Hey there!

We've taken a step back to see what's behind the scenes. While 2023 marked an unprecedented surge in the popularity of Large Language Models, led by the phenomenal success of ChatGPT, beneath this explosion, lurks a significant environmental concern: the carbon footprint of these models.

Our last issue highlighted that LLM training relies on massive data centers and thousands of GPUs. These facilities consume enormous amounts of electricity, equivalent to lighting up a small country for several hours, resulting in substantial carbon emissions. While the industry has made strides in acknowledging and addressing the carbon emissions from training LLMs, a critical aspect often goes unnoticed: the emissions from running apps powered by these models.

Carbon ScaleDown: Rethinking the Environmental Impact of our AI Conversations

ChatGPT, for instance, has been serving millions of daily active users for over a year, far exceeding its training duration. The implication is clear: the environmental impact of LLMs extends beyond development into their everyday use.

This is why we have some exciting news to share with you! We've created Carbon ScaleDown, a Chrome Extension that will help you measure and track the carbon footprint of your ChatGPT chats! This extension calculates emissions based on the generated tokens and images, offering users a tangible understanding of their digital environmental impact.

We wanted to give you a simple tool to help you be more conscious about your use of LLM models. We hope you'll love it!

Check out the extension!

In our first article, we talk more about our motivation behind building this extension and briefly describe how it works. We'll also take a closer look at some research papers that show us how much carbon is produced by different ML models and tasks. We'll see how the complex models we use today produce orders of magnitude more carbon emissions than the biggest models from just a few years ago. Read more below!

Calculating the Carbon Emissions of ChatGPT

While researchers have begun examining the factors that contribute to carbon emissions, focusing on specific tasks and models, research on the emissions resulting from model inference is still in its early stages.