Discover how TELUS Digital successfully deployed a robotic process automation (RPA) solution for a leading waste management company to minimize time-consuming tasks and reduce the errors associated with manual data entry.
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.
Learn how TELUS Digital partnered with the SETU Foundation to train a computer vision workforce for current and future annotation projects.
Boost AI reliability by preventing AI hallucinations with WillowTree's three-pronged approach to minimize and mitigate incorrect information produced by LLMs.
Learn how we helped a leading multinational technology company train their recommendation engine using image classification.
Discover how Ledcor, a leading construction company, introduced robotic process automation (RPA) with RPA-as-a-Service (RPAaaS) to make key finance processes more efficient.
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.
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