Carbon Emissions of an ML Engineering Team

Everybody is aware of the climate crisis due to global warming as a result of human activities. To prevent its catastrophic consequences [1], the world needs to reduce our greenhouse gas emissions drastically, with many countries setting a target of net zero emissions by 2050. The technology boom of AI in recent years has also raised concerns about its environmental cost. If we only look at its direct contributions, this will come through the use of electricity to train and power models. For example, training ChatGPT-3 with its 175 billion parameters generated a whopping 502 tonnes of carbon equivalent emissions (tCO2e) [2]. The new kid on the block Llama2 outputs a similar 539 tCO2e for training its family of four models [3]. For context, each of these is equivalent to the emissions of a passenger taking a one-way flight from New York to San Francisco 500 times. <a href="https://towardsdatascience.com/carbon-emissions-of-an-ml-engineering-team-ce170bd4fae9">Website</a>