TECH & AI
NVIDIA AI Enterprise
“ Once you ’ ve fine-tuned and validated your model , you can deploy it using RAG . Combining high-quality data , supervised fine-tuning , and RAG enables your model to perform better . This means the model will provide the sought-after answer to prompts ( a question by another name ) on the first go more often instead of having to iterate your prompt several times before the model figures out what you are after . It starts to become expensive .
“ And so for those firms , as they start experimenting , they realise that model accuracy leads to more efficiency and a better experience .”
This is the next consideration for banks – efficiency , both in terms of time and costs .
It ’ s clear that data quality , model accuracy , and model size are all interrelated when it comes to efficiency and cost savings .
Building an AI Factory that supports multi and hybrid cloud The next challenge for banks is to leverage an AI Factory that enables them to develop and deploy models anywhere . If they have sensitive data , need to prove their workload is resilient , would like to meet customers across clouds , or are concerned about accuracy , cost ,
138 August 2024