TECH & AI
Malcolm . It is in this way a unified data set feeds into the delivery of curated data .
“ Model accuracy is influenced by the size of the model ,” he continues . “ The larger the model in parameters , the better its reasoning skills , and the better its thought , the more accurate it is . The more data it ’ s trained on , the better it is at understanding the world which is described in words .
“ When you have this , you have a large language model , ie , transformers or generative AI .”
Leveraging open-source , improving efficiency The advent of open-source models has significantly helped financial institutions in this regard . “ These open source models allow firms to not have to go out and build their own foundational model ,” adds Malcolm , cutting down on technology investment , time and manpower costs .
“ Jensen Huang describes an opensource model as a University graduate who knows a lot about the world but nothing about your organisation . So banks must train that model on their business data ,” Malcolm explains .
“ Customising open-source models to your organisation ’ s needs is achieved using various techniques , such as supervised fine-tuning and Retrieval Augmented Generation ( RAG ). This really helps improve model accuracy .
“ The leading firms are working hard at data quality and experimenting with fine-tuning techniques , or partial finetuning techniques in combination with RAG to improve model accuracy .
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