Remove Automation Remove Data Integration Remove ESG
article thumbnail

AI in 2025: Purpose-driven models, human integration, and more

AI News

Experimentation with pause moments for human oversight and intentional balance between automation and human control in critical operations such as healthcare and transport. However, Wilson warns of new questions on boundaries between personal and workplace data, spurred by such integrations. The solutions?

ESG 311
article thumbnail

How to accelerate your data monetization strategy with data products and AI

IBM Journey to AI blog

Serve: Data products are discoverable and consumed as services, typically via a platform. Take the example of a client who integrated a set of disparate company ESG data into a new dataset. Data monetization is about realizing value from data. watsonx.data adds data product lakehouse abilities and watsonx.ai

ESG 315
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

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.

article thumbnail

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. This guide can be used as a roadmap for integrating generative AI effectively within sustainability strategies while ensuring alignment with organizational objectives. A Gartner, Inc.

ESG 130
article thumbnail

Harnessing Machine Learning for Climate Change Mitigation: A Roadmap to Sustainable Future

Heartbeat

Through integrating sensor networks, satellite systems, and IoT devices, ML algorithms can continuously monitor environmental parameters, detect anomalies, and trigger automated responses or alerts. The below example code demonstrates the training and evaluation of a simple regression model.