“LLMs are currently the most popular tech term, and their significance in the artificial intelligence (AI) world is becoming greater by the day. LLMs continue to fuel the generative AI revolution as these models learn to process human languages, such as ChatGPT and Bard.
LLMs have become a significant player in today’s evolving market due to their ability to mirror human conversations through their in-depth natural language processing (NLP) systems. Naturally, everything has its limitations, and AI-powered assistants have their unique challenges.
This unique challenge is the potential for LLM bias, which is entrenched in the data used to train the models”
Reference: Understand and Mitigate Bias in LLMs | DataCamp
LLMs are the new way of thinking, and summarize that thinking. LLMs is a great tool for the DH world as it can be used in various ways that improve the ideas of DH.
The issue we currently see with LLMs is generation of Bias or misconceptions. The two that are typically most noted are
The two main origins of biases in LLMs are:
- Data sources
- Human evaluation Understand and Mitigate Bias in LLMs | DataCamp
My thoughts are that for community, by community so it’s ok to use these tools with the proper monitoring and regular ongoing evaluations for quality improvement purposes.
LLMs show great strength, but it’s also important to know that the tool is very newly established and will have a ton of kinks to work out.
It’s not all-knowing, it’s biased – Demystifying AI (middcreate.net)
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