Large language models show incredible capabilities. Learn about the technology behind them and how they came to be the powerful machines they are today.
Part 2 in our series explores how WillowTree benchmarks the accuracy of applications with large language models in the loop, examining the metric of "truthfulness" on a nonbinary scale.
Our latest findings on the differences in behavior between the OpenAI and Azure OpenAI API
Model drift degrades the accuracy of your ML model over time. Discover some best practices for detecting and mitigating it quickly and efficiently.
WillowTree’s approach to benchmarking accuracy of applications with large language models in the loop.
Boost AI reliability by preventing AI hallucinations with WillowTree's three-pronged approach to minimize and mitigate incorrect information produced by LLMs.
AI hallucinations are a reality of working with large language models (LLMs), but a defense-in-depth approach helps reduce generative AI hallucination rates.
High-quality data annotation is critical to the performance of your AI model. Here are four key metrics to consider for measuring annotation accuracy.
Staff augmentation relieves many common problems in data engineering and data science. Learn how TELUS Digital helps businesses properly augment their data teams.
Hallucinations are an obstacle to building user trust in generative AI applications. Learn about the phenomenon, including best practices for prevention.
A survey conducted by TELUS Digital unveiled consumer concerns about misinformation and bias in generative AI. Learn more.
Choosing the best artificial intelligence (AI) consulting company for your business involves diving into each firm’s track record, strategic approach, and more.
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