LLMs, or large language models, should be used with caution as they can prove to be unreliable, particularly for those without analytics training. However, that does not mean that they should not be used, because when used correctly, they can play a key role.
Will they replace data analysts?
Used correctly, LLMs can provide greater analysis and crunch more data than a data analyst alone. But while we can never be certain what will happen with technology in the future, there is no sign that they will replace the human data analyst any time soon.
Instead, data analysts are needed more than ever to work with LLMs to make sure that prompts are crafted carefully and to verify that outputs are accurate. If you do not have in-house data analysts, it is worth using the services of a data analysis company like //shepper.com/ to be able to use the potential of LLMs fully.
Text Analysis
LLMs can accelerate text analysis and, if multimodal, can even analyse and interpret oral language. Ways they can help include transcribing spoken outputs, translation, highlighting categories of words, looking for commonalities like common references, providing semantic scoring and identifying contextual information.
An example is in customer feedback. An LLM could analyse customer reviews, picking out common elements and sorting them into positive and negative comments to help a company understand areas they need to improve.
Visual Media Analysis
LLMs can analyse the content of visual media like charts, pictures, and videos. This ranges from identifying the number of a particular object in a picture to more subtle activities like analysing the colour palette of a YouTube video. They can also be used to identify trends across a whole range of media, something that could take a vast amount of time for a human analyst working alone.
Potential Threat Identification
With their ability to analyse data far quicker than humans alone, LLMs can analyse both text and visual media. Combined with data from other sources, they may be able to identify potential security threats.