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Sustainability trends: 5 issues to watch in 2024

IBM Journey to AI blog

As more companies set broad environmental, social and governance (ESG) goals, finding a way to track and accurately document progress is increasingly important. 2 For example, some are turning to software solutions that can more easily capture, manage and report ESG data. The smart factories that make up Industry 4.0

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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning Blog

ESG and SRI focus**: A significant portion of the list consists of ETFs/ETNs with an Environmental, Social, and Governance (ESG) or Socially Responsible Investing (SRI) focus, which suggests a emphasis on sustainable investing. xxxx USD Corporate Bond 0-3yr ESG UCITS ETF USD (Dist) 2. Arghya Banerjee is a Sr.

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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Journey to AI blog

These innovations have showcased strong performance in comparison to conventional machine learning (ML) models, particularly in scenarios where labelled data is in short supply. Practical integration into software like the IBM Envizi ESG Suite can simplify the process while increasing the speed to insight.

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Data Integrity: The Foundation for Trustworthy AI/ML Outcomes and Confident Business Decisions

ODSC - Open Data Science

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

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The executive’s guide to generative AI for sustainability

AWS Machine Learning Blog

Organizations are facing ever-increasing requirements for sustainability goals alongside environmental, social, and governance (ESG) practices. Within this context, you can use generative AI to advance your organization’s ESG goals. The typical ESG workflow consists of multiple phases, each presenting unique pain points.

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Data Challenges In ESG Investing?—?A Comprehensive Guide

Mlearning.ai

Building a Resilient ESG Data Infrastructure for Sustainable Investment Continue reading on MLearning.ai »

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Accelerating sustainable modernization with Green IT Analyzer on AWS

IBM Journey to AI blog

Businesses are increasingly embracing data-intensive workloads, including high-performance computing, artificial intelligence (AI) and machine learning (ML). Companies are also striving to balance this innovation with growing environmental, social and governance (ESG) regulations.