Tiago Ramalho, CEO of Recursive Inc., gave us an overview of how generative AI is playing a role in sustainability. He began by giving the background of his company, Recursive which is to make a fair and sustainable society by using advanced AI technologies.
In the beginning stage of Recursive, they spent time on how AI can be used to assist sustainability. They came down into 4 pillars; Accelerating innovation to bring products faster to the market, Increasing productivity with less energy and pollution, Providing better work and education to tackle the issue of labor markets, and Preparing and monitoring risks to prevent or forecast them.
Tiago stated that Recursive is using generative AI as a key to enable the use case of AI in sustainability as it can collect data without human contact.
He also gave us example use cases of generative AI from their clients. First, The double eyelid surgery forecast shows the customer the outcome of the surgery. This improves the satisfaction of their customer
Secondly, The weather data measurement combines data from various sources and types to process it and provide smaller scale detail from 1 pixel = 1km to 1 pixel = 300m he called this a “ Fused Data Representation”. In addition, the adaptation of the weather data can be used as a tool to help place solar panels in the most efficient area, he stated.
Next, Tiago said that 71% of students believe that AI teaching assistants will have a positive impact on their education as AI can enable opportunities in education access and teachers can spend more time with their students.
Lastly, The use of AI in risk mitigation is being used to monitor groundwater levels in Indonesia; to know the amount of irrigation required to prevent forest fires by collecting satellite images and AI learning to forecast groundwater levels.
Ending his speech, he mentioned that ensuring success is to overcome the challenges in integrating AI into the company’s workflows and processes along with aligning the development with the end users and society as a whole.
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