Category: AI & 机器学习 (AI & Machine Learning)

> **Core Executive Summary**: Single GPU VRAM cannot host 100B+ LLM training parameters, gradients, and optimizer states (a 70B FP16 model requires 1.12TB train

> **Summary**: Computer vision architectures evolved from handcrafted local inductive biases (CNNs) to data-driven global self-attention (ViT). This 100% exhaus

> **Core Executive Summary**: LLMs often generate plausible-sounding but unfactual or logically contradictory text, known as **Hallucination**. Hallucinations r

> **Core Executive Summary**: Since its introduction in 2017, the Transformer architecture has fundamentally reshaped artificial intelligence, serving as the un

> **Core Executive Summary**: Linear algebra is the substrate of machine learning and deep learning: every tensor is a matrix, every layer is a matrix multiplic

> **Core Executive Summary**: Vision-Language Models (VLMs) empower LLMs to perceive visual scenes. Rather than training multimodal models from scratch, VLMs ut

> **Core Executive Summary**: Moving RAG knowledge bases and agentic systems from demo to enterprise production is a distributed-systems problem as much as an M