Bloomberg research: RAG LLMs may be less safe than you think
Retrieval-Augmented Generation, or RAG, has been hailed as a way to make large language models more reliable by grounding their answers in real documents. The logic sounds airtight: give a model curat...
Low-rank adaptation (LoRA)
Low-rank adaptation (LoRA) represents an innovative stride in enhancing the performance of large language models within artificial intelligence (AI). By focusing on efficiency and adaptability, LoRA s...
Segment Anything Model (SAM)
The Segment Anything Model (SAM) represents a significant advancement in the field of image segmentation, leveraging deep learning to redefine how multiple objects can be identified and delineated in ...
In-context learning
In-context learning revolutionizes the educational landscape by customizing learning experiences based on individual circumstances. By recognizing that each learner operates within a unique set of con...
ANFIS
ANFIS, or Adaptive Neuro Fuzzy Inference System, stands at the intersection of two powerful computational paradigms: fuzzy logic and artificial neural networks. This unique combination enables ANFIS t...
