Enhance your customer experience, empower users to create and share custom copilots, and proactively identify and mitigate risks with Fuel iX by TELUS Digital. Discover how more than 50,000 users are leveraging our award-winning generative AI engine to achieve results.
TELUS Digital creates human-aligned datasets to fine-tune and evaluate generative AI models. Explore how this diverse and accurate data can increase your model performance, adaptability and safety.
Explore how TELUS Digital created an off-the-shelf dataset to advance the capabilities of large language models (LLMs).
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.
See how a major North American financial services firm developed a safe, secure, and expansive conversational AI assistant with help from TELUS Digital.
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.
Learn about some popular customer experience GenAI use cases, and how the technology can help CXM leaders maintain a competitive advantage.
Data pruning helps generative AI developers manage increasingly massive datasets for better performance, lower costs, and more useful analytics.
Discover five critical strategies for mitigating bias when implementing generative AI into your organization.
A recent TELUS Digital survey explored consumer sentiment around the origin and quality of generative AI training data. Take a look at the findings.
The Supervisor LLM moderation technique uses one large language model to filter and moderate the content generated by another to prevent harmful outputs.
These 3 real-world examples show how generative AI in healthcare boosts physician productivity, lowers costs, and improves patient outcomes.
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.
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