Research and Development (R&D) in various types of Artificial Intelligence (AI), there underlining infrastructure, and methodologies, such as:

• Large Language Models (LLMs)
• Large Reasoning Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Cache-Augmented Generation (CAG)
• Deep Learning (DL)
• Artificial Neural Networks (ANNs)
• Feedforward Neural Networks
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Long Short-Term Memory (LSTM) Networks
• Generative Adversarial Networks (GANs)
• Transformer Networks
• Fluid Artificial Intelligence (FAI)
• Crystallied Artificial Intelligence (CAI)
• Edge AI
• Distributed AI
• Long and Short Term Memory (LSTM)
• Natural Language Processing (NLP)
• Natural Language Understanding (NLU)
• Natural Language Generation (NLG)
• Natural Language Acquisition (NLA)
• Neural Machine Translation (NMT)
• Machine Learning (ML)
• Reinforcement Learning (RL)
• Generative AI
• Agentic AI
• Predictive AI
• Computer Vision
• Machine Vision
• Algorithms (various types)
• Supervised Learning
• Unsupervised Learning
• Open Source Software and Tools
• Open Source Algorithms and Models
• Long Chain Framework
• Long Graph Framework
• and a lot more