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Understanding the 27 Unique Challenges in Large Language Model Development: An Empirical Study of Over 29,000 Developer Forum Posts and 54% Unresolved Issues

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Understanding the 27 Unique Challenges in Large Language Model Development: An Empirical Study of Over 29,000 Developer Forum Posts and 54% Unresolved Issues

Revolutionizing AI with Large Language Models (LLMs)

Practical Solutions and Value

LLMs like OpenAI’s ChatGPT and GPT-4 have transformed natural language processing and software engineering, offering capabilities for tasks such as text generation, understanding, and translation.

However, developers face challenges in integrating LLMs into applications, including API management, unpredictable model output, and data privacy and security.

Empirical studies have identified 27 unique challenges in LLM development, providing valuable insights for developers and organizations to improve the process.

These challenges highlight the need for better support, documentation, and resources to facilitate efficient LLM development and integration into various applications.

Evolution with AI

For companies looking to evolve with AI, leveraging the insights from the study on LLM development can help stay competitive and redefine work processes.

AI can be used to identify automation opportunities, define measurable KPIs, select suitable AI solutions, and implement AI gradually for impactful business outcomes.

Connect with Us

For AI KPI management advice and continuous insights into leveraging AI, connect with us at hello@itinai.com.

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Vladimir Dyachkov, Ph.D
Editor-in-Chief itinai.com

I believe that AI is only as powerful as the human insight guiding it.

Vladimir Dyachkov PhD

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