DL

Demystifying Agentic Search Engines

Agentic search engines—such as Google AI Mode, Perplexity, Bing Copilot, ChatGPT Search no longer means “type keywords, get ten blue links.” AI Search experience capable of understanding tasks, planning queries, calling tools, and synthesizing results and deliver a conversational response with inline citations, minimizing user effort. In this post, I’ll walk through the stack from bottom to top, how it crawls and indexes pages, how it retrieves and ranks information, and how recent features like RAG and Agentic search build upon these foundations.

各领域的深度学习模型

本文简要总结了深度学习在NLP、计算机视觉、信息检索和推荐系统四大主流领域的演进脉络：从早期RNN、CNN等专用模型，到Transformer全面主导，再到如今BERT/GPT、ViT、Diffusion等预训练大模型横扫各领域。核心趋势是预训练+生成式范式取代传统任务特定模型，统一建模与生成式架构正在加速推动各领域融合与新一轮创新。

模型训练的方法与实践

深度学习模型架构的演进

本文系统回顾了深度学习的发展脉络，从基础神经网络到Attention 与 Transformer的出现，再到深度生成模型的兴起，最后介绍了多模态与统一建模架构的发展趋势，展示了当前主流的模型体系。