Official account of Tencent Technology. A platform for publishing and analyzing Tencent's technological innovations and cutting-edge developments.
The article gathers diverse opinions from eight engineers on whether systematic book study remains essential for programmers in the AI age, arguing that combining foundational reading with AI‑assisted practice builds deeper understanding while pure reliance on AI or rote reading alone falls short.
This article walks through the complete process of creating a WeChat mini‑program that uses large‑language‑model chat to recommend personalized fragrances, covering idea generation, tool selection, prompt design, AI‑assisted debugging, UI/UX refinement, mini‑store integration, and final publishing steps.
This article explores the evolution of AI infrastructure, comparing it with traditional backend systems, and details how hardware shifts to GPU-centric designs, software adaptations like deep learning frameworks, and engineering challenges in model training and inference can be addressed using established backend methodologies.
The A.S.E (AI Code Generation Security Evaluation) framework provides a comprehensive, project‑level benchmark for assessing the safety, quality, and stability of AI‑generated code across multiple languages and vulnerability types, helping developers and researchers evaluate and improve large language model coding assistants.
A collection of engineers' perspectives discusses Go's strengths, challenges, and future prospects over the next five to ten years, highlighting its role in cloud‑native infrastructure, AI limitations, industry adoption, and the importance of continuous learning for developers.
This article provides a concise overview of the latest AI concepts—including AIGC, Retrieval‑Augmented Generation, Function‑Calling models, intelligent agents, and the Model Context Protocol—explaining their principles, differences, and how they can be combined to build more powerful AI applications for developers outside the AI field.
This article details the Angel‑HCF team's end‑to‑end DeepSeek inference optimizations—including PD separation, multi‑layer MTP, EP and DP parallelism, hardware‑aware kernels, and load‑balancing strategies—that boost throughput to over 15,800 tokens per second while keeping per‑token latency under 50 ms.
This article explains how modern GPUs evolved from graphics rendering to general‑purpose computing, details the CPU‑GPU heterogenous architecture, walks through a CUDA demo that adds two billion‑element arrays, compares CPU and GPU performance, and describes the compilation, loading, and execution pipeline of CUDA kernels.
Tencent’s TEG team secured first place in the NTIRE 2025 UGC Video Enhancement competition by introducing a progressive, three‑stage AI framework that decomposes enhancement tasks into expert models for color correction, denoising, and temporal stability, incorporates advanced loss functions, extensive hardware‑level optimizations, INT8 quantization techniques, and outlines future diffusion‑based generative enhancements.
This article details how the Wukong AI Agent automatically audited the popular LLaMA‑Factory project, discovered a high‑severity remote code execution vulnerability (CVE‑2025‑53002) caused by unsafe torch.load usage, reported it to the maintainers, and demonstrated the official fix that adds a secure weights_only flag.
