LLY-HDC uses hyperdimesnional computing and neurosymbolic AI to implement a high-performance AI model on quantum computers

LLY-GLLM is the precursor to the interpretative Large Language Model of the LILY Project and is designed to understand relationships between words. It is based on parameterized quantum gates.

LLY-GP is an estimated Language Quantum Model that can infer relationships between words based on input terms.

LLY-DML is part of the LILY QML Project and is a Quantum Machine Learning initiative specifically designed for image recognition. It represents a specialized version of the LLY-DML model.

LLY-DML is part of the LILY project and is a Quantum Machine Learning model. It uses so-called L-Gates. These gates are Machine Learning gates that modify their state based on an input to map to a desired state of an input.

LLY-LLM is the Quantum Large Language Model of the LILY project and describes a model that can generate responses and represent complex relationships through training.