Baidu Tech Salon, organized by Baidu's Technology Management Department, is a monthly offline event that shares cutting‑edge tech trends from Baidu and the industry, providing a free platform for mid‑to‑senior engineers to exchange ideas.
This article traces Baidu Search’s 20‑year evolution, outlines its six generational shifts, explains the AI‑native reconstruction of the product, details the diverse product lines and rigorous evaluation framework, and maps the career growth path and skill expectations for search product managers.
The article surveys Baidu Search’s intelligent question‑answering system, tracing its evolution from feature‑engineered retrieval to large pre‑trained and generative models, and detailing hierarchical readers, multi‑teacher distillation, retrieval‑enhanced generation, and instruction decomposition as key techniques for delivering fast, accurate, citation‑rich answers.
Baidu’s upcoming technical salon series on search will showcase its open‑source ANN retrieval framework Puck—demonstrating superior performance on massive benchmarks—and feature nightly live sessions covering product management, GPU optimization, intelligent Q&A, model architecture, and image generation, with registration via QR‑code.
In a live session, NVIDIA senior deep‑learning solutions architect Zhai Jian demonstrates how to use Nsight Systems and Nsight Compute to analyze a simple neural‑network training workload, accelerate BERT with mixed precision, and examine matrix‑transpose kernels, with registration via QR code and a detailed event schedule.
This article explains the technical workflow behind Baidu App’s AI‑assisted text generation, covering large‑language‑model fundamentals, three‑layer system architecture, prompt design, risk‑control measures, SSE streaming, and a custom Android TextView implementation for smooth, gradient‑styled output.
Urban graphs often exhibit spatial heterophily, where neighboring nodes differ significantly, limiting traditional GNNs; this article introduces a Spatial Heterophily Aware GNN (SHGNN) that partitions neighborhoods by geographic proximity, employs rotation‑scaling aggregation and heterophily‑sensitive interaction, and demonstrates superior performance on three real city datasets.
Baidu’s Wenxin Yiyan, a knowledge‑enhanced large language model now at version 3.5, outperforms ChatGPT, showcases rapid training and inference, and is being deployed across transportation, agriculture, energy and other sectors, illustrating AI’s transition to industrial mass production and its strategic boost for China’s high‑quality economic growth.
A Tsinghua University evaluation of seven large language models found Baidu’s Wenxin Yiyan topping the domestic rankings with the highest overall score across 20 metrics—especially Chinese semantic understanding and safety—surpassing ChatGPT and tying GPT‑4, while also demonstrating rapid training, inference speed, and broad industry adoption.
IDC’s 2023 AI Large Model Technology Capability Assessment names Baidu’s Wenxin (ERNIE) series as the overall leader, earning seven full scores across twelve dimensions—including the sole perfect score for algorithm model—thanks to its four‑layer stack, knowledge‑enhanced core, PaddlePaddle platform, and extensive industry deployments with over 150,000 enterprises.
The article details how Android developers can protect APK dex files by progressively hardening code—using dynamic loading, hooking, instruction extraction, java‑to‑C++ conversion, and ultimately DEX‑VMP virtual machine encryption—while outlining implementation steps, custom opcodes, JNI integration, and addressing compatibility and performance trade‑offs.
