Sensitive to size and diversity of data sets

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Tools like Perplexity generate answers based on the datasets they have been trained on. Since these LLMs are fairly recent in their development, their datasets are still smaller and not very diverse.

This is one of the reasons why interactive search engines like Perplexity do not always give accurate answers.

For example, we asked Perplexity to give us ad headlines that were no longer than 60 characters to help us promote an upcoming webinar. The responses generated were less than 30 characters and were not very engaging. This is likely because their training did not include enough ad copy or similar marketing language.

Lack of data diversity in AI Perplexity

Perplexity AI may not always provide accurate insights due to lack of diversity in data sets

Perplexity IA Reviews on Reddit
We took to Reddit to find out what people think about Perplexity. Many users have highlighted that Perplexity can write code efficiently by referring to online sources.

However, users also noted that Perplexity gives inconsistent and short answers to their search queries. This compliance directors email list can limit troubleshooting and research.

" TL;DR : Perplexity AI excels at coding with online sources, solving difficult math problems with the help of WolframAlpha, offering specific search modes, effectively searching Reddit, finding local businesses, and providing concise answers. However, it falls short on complicated science outside of math, lacks problem-solving capabilities, sometimes provides inconsistent and short answers, and has limits on search breadth and format. Despite its limitations, Perplexity AI is worth a try, especially when combined with other AI models to improve information accuracy.