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  1. Responsible AI

    How to design trustworthy AI products for healthcare: Five design principles

    Learn how these five artificial intelligence design techniques build trust in highly regulated industries like healthcare.

  2. Generative AI

    A 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.

  3. Generative AI

    Dataset pruning for intent classification: Because bigger isn’t always better in GenAI

    Data pruning helps generative AI developers manage increasingly massive datasets for better performance, lower costs, and more useful analytics.

  4. Generative AI

    Five strategies to mitigate bias when implementing generative AI

    Discover five critical strategies for mitigating bias when implementing generative AI into your organization.

  5. AI Strategy

    AI in business: The value of an orchestrated approach

    Navigating the challenges of artificial intelligence through an orchestrated approach

  6. Generative AI

    Infographic: 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.

  7. Generative AI

    Using LLMs to moderate LLMs: The supervisor technique

    The Supervisor LLM moderation technique uses one large language model to filter and moderate the content generated by another to prevent harmful outputs.

  8. Generative AI

    Generative AI in healthcare: Three real-world examples leaders can learn from

    These 3 real-world examples show how generative AI in healthcare boosts physician productivity, lowers costs, and improves patient outcomes.

  9. AI Strategy

    AI and ML: The cure for navigating healthcare complexities and concerns

    AI powers more efficient and intuitive digital healthcare experiences.

  10. Responsible AI

    Detecting AI hallucination risk using a CIA technique

    A CIA technique called a canary trap helps us detect AI hallucination risk in large language models (LLMs) enhanced with retrieval augmented generation (RAG).

  11. Generative AI

    Explainable 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.

  12. Generative AI

    Continuous evaluation of generative AI using CI/CD pipelines

    Integrating continuous evaluation of large language models (LLMs) into your CI/CD pipelines keeps undesired changes from impacting your generative AI solutions.

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