Vesela Motika Blog

  • The Most Effective AI Techniques for Lowering CO2 Emissions in Food and Automotive

    by Sergej Lugovic The Most Effective AI Techniques for Lowering CO2 Emissions in Food and Automotive
    This post investigates the substantial CO2 footprint of food and cars, examining both production and usage aspects, while exploring AI's potential to address associated environmental challenges. Analyzing data from food production, food waste, car production, and car usage, we reveal striking disparities and highlight opportunities for emission reduction. For instance, we find that food production emits nearly 40 times more CO2 than cars, with cars utilizing potentially recyclable materials for 3/4 of their production. Moreover, food waste accounts for almost 70% of the global CO2 emissions from cars. Through AI interventions like Natural Language Processing (NLP), Computer Vision, Forecasting, Personalization, and Fraud Detection, we propose strategies to curtail food waste, optimize resource use, foster sustainable consumption, and enhance automotive sector sustainability. These insights underscore AI's transformative potential in mitigating CO2 emissions and steering us towards a more resilient, sustainable future.