According to Google Flights' estimate, a round trip of a fully loaded passenger jet between San Francisco and New York would release 180 tonnes of carbon dioxide equivalent (CO2e). Meanwhile, the training emissions of Google's 11 billion parameter T5 language model and OpenAI's GPT-3(175 billion parameters) stands 26%, 305% of the round trip, respectively. The "state-of-the-art" models require a substantial amount of computational resources and energy, leading to high environmental costs. Deep learning models are getting larger by the day. Such large models are routinely trained for thousands of hours on specialised hardware accelerators in data centers.

Technology, artificial intelligence and automation are supposed to solve our biggest problems, not create new ones or exacerbate existing issues. Unbeknownst to many, big tech is actually putting a huge burden on the environment. In a study assessing the energy consumption required to train several common large AI models, Researchers at the University of Massachusetts Amherst said artificial intelligence emissions can be over 626,000 pounds of carbon dioxide, which is about 5 times as much the lifetime emissions of an average car. According to research firm IDC, spending on AI systems is exploding, with the figure expected to hit nearly $98 billion in 2023, more than 3.5 times the $37.5 billion being spent this year. The U.S. is expected to deliver more than half of that spending through the forecast, which will be led by the retail and banking industries, according to IDC.