Addressing bias in AI models is a key principle of responsible AI. Discover how diversifying your team of AI contributors through impact sourcing can help.
Discover how a potential AI training data shortage for language models could affect your business, and what you can do to offset its impact.
Artificial intelligence is set to define the future of banking. Learn about how banks are using machine learning, RPA and other AI-powered tech.
AI data demands classification to be useful at scale. Learn the benefits, challenges and best practices of data classification.
Learn how a leading technology client leveraged TELUS International’s AI Data Solutions to build a multilingual dataset that helps researchers scale natural language understanding technology.
Data annotation can create bottlenecks in AI and machine learning projects. Learn how to improve data quality and overcome data annotation challenges.
Examine how TELUS International evaluated high-quality data and merchant ratings to enhance the customer experience.
Training AI systems demands observing data quality best practices. Learn more about AI data quality control in this primer.
Experts believe autonomous vehicles will substantially improve road safety. Discover how large, diverse and accurate datasets are enabling this vision.
Machine learning demands massive amounts of clean, structured, labeled data. Learn the fundamentals of data labeling for successful AI training.
Discover TELUS International’s responsible AI principles for delivering better AI outcomes.
Learn how computer vision will play a vital role in transforming the metaverse into a commercially accessible reality for brands across industries.
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