LILY is a project aimed at making Quantum Machine Learning accessible to the public, as well as developing new Quantum Machine Learning models. Eventually, all

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.

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 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 …

Stanford CS149 -- Assignment 3

A convolutional neural network implemented in hardware (verilog)

opensouce RISC-V cpu core implemented in Verilog from scratch in one night!

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants