OpenAI has moved from a limited ad test in February to a full‑scale ChatGPT Ads platform after the GPT‑5.5 Instant release, detailing how it infers user interest through memory, separates ad slots from answers, sets premium pricing, and balances free‑user controls with privacy safeguards.
The article evaluates twelve legitimate, free methods for accessing overseas large language models from within China in 2026, categorizing options that require direct domestic connectivity, domestic alternatives, and international platforms with free tiers, and provides usage examples, free quotas, suitable scenarios, and step‑by‑step setup instructions.
In the past six months the humanoid robot industry has moved beyond mere mobility, with dozens of companies deploying robots continuously in factories, warehouses, retail and homes, yet production pace, scenario choices and technical paths still leave several engineering bottlenecks before large‑scale delivery can be achieved.
The article analyzes how AI is now writing code, compressing development cycles from half a day to minutes, reshaping programmer roles through three historical value shifts, highlighting new AI‑centric responsibilities, and offering a concrete learning path for Java developers to thrive in the AI era.
This article provides a multi‑dimensional strategic analysis of three representative AI‑focused platforms—Dify, n8n, and ComfyUI—examining their product positioning, architecture, interaction models, commercialization strategies, and agent capabilities, and offers concrete recommendations for product managers on choosing the right tool based on ease of use, control, scalability, and total cost of ownership.
Dify’s rapid rise—over 1,000 contributors, 120K GitHub stars, 5M downloads, and adoption by more than 40 Fortune‑500 firms—illustrates how an open‑source AI middleware can turn technical parity into a global product advantage, while the founder’s startup lessons reveal the strategic choices behind its success.
This article compares four leading AI agent development platforms—Coze, Dify, Tencent Yuanqi, and Baidu Wenxin—detailing their strengths, weaknesses, and ideal use cases to help developers and businesses choose the most suitable solution for chatbots, data assistants, or social‑media automation.
Developers can stay current with recent AI advancements as Anthropic introduces Claude’s educational mode, Amazon launches the Nova model hub and Act SDK, Solo.io unveils the MCP Gateway for AI tool integration, Kong updates its AI Gateway to curb hallucinations, env0 releases Cloud Analyst, CodeSignal adds AI skill assessments, and Zencoder offers new AI coding and testing agents.
This article proposes a quantitative model that breaks AI usage effectiveness into three multiplicative factors—professional ability, prompt engineering skills, and AI platform capabilities—detailing each component, offering a prompt framework (BROKE), and providing tailored recommendations for beginners, competitors, and applied learners.
This article chronicles the author's three‑year journey as an AI product manager at JD.com, detailing the decision to enter the AI field, key project experiences such as platform integration and edge‑intelligence, a three‑stage growth roadmap, essential capabilities across four quadrants, and a forward‑looking view of AI's industry impact.
A recent test on Google Vertex AI showed Gemini‑Pro introducing itself as Baidu’s Wenxin model during Chinese conversations, sparking debate about model attribution, pricing, developer tools, and the broader competition among major AI platforms.
In this interview, Zuoyebang’s NLP lead explains how the company built self‑developed platforms like IQC and FTP to automate text quality inspection and intelligent labeling, outlines their architecture, shares practical deep‑learning applications such as translation and grammar correction, and discusses future research directions in large‑scale multi‑label classification, few‑shot learning, and multimodal models.
The article examines three key design dimensions of modern AI platforms—choice of programming language, runtime environment isolation, and model deployment—highlighting how Python’s dominance, container‑based resource management, and efficient data sharing shape platform architecture and performance.
This article shares seven actionable insights—from demand management and platform design to verification, collaboration, branding, and growth challenges—drawn from Ant Group’s experience building AI‑driven platforms, illustrating how product managers can turn abstract methods into concrete, user‑centric solutions.
Jia Yangqing’s talk from the Alibaba CIO Academy explains what artificial intelligence is, its applications, the challenges of perception and decision making, the evolution of deep‑learning models, the need for massive compute power, and how enterprises can strategically adopt AI and big‑data technologies to drive innovation.
In this interview, Long Mingkang, Vice President of iFlytek's Cloud Computing Institute, shares his experience building large‑scale speech cloud services, discusses the technical hurdles of speech recognition and AI platform development, compares TensorFlow and MXNet, and offers insights on AutoML, industry trends, and how engineers can master AI.
