Learn how to evaluate LLM quality and limitations using a range of testing techniques, from unit and regression testing to ...
Companies investing in generative AI find that testing and quality assurance are two of the most critical areas for improvement. Here are four strategies for testing LLMs embedded in generative AI ...
Application security solution provider White Source Ltd., also known as Mend.io, today launched System Prompt Hardening, a dedicated capability designed to detect issues within the hidden instructions ...
In the chaotic world of Large Language Model (LLM) optimization, engineers have spent the last few years developing increasingly esoteric rituals to get better answers. We’ve seen "Chain of Thought" ...
As generative AI, and in particular large language models (LLMs), are being used in more applications, ethical issues like bias and fairness are becoming more and more important. These models, trained ...
Pilots that looked promising do not always survive the transition, and the failure pattern is consistent enough that data leaders can plan around it. This article describes three failure modes that ...
As businesses move from trying out generative AI in limited prototypes to putting them into production, they are becoming increasingly price conscious. Using large language models (LLMs) isn’t cheap, ...
Look to these key metrics and benchmarks to evaluate the performance, capability, reliability, and safety of your AI models ...
IBM has inked an agreement with AI Singapore (AISG) to test the latter's Southeast Asian large language model (LLM) and make it available for developers to build customized artificial intelligence (AI ...
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