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{"id":6214,"date":"2023-06-09T10:15:11","date_gmt":"2023-06-09T10:15:11","guid":{"rendered":"https:\/\/seoulchronicle.com\/disruptive-technology-by-permutable-ai-redefines-carbon-emission-predictions-in-business-supply-chains\/"},"modified":"2023-06-09T10:15:11","modified_gmt":"2023-06-09T10:15:11","slug":"disruptive-technology-by-permutable-ai-redefines-carbon-emission-predictions-in-business-supply-chains","status":"publish","type":"post","link":"https:\/\/seoulchronicle.com\/disruptive-technology-by-permutable-ai-redefines-carbon-emission-predictions-in-business-supply-chains\/","title":{"rendered":"Disruptive Technology by Permutable AI Redefines Carbon Emission Predictions in Business Supply Chains"},"content":{"rendered":"
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Permutable AI, an award-winning AI-driven sustainability data solutions provider, has launched a groundbreaking project aimed at revolutionizing the prediction of carbon emissions within global supply chains. With an emphasis on sustainability and collaboration with data partners worldwide, Permutable seeks to enhance the accuracy and transparency of undisclosed company emissions data, providing valuable insights into carbon emissions across industries and countries.\"\"<\/div>\n

Permutable AI<\/a>, an award-winning AI-driven sustainability data solutions provider, has launched a groundbreaking project aimed at revolutionizing the prediction of carbon emissions within global supply chains. With an emphasis on sustainability and collaboration with data partners worldwide, Permutable seeks to enhance the accuracy and transparency of undisclosed company emissions data, providing valuable insights into carbon emissions across industries and countries.<\/p>\n

Supported by a grant from Innovate UK<\/a>, the UK\u2019s national innovation agency, the project addresses the critical need for reliable carbon emissions reporting in the supply chain sector. As the world becomes increasingly aware of the environmental impact of greenhouse gas emissions and the urgent need to combat climate change, organizations are under growing pressure to disclose their emissions data and demonstrate progress in reducing their carbon footprint.<\/p>\n

One of the primary challenges in accurately assessing and reducing greenhouse gas emissions lies in the lack of comprehensive and standardized reporting. Many companies are not obligated to disclose emissions beyond scope 1, resulting in significant gaps in emissions data. Permutable AI\u2019s project bridges this gap by leveraging its expertise in natural language processing and data science to predict and estimate emissions across scopes 1, 2, and 3, offering a holistic view of companies\u2019 carbon footprints.<\/p>\n

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Precise predictions of corporate emissions have far-reaching implications for stakeholders across the supply chain industry. The development of effective climate policies and regulations relies on accurate emission data, enabling the implementation of measures to mitigate climate change.\u00a0<\/p>\n

By leveraging accurate emissions predictions, companies driven by a sense of corporate responsibility can set reduction targets, track progress, and showcase their commitment to sustainability. Investors can also benefit from reliable emissions predictions, enabling them to make informed decisions and assess the sustainability of potential investments. Furthermore, accurate predictions support effective climate risk management, enabling companies to identify and address climate change-related risks.<\/p>\n

The project\u2019s results have already showcased the superiority of machine learning models over traditional statistical methods in predicting emissions. Permutable AI\u2019s machine learning models demonstrated remarkable accuracy improvements, ranging from 68% to 99%, compared to using country averages. These results underscore the potential of machine learning techniques in estimating carbon emissions with relatively limited data.<\/p>\n

Benefits for companies in practical applications of Permutable AI\u2019s project include:<\/p>\n