LLMs are designed to predict sequences
of words:
To overcome their limitations in non-text processing, they need to be connected to the right tools.
LLMs have only trained with public domain data:
Private or restricted information is beyond your “knowledge”.
The data is out of date:
Large AI models are trained until a cutoff date, after which the training data is losing its update. The web searches they perform are inconsistent and do not retrain the model with updated data.
LLMs don't have your specific corporate context:
They don't know your internal processes, business nomenclature, policies, etc.; nor do they have the intuition to make up for that lack of context.
Limitations on the
context window:
A language model can only simultaneously “remember” and process a finite amount of information; if you exceed that limit, the model “forgets” initial details or detracts from them.
Inadequate instructions:
AI can't guess what you're looking for if you don't specify it in a way that's understandable to the model. Inaccurate instructions increase probabilistic uncertainty, producing generic, erroneous answers or hallucinations.
Your data is difficult
to process:
Even when you connect your documentation, if the data is cluttered or improperly formatted, the AI can't find, read or contextualize it well.
At iAutomator, we work with you to overcome these obstacles and make the most of artificial intelligence.
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