As the poster boy of all things new and cool, Generic Artificial Intelligence (General AI) has been talked about as the cornerstone that will rapidly drive company purpose, with sustainable solutions on top. As a foundation model that works on the data it is given, Gen AI is often touted as a panacea for all the complex problems plaguing industries across the board. Therefore, this is a huge vote of confidence for the technology in the context of canceling the major problem statements of global warming, rising water levels and carbon footprint. It remains to be seen how well the technology performs.
At the recently concluded COP28, nations finalized agreements to focus on reducing emissions, thus aligning with the Paris Agreement’s goal of limiting global warming to 1.5°C above pre-industrial levels. Went. Although this work requires a deep understanding of the factors contributing to the problem, we are hopeful that the achievements of nominal technology (foundation models and machine learning) in the relatively short time since its inception will allow us to progress significantly faster. There may be some glimpse of solution. ,
As expectations and technology align, here are some pointers on how General AI can play a constructive role in reducing carbon emissions.
GenAI can significantly reduce CO2 emissions through sustainable manufacturing processes driven by machine learning algorithms. The platform can focus on efficient use of natural resources and prioritize waste management for better end-to-end manufacturing process optimization.
We see that the green building concept is being adopted by many organizations. Many of them are changing their headquarters to run on more eco-friendly principles. General AI, with its learning mechanisms, can predict the amount of energy required. Such optimization of grid management leads to greater accountability of resource consumption.
Any process requires constant analysis to improve itself. General AI, when working in collaboration with IoT technology-powered devices, can deliver accurate carbon reporting values ​​and insights, making the carbon-neutral process more efficient.
One of the key features of AI is its ability to study content patterns. If allowed, General AI, with its holistic approach, can analyze individual or collective data to suggest personalized actions to reduce carbon footprint, such as adjusting energy consumption or travel habits. On an industry scale, we can also refer to this as understanding the important pillars of scope emission levels.
Every industry has planned downtime for maintenance purposes, but there are also some problems in the form of equipment failures. General AI, by going through the operational history of the machine, can help stakeholders arrive at timely service roadmaps that not only extend the lifespan of the said equipment but also enhance their efficiency.
Management can funnel the huge potential of General AI to climate modeling and research by analyzing huge datasets and simulating scenarios. This can help key stakeholders have a better understanding of the climate crisis and adopt strategies that directly reduce carbon emissions.
Every process works on data. Data that is transformed into knowledge when shared with global players for a singular purpose. Gen AI platforms can empower knowledge sharing between industries to improve their approach to GHG emissions through potential partnerships in the form of joint research initiatives and technology transfer platforms.
This article is written by Lalit Das, Founder and CEO, 3SC Solutions.
