The article details how a three‑layer multimodal AI agent framework—covering AI quality inspection, multimodal content generation, and QA interaction—transforms private‑domain marketing by automating content creation, boosting conversion efficiency, and achieving measurable cost and performance gains.
The author explains how, after ten years of writing, they analyzed their own articles, extracted evolving stylistic patterns, and engineered a modular, reusable writing skill—/phodal-writer/—that can be repeatedly loaded by AI to produce consistently structured, paced, and judgment‑rich content.
This article walks through building a Python pipeline that uses DeepSeek and Alibaba Qwen to generate AI‑written articles, creates cover images, and automatically saves them as drafts in a WeChat public account, with detailed environment setup, client implementations, fallback strategies, and deployment tips.
This guide walks you through building an automated workflow that uses Google’s Antigravity AI to generate a fully formatted WeChat public‑account article—including text, multiple high‑quality images, cloud upload, and markdown‑to‑WeChat conversion—so you can copy‑paste the result directly into the editor.
The open‑source Xiaohongshu MCP (Multi‑Channel Publisher) leverages AI to predict hot topics, auto‑generate copy, titles and tags, monitor performance, analyze competitors, and manage multiple accounts, enabling creators to boost followers from a few hundred to thousands without costly subscriptions, with step‑by‑step deployment instructions and a free GitHub repository.
The open‑source Xiaohongshu MCP (Multi‑Channel Publisher) leverages AI to predict high‑traffic topics, auto‑generate copy, titles and tags, monitor performance, analyze competitors, and manage multiple accounts, enabling creators to boost followers from a few hundred to thousands without costly subscriptions.
The article explores the rise of AI‑generated Guo Degang videos that blend his comedic style with popular games, explains the underlying technologies such as TTS, STT, NLP, and computer‑vision, and discusses the creative, ethical, and societal implications of human‑AI collaboration in content production.
This tutorial walks you through a complete, zero‑code workflow using Tongyi Lingma to import, clean, visualize, and automatically generate a data analysis report—and even create AI‑driven content based on the insights.
This presentation explores the evolution of AI agents in e‑commerce content creation, detailing the transition from text‑only industrial production (1.0) to multimodal image and video generation (2.0) and finally to quality‑driven optimization and decision‑making (3.0), highlighting technical architectures, challenges, and future directions.
The article examines Chrome 133+’s enhanced CSS attr() function, showing how it can dynamically generate content, apply attribute values to dimensions, support typed values and fallbacks, and enable flexible atomic‑style patterns such as tooltips, progress bars, and advanced styling, while also discussing its current limitations and future potential.
Taobao’s AI‑driven content system now generates product guides, videos and multimodal assets across the shopping journey by automatically converting designer mock‑ups into HTML templates, extracting key information, filling slots with product data, and refining layouts via natural‑language feedback, dramatically cutting manual effort and enabling rapid, personalized e‑commerce experiences.
Taobao’s AIGC pipeline combines a human‑feedback multimodal reward model, audio‑visual joint pre‑training, and Mixture‑of‑Experts distillation to clean data, align outputs with user preferences, and achieve state‑of‑the‑art multimodal LLM performance that drives content cold‑start and conversion gains in e‑commerce.
This article demonstrates how to combine DeepSeek's AI‑driven content generation with Kimi's visual design engine to create professional, data‑rich PPTs up to 80% faster, offering reusable prompts, a four‑step workflow, a real‑world case study, and advanced collaboration tips.
This article analyzes Taobao’s AIGC video virtual try‑on pipeline, detailing the challenges of frame‑level realism and continuity, the upgraded DiT‑based model, 3D‑VAE compression, large‑scale data collection, template‑matching mechanisms, and the resulting product capabilities for automated marketing and personalized shopper experiences.
JD Retail’s self‑built AIGC platform ‘JingDianDian’ leverages multimodal diffusion models, ControlNet, RAG and reinforcement learning to automatically generate high‑quality product images, videos and marketing copy, cutting production time from days to seconds, slashing costs by over 99% for more than 350 k merchants.
This article explains what AIGC agents are, outlines their four main characteristics, describes the underlying transformer‑based architecture, dual‑stage learning, probabilistic generation and feedback optimization, and explores their current and future commercial use cases across content creation, knowledge bases, customer service, internal operations, and product design.
In 2024, AI‑generated content transforms fresh‑food e‑commerce by leveraging large language and multimodal models to automatically craft concise product copy, synthesize realistic images and short‑video GIFs, detect and fix visual defects, and build brand‑specific style libraries, paving the way for future voice‑driven storytelling and personalized shopping experiences.
This article explains how Ant Group’s insurance marketing team leverages Artificial Intelligence‑generated content (AIGC) to create personalized marketing materials, automate recommendation workflows, and produce video scripts, thereby improving efficiency, compliance, and user engagement in the insurance sector.
AIGC, or AI‑generated content, spans text, image, audio and video creation, evolving from early experiments to rapid growth marked by breakthroughs like ChatGPT and GPT‑3/4, with large models providing the technical foundation, while addressing technical hurdles, ethical concerns, and future application trends worldwide.
This article examines the technical challenges of traditional e‑commerce live streaming, presents a 24‑hour AI‑driven virtual live‑broadcast system built by Yanxuan and NetEase Fuxi, and details its architecture, virtual‑human generation, automated content creation, intelligent interaction, and future expansion plans.
This talk explores how multimodal AI, knowledge‑graph‑enhanced script generation, and advanced reading‑comprehension techniques enable virtual anchors to transform e‑commerce live streaming from simple Q&A bots into interactive, content‑rich live broadcasts, addressing challenges of material sourcing, personalization, and low‑latency response.
The article reviews the rise of AI‑driven intelligent writing robots, outlines industry use cases, explains two main generation methods, and details how 58.com leverages massive structured data to automatically produce narrative, emotion‑rich listings for vehicles, housing, and jobs, enhancing user engagement.
The article explains how Alibaba's 1688 B2B platform uses AI‑driven supply‑demand matching, intelligent assistants, and automated content generation to streamline massive product operations, improve market analysis, and boost conversion rates, illustrating the underlying data‑driven models and workflow architecture.
