Learn and create, pioneering the AI era.
The article evaluates OpenAI’s o1 series—o1‑preview, o1‑mini and the upcoming full model—by comparing their complex reasoning strength, slower inference speed, higher pricing, API restrictions, and prompting best practices, helping developers decide when to adopt them.
This article walks through how to enable voice-driven coding with GitHub Copilot, VS Code Speech, and Cursor, detailing plugin installation, configuration steps, shortcut keys, and tips for using system or input‑method speech input to create a seamless hands‑free AI coding experience.
The article examines OpenAI’s newly released o1 model, highlighting its superior performance in complex reasoning tasks such as math, programming, and science, and explains how model‑level chain‑of‑thought optimization and product‑level UI design give it an edge over competitors like Claude.
When a new ChatGPT web release triggers a "Oops, an error occurred! (Try again)" message on older browsers, the article explains how the missing Array.prototype.toSorted() method causes the failure and guides readers through creating a Tampermonkey user script that injects a polyfill to restore functionality.
The article evaluates GPT‑4o’s API by comparing its halved pricing, 50% higher token utilization, roughly double inference speed, and new prompt‑sensitivity quirks against GPT‑4‑Turbo and other models, then offers practical tips for integration and troubleshooting.
The article provides a hands‑on review of OpenAI's newly released GPT‑4o model, covering its multimodal capabilities, real‑time voice demo, desktop client rollout, access options for paid and free users, practical usage tips, and early observations on API performance and limitations.
The article evaluates DeepSeek v2, a 100‑billion‑parameter MoE model, highlighting its near‑GPT‑4 benchmark performance, OpenAI‑compatible API, 32k‑token context, exceptionally low pricing, a custom token‑utilization metric, and the practical drawbacks observed during hands‑on testing.
The article explains what the ChatGPT Code Interpreter is, demonstrates three practical use‑cases—document conversion, batch file processing, and fixing math errors—and outlines how to embed it in GPTs while noting its current limitations.
This step‑by‑step guide shows how to claim your free Kimi API credit, create an API key, test the service with Postman, and integrate it via Python SDK, frontend projects, or no‑code tools like Dify, enabling anyone to build AI applications without writing code.
This article addresses frequent Kimi API queries, explains the API's purpose, available endpoints, model specifications, token‑based pricing, differences from the web assistant, response variability, JSON output workarounds, and shares upcoming roadmap items for developers building AI applications.
