SPECIALISED APPLICATIONS CAN NOW BE DEVELOPED THAT APPLY GENAI-TYPE TECHNIQUES , CONTEXTUALLY , TO DATA THEY HAVEN ’ T SEEN BEFORE – LEARNING FROM AND PROCESSING THE CONTENTS ON THE FLY . that efforts to monitor its integrity do not undermine the significant efficiency gains that are possible .
H E A L T H I N S I G H T S
by human team members ; sampling which can be calibrated as confidence grows in the technology ’ s performance – ensuring
SPECIALISED APPLICATIONS CAN NOW BE DEVELOPED THAT APPLY GENAI-TYPE TECHNIQUES , CONTEXTUALLY , TO DATA THEY HAVEN ’ T SEEN BEFORE – LEARNING FROM AND PROCESSING THE CONTENTS ON THE FLY . that efforts to monitor its integrity do not undermine the significant efficiency gains that are possible .
Streamlined technology validation
Because LLMs make it possible to bypass the need to train AI models or algorithms , a single technology solution can handle all variations of incoming data , simplifying the system validation burden . RAG patterns can play an important role here , in explaining a standard operation procedure to an LLM using natural language , so that the system knows what to do with each of many thousands of forms – without the need for special configuration for each relative format .
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