Generative AIFine-tuning large language models: A primer
Companies are eager to leverage the benefits generative AI (GenAI) offers. Implementing the technology, however, isn't a 'plug-and-play' process. Instead, it hinges on a critical task — fine-tuning a pretrained large language model (LLM) to be a specialist at your intended domain or application.
Data CollectionAutomotiveADAS field operations testing: Four essential considerations for program success
Discover the processes involved in field operations testing for enhancing advanced driver assistance systems and key considerations for program success.
Responsible AIHow to build responsible AI practices into your organization
As GenAI implementations become more prominent, it's critical to adhere to responsible AI practices to protect your brand and foster customer trust.
Generative AIHow empathy in your large language model can improve your CX
Can a chatbot be empathetic? Discover what empathetic chatbots look like, how're they're trained and the impact they could have on your business.
Generative AIA practical guide to GenAI applications for customer experience management
Learn about some popular customer experience GenAI use cases, and how the technology can help CXM leaders maintain a competitive advantage.
Generative AIFive strategies to mitigate bias when implementing generative AI
Discover five critical strategies for mitigating bias when implementing generative AI into your organization.
Generative AIInfographic: Consumer sentiment on generative AI training data
A recent TELUS Digital survey explored consumer sentiment around the origin and quality of generative AI training data. Take a look at the findings.
Generative AIExplainable AI: A four-step framework for intellectual oversight
As use of generative AI increases, it's critical to be able to understand how models arrive at the output they do in order to foster trust.
Generative AIHow to select a large language model
With so many diverse large language models to choose from, selecting one for your business can be overwhelming. Here are some key factors to consider.
Linguistic AnnotationNatural language processing: The power behind today's large language models
Large language models show incredible capabilities. Learn about the technology behind them and how they came to be the powerful machines they are today.
AI Best PracticesHow to detect and mitigate machine learning model drift
Model drift degrades the accuracy of your ML model over time. Discover some best practices for detecting and mitigating it quickly and efficiently.
Data AnnotationFour key metrics for ensuring data annotation accuracy
High-quality data annotation is critical to the performance of your AI model. Here are four key metrics to consider for measuring annotation accuracy.
Check out our solutions
Enrich your data with our range of human-annotation services at scale.
Learn more