GLYNT.AI Inc., The Sustainability Data Company, announced today that its innovative AI technology leads to lower energy and water use when using AI to prepare data than would be used by LLMs or typical cloud AI tools for the same task. GLYNT.AI released its white paper, “The Sustainable Way to Prepare Sustainability Data” which details how it measured its level of energy, water and emissions, and how the result compares to other AI algorithms used for the same tasks.
“When building our technology platform, GLYNT.AI faced a huge challenge: How to unlock the key data needed for sustainability and climate reporting that is trapped in invoices, utility bills, manifests and other PDFs, CSVs and JSON files,” said GLYNT.AI CEO Martha Amram. “The files are hugely varying and change over time. So we needed a powerful AI system to unlock the data at scale while maintaining accuracy.
“We built a deployment of ‘Few Shot’ ML that uses a library of tiny, tiny training models. Each model can be trained in minutes and needs just three training samples. The model returns data at greater than 98% accuracy rates from the start and so very little retraining is needed. Our hyper-efficient use of computing resources leads to energy and water usage that is less than 5% that of LLMs, and less than 20% of the emissions from standard AI tools from cloud providers for the same task.”
The Bottom Line:
The study shows our customers that there is no tradeoff: GLYNT.AI’s technology is hyper-efficient, delivering both business and sustainability wins.
