Practical AI for solving real problems and creating value
Anthropic’s Claude Sonnet 4.5 arrives with unchanged pricing but claims top‑tier coding performance, superior reasoning and safety scores, a new Agent SDK for long‑running tasks, and an "Imagine with Claude" preview that lets users generate live software, all backed by benchmark comparisons and real‑world case studies.
In this walkthrough I show how, within minutes, I used AI‑driven code search and simple curl commands to locate, enable, and test the newly added API server feature in the open‑source Cherry Studio project, illustrating the power of an AI‑first workflow.
The article analyzes why many workers reject AI adoption, examining technological maturity limits, lack of best‑practice guidance, human‑nature learning barriers, and misaligned incentives, while illustrating points with real‑world examples and personal observations from a podcast discussion.
The article summarizes insights from the GOSIM conference, highlighting AI's disruptive impact on education, the future of work, new human‑AI collaboration models, essential skill sets for engineers, and the urgent need for universities to adapt curricula to the AI era.
This guide shows how to install Cherry Studio, configure multiple AI model providers, and send a single prompt that triggers several models at once, with step‑by‑step screenshots, layout tips, and cost considerations for free and paid services.
At the 2025 Zhejiang "AI+" summit, leading academicians and industry veterans outlined a three‑point roadmap for AI innovation, industry integration, and knowledge dissemination, while highlighting practical challenges, data importance, and the transformative impact of large‑model agents on businesses and society.
After attending the GOSIM HANGZHOU 2025 conference, the author tested four AI-powered real‑time transcription services—Tongyi Qianwen, Tencent Ima Knowledge Base, Alibaba’s Tongyi Tingwu, and iFlytek Listening—detailing their setup, language support, mobile availability, integration with AI, limitations, and recommending a usage priority based on cost, features, and performance.
The author shares a personal journey from traditional Java development to becoming an AI expert, offering concrete observations, tips, and industry insights on how engineers across roles can effectively transition to AI work in today's rapidly evolving tech landscape.
After years of failed attempts with various image‑enhancement tools, I used the Nano Banana model in Google AI Studio, crafted a simple prompt, uploaded my damaged photos, and within minutes achieved surprisingly high‑quality restorations that revived old memories.
A first‑batch tester spends two days with Meituan’s AI assistant XiaoMe, detailing its restaurant recommendation and ordering flow, pinpointing mismatched venue selections, coupon‑saving quirks, unsupported tasks like ride‑hailing, and evaluating the underlying LongCat‑Flash‑Chat model’s speed and personalization.
