The Quantization Horizon: Navigating the Transition to INT4, FP4, and Sub-2-Bit Architectures in Large Language Models

1. Executive Summary The computational trajectory of Large Language Models (LLMs) has reached a critical inflection point in the 2024-2025 timeframe. For nearly a decade, the industry operated under a Read More …

Neuromorphic–GPU Hybrid Systems for Next-Gen AI

Introduction: The Dichotomy of Modern AI Acceleration The field of artificial intelligence is defined by a fundamental conflict: an insatiable, exponentially growing demand for computational power clashing with the physical Read More …

The New Silicon Triad: A Strategic Analysis of Custom AI Accelerators from Google, AWS, and Groq

Executive Summary The artificial intelligence hardware market is undergoing a strategic fragmentation, moving from the historical dominance of the general-purpose Graphics Processing Unit (GPU) to a new triad of specialized Read More …

The Architectural Arms Race: An In-Depth Analysis of Specialized GPU Hardware for AI Acceleration

The Imperative for Specialization: From General-Purpose GPUs to AI-Centric Accelerators The trajectory of modern artificial intelligence (AI) is inextricably linked to the evolution of the hardware that powers it. For Read More …

Matrix-Centric Computing: An Architectural Deep Dive into Google’s Tensor Processing Unit (TPU)

The Imperative for Domain-Specific Acceleration The landscape of computing has been defined for decades by the relentless progress of general-purpose processors. However, the dawn of the deep learning era in Read More …

The Bandwidth Dichotomy: An Architectural and Economic Analysis of HBM and GDDR Memory Technologies in the Era of AI

Executive Summary This report provides a comprehensive architectural and economic analysis of the two dominant high-performance memory technologies, High Bandwidth Memory (HBM) and Graphics Double Data Rate (GDDR). It frames Read More …