Technology9

Learning Portal @T9

  • Implementing RAG Retrieval Process in AI Models

    Retrieval-Augmented Generation (RAG) is an advanced technique in Natural Language Processing (NLP) that combines the capabilities of retrieval mechanisms with generative models. At its…

  • Implementing RAG Vector Database in AI Models

    Retrieval-Augmented Generation (RAG) leverages external knowledge to enhance AI models’ ability to generate accurate and contextually relevant outputs. A pivotal component of this architecture…

  • Implementing RAG Embedding in AI Models

    Retrieval-Augmented Generation (RAG) relies heavily on embeddings to establish a shared semantic space for efficient retrieval and generation of information. Embedding in RAG transforms…

  • Close source AI Model

    Closed source models in AI refer to proprietary artificial intelligence systems whose internal workings, codebase, or training data are not publicly accessible. These models…

  • Training Data in LLMs

    Large Language Models (LLMs), such as GPT-3 and GPT-4, have revolutionized the field of natural language processing (NLP) by demonstrating remarkable capabilities in generating…

  • Open source Embedding in AI Systems

    Embeddings have revolutionized the field of artificial intelligence (AI) by providing a robust way to represent high-dimensional data like text, images, and audio in…

  • Pre-Trained AI Models

    Pre-trained models are a cornerstone of modern artificial intelligence (AI), enabling rapid development and deployment of AI solutions across various domains. These models are…

  • Fine tuning AI Models

    Fine-tuning is a pivotal concept in artificial intelligence (AI) that allows pre-trained models to adapt to specific tasks. It involves training an already trained…

  • OpenAI Vision API

    The OpenAI Vision API represents a transformative leap in artificial intelligence, focusing on image processing, computer vision, and multimodal capabilities. This API integrates advanced…

  • Token and Tokenizing in AI Systems

    Tokens and tokenization are foundational concepts in artificial intelligence (AI), especially in natural language processing (NLP). These techniques enable the transformation of unstructured text…

  • DALL-E API

    The DALL-E API, developed by OpenAI, represents a revolutionary step in generative AI, allowing developers to integrate advanced image generation capabilities into their applications.…

  • Prompt engineering

    Prompt engineering is a critical technique in artificial intelligence (AI), particularly in the domain of natural language processing (NLP). It involves crafting input prompts…

  • AI Agents

    Artificial Intelligence (AI) agents are intelligent systems designed to perform tasks, make decisions, and solve problems autonomously. These agents mimic human-like behaviors and cognitive…

  • Inference in AI

    Inference is a crucial component in the field of Artificial Intelligence (AI) that allows models to apply learned knowledge to make predictions, decisions, or…

  • Open Source Models in AI

    OpenOpen source models in AI are freely accessible and available for use, modification, and distribution under specific licenses. These models are built collaboratively by…

  • RAG in AI

    Retrieval-Augmented Generation (RAG) is a powerful technique in natural language processing (NLP) that combines the strengths of both retrieval-based and generation-based models. RAG enhances…

  • Vector Database & AI Model Integration

    In modern AI systems, the integration of vector databases with AI models is a significant advancement that enhances data storage, retrieval, and processing capabilities.…

  • Machine Instructions in Computer Organization and Architecture

    Machine instructions are the fundamental operations that a computer’s central processing unit (CPU) can execute directly. These instructions are part of a computer’s instruction…

  • Medium Access Control (MAC)

    Medium Access Control (MAC) is a sublayer of the Data Link Layer in the OSI model. It plays a critical role in managing how…

  • Virtual Circuit Switching in Computer Networks

    Virtual Circuit Switching (VCS) is a communication method used in packet-switched networks to establish a predefined logical path between source and destination nodes before…

  • Fragmentation in Computer Networks

    Fragmentation in computer networks is a process where large packets of data are divided into smaller pieces to fit the Maximum Transmission Unit (MTU)…