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Category: llm

  • Energy Costs of Using LLMs within Enterprise

    Energy Costs of Using LLMs within Enterprise The energy costs of using Large Language Models (LLMs) within an enterprise are a multifaceted issue with implications for both operational expenses and environmental sustainability. These costs arise primarily from two key stages in the LLM lifecycle: training and inference. Factors Influencing Energy Consumption Model Size: The number Read more

  • AMD vs. NVIDIA LLM Performance

    AMD vs. NVIDIA LLM Performance (May 2025) This article compares the performance of AMD and NVIDIA hardware when running Large Language Models (LLMs) as of May 2025, based on recent reports and trends. Key Factors Influencing LLM Performance VRAM (Video RAM) The size of the GPU’s memory is crucial for handling large LLMs. Larger models Read more

  • Top 5 Code Generation Models (May 5, 2025)

    Top 5 Code Generation LLMs (May 5, 2025) The landscape of Large Language Models for code generation is dynamic. This list highlights five prominent models based on their performance, features, and recognition as of today. 1. GPT-4o Provider: OpenAI Key Details: Often cited as a leader in overall LLM benchmarks, including code generation. Known for Read more

  • Using local LLM for Document Extraction

    Non-Cloud LLM for Document Extraction This guide explains how to use a non-cloud version of a pretrained Large Language Model (LLM) for document extraction, focusing on open-source models and local execution. Phase 1: Setting Up Your Local Environment 1. Hardware Requirements Ensure your system meets the following recommendations: CPU/GPU: An NVIDIA GPU with sufficient VRAM Read more

  • CUDA vs. ROCm for LLM Training

    CUDA vs. ROCm CUDA (Compute Unified Device Architecture) and ROCm (Radeon Open Compute) are the two primary software platforms for General-Purpose computing on Graphics Processing Units (GPGPU) used in accelerating computationally intensive tasks, including the training of Large Language Models (LLMs). CUDA is developed by NVIDIA and is designed for their GPUs, while ROCm is Read more

  • Exploring CUDA (Compute Unified Device Architecture)

    Exploring CUDA CUDA is a parallel computing platform and programming model developed by NVIDIA for use with their GPUs. It allows software developers to leverage the massive parallel processing power of NVIDIA GPUs for general-purpose computing tasks, significantly accelerating applications beyond traditional CPU-bound processing. 1. CUDA Architecture: The Hardware Foundation NVIDIA GPUs are designed with Read more

  • AMD GPUs vs. NVIDIA GPUs for LLM Training

    AMD GPUs vs. NVIDIA GPUs for LLM Training Here we dive into how AMD GPUs can be used for LLM training, and compare them directly with the dominant player in this field: NVIDIA GPUs. Comparison: AMD vs. NVIDIA GPUs for LLM Training Feature NVIDIA GPUs AMD GPUs Dominant Architecture/Platform CUDA (Compute Unified Device Architecture) – Read more

  • Vector Embeddings in LLMs: A Detailed Explanation

    Vector Embeddings in LLMs: A Detailed Explanation What are Vector Embeddings? Vector embeddings are numerical representations of data points, such as words, phrases, sentences, or even entire documents. These representations exist as vectors in a high-dimensional space. The key idea behind vector embeddings is to capture the semantic meaning and relationships between these data points, Read more

  • How GPU Architecture revolutionized LLMs

    How GPU Architecture Helped LLMs The development and advancement of Large Language Models (LLMs) have been significantly propelled by the unique architecture of Graphics Processing Units (GPUs). Their parallel processing capabilities, high memory bandwidth, and specialized compute units have made training and deploying these massive models feasible and efficient. 1. Massively Parallel Processing LLMs involve Read more

  • Salesforce Agentic AI: A Comprehensive Overview

    Salesforce Agentic AI: A Comprehensive Overview Salesforce Agentic AI represents a significant evolution in how artificial intelligence is integrated into the Salesforce platform. Moving beyond simple automation and predictive analytics, Agentic AI aims to create intelligent, autonomous agents capable of understanding complex goals, planning multi-step actions, and executing tasks on behalf of users. This detailed Read more