How AI leaders are reducing their environmental impact

The AI ​​rollercoaster of expectations and concerns continues to move at a breakneck pace as companies move closer to understanding the rapidly changing technology and its potential functions within their business. Recently, advanced artificial intelligence platforms such as generative AI and large language models (LLMs) have come under scrutiny for their voracious energy consumption and resulting ecological impact, with some researchers hypothesizing that LLMs consume hundreds of liters of fresh water and produce annual emissions equivalent to that of a small country.

As global warming exceeds 1.5 degrees for the first time in a full year, global stakeholders are asking where the bulk of the responsibility should lie to prevent the climate crisis from worsening. Climate change remains an issue of critical importance to both consumers and businesses amid these global efforts to reduce carbon emissions, which bodes ill for the public image of any company that uses consumptive AI tools without considering its carbon footprint to keep control. More importantly, rampant unchecked AI use could have disastrous consequences for the environment. Research from MIT shows that training actually has the potential to significantly slow global progress against climate change.