Explore a technical overview of AI red teaming principles, informed by methodologies our experts at TELUS Digital employ when stress-testing our clients' models for safety and security vulnerabilities.
Explore a detailed technical account of how the team at TELUS Digital built a proof of concept using OpenAI’s Apps SDK, including the architecture choices made, the pitfalls encountered and the lessons learned building on this emerging platform.
Explore our benchmarkable multimodal dataset designed for fine-tuning and evaluating scientific reasoning through domain-grounded visual question answering.
Explore the three paths to AI adoption — enterprise, platform native and point solutions — to build your business’s adoption strategy.
Learn how Fuel iX™ is helping organizations move from AI confusion to confident implementation through hands-on education and actionable insights shared at the AI Ignition events in Toronto and Montreal.
Explore a comprehensive conceptual approach for systematically evaluating agentic AI models and assessing their readiness for real-world applications.
Discover how AI can transform post-discharge healthcare, improve patient outcomes and significantly reduce hospital readmissions and healthcare costs. Download the full report to unlock the future of personalized, efficient and effective healthcare delivery.
This playbook breaks down real-world use cases, cost-saving formulas, and implementation tips to help you assess AI agent impact in your organization.
Discover how TELUS Digital incorporates automated quality control agents into our training data pipelines for greater efficiency and accuracy.
How your conversational AI talks to users has a direct impact on customer satisfaction, retention and loyalty. Businesses that understand this are the ones making continuous evaluation of their conversational AI systems a standard practice. This whitepaper presents TELUS Digital's proven method for ...
Large language models (LLMs) offer the efficiency and advanced semantic understanding that today’s text summarization systems need. By prompting an LLM to act as an evaluator — a technique known as LLM-as-a-Judge — AI teams gain valuable insights for enhancing system performance.
With this guide on advanced RAG techniques, you’ll drive greater performance and lower costs from your retrieval augmented generation system and LLMs.
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