Software Testing: Acceptance Test-Driven LLM Development

The development of large language models (LLMs) and the role of acceptance test-driven development (ATDD) are central topics in software development with artificial intelligence (AI). David Farago, an expert in the development and quality assurance of AI-based telephone bots for medical practices, shares his experience and insights into this process in this episode of the Software Testing podcast.

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ATDD: Challenges and Solutions

Richard Seidl and his guests will shed light on the challenges and solutions faced during training and testing of LLMs, including the use of accelerated engineering and fine tuning. Particularly noteworthy is the approach of applying ATDD methods in LLM development to improve the quality and effectiveness of models. Another focus of the episode is on the CPMAI (Cognitive Project Management for AI) process, which represents a modern approach to the development and implementation of AI projects.

Software Architecture Gathering 2024 in Berlin: the event is set

A note from Richard Seidl: “Sorry for the poor audio quality, unfortunately we only noticed that later. I hope the content will comfort you :-)”

This podcast is all about software quality: whether test automation, quality in agile projects, test data or testing teams – Richard Seidl and his guests look at the things that bring more quality to software development.

The current issue is also available on Richard Seidl’s blog: “Acceptance Test-Driven LLM Development – David Farago” and stands Available on Youtube,

(MDO)