.8. This shows that we use a lot less water, which is better for the environment.
And like we said before, our infrastructure is a 100 percent powered by renewable energy. The renewable share in the industry overall is 60 percent. These numbers make GreenPT a leader when it coms to sustainable AI-operations.
Why choosing responsible artificial intelligence matters
While AI is booming in every possible direction, it may be hard to think about sustainability at first. But at the same time, the use of AI puts pressure on our power grids, water systems and global supply chains. AI is not some kind of magic, it has a very physical component to it.
In order to manage the environmental impact of generative and predictive models, conscious choices have to be made. That’s why we developed a sustainable alternative to the big GPT’s we all know already. With us, green energy powers every prompt.
We believe in smarter tech with a smaller footprint. Start your GreenPT trial today. Create an account and explore our green and privacy-first AI-platform. There are flexible plans, no strings attached, cancel anytime.
