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Anysphere's AI programming assistant, Cursor, has successfully raised $900 million, valuing the company at $9.9 billion. This is the third funding round for the company within a single year, demonstrating its astonishing revenue growth rate. Established just three years ago, Anysphere's annualized recurring revenue (ARR) has exceeded $500 million, growing by 60% from the previously reported $300 million in April. It is worth noting that the company's ARR approximately doubles every two months, which has attracted significant attention.

According to the latest data in the Internet Queen's AI Trend Report, the number of AI users, usage volume, and related capital expenditures (CapEx) are showing unprecedented growth. The report emphasizes that this upward trend is not only reflected in the soaring number of AI users and usage volumes, but also strongly supported by related capital expenditures. For example, ChatGPT saw its weekly active user base increase 8 times to reach 800 million in just 17 months. The Internet Queen's AI Trend Report points out that ChatGPT reached 100 million users at a fast pace.

According to a deep analysis of Mary Meeker's latest AI trend report, the world's largest tech companies are investing in AI research and development and capital expenditure on an unprecedented scale and speed. The report points out that over the past two decades, capital expenditures in the technology industry have been continuously increasing, initially for storing and accessing data, then for distributing and scaling, and now mainly focusing on computing and intelligence. This AI trend report highlights that by 2023, AI has evolved from a research function into an important capital expenditure project. The six major U.S. companies...

With the surge in demand for high-quality data from artificial intelligence, efficient web scraping tools have become the core need for AI developers. AIbase learned from social media platforms that Firecrawl has launched a groundbreaking feature - the new /search API, which allows both web search and content scraping with just one API call and outputs data in AI-friendly formats. This release marks an important step forward for Firecrawl in the field of AI-driven web data processing. This article will explore

OpenAI announced significant updates to its image generation API (Responses API), adding new features such as streaming transmission, multi-round editing, and integration with Model Context Protocol (MCP) tools and real-time web data search. These new features not only improve the efficiency of image generation but also provide developers with more flexible creation methods, marking a new stage for AI-driven visual content creation. AIbase has compiled the core highlights of this update and its far-reaching impact on the industry.

Recently, Vidu AI and ComfyUI have launched a new collaboration, bringing creators a new experience from image to video creation. The Vidu API node will be officially launched on ComfyUI soon, enabling easy image-to-video generation and upgrading the creative process again. For creators, mastering new features quickly is crucial. This collaboration provides clear operational guidance: creators first need to update ComfyUI or the ComfyUI desktop version, then log in and purchase corresponding points, next go to the 【Workflow】, view the 【Browse model】

Against the backdrop of the rapid development of the AI agent market, the Alibaba Cloud Qianlian MCP Plaza has officially launched. Meitu Imaging, Yingmi Qianshan, XiaoIce Digital Humans, and more than 40 high-quality MCP services have made their debut, providing users with capabilities to build AI agents across multiple fields such as image editing, financial analysis, digital humans, etc. With the significant enhancement of large model inference capabilities, intelligent application is experiencing explosive growth. Market research institutions such as Markets and Markets and IDC predict the smart agent market will reach hundreds of billions of US dollars.

Mistral recently launched its new Agents API, a framework designed for developers to simplify the creation of AI agents that can execute various tasks such as running Python code, generating images, and performing Retrieval-Augmented Generation (RAG). The launch of this API aims to provide a unified environment for large language models (LLMs) to interact with multiple tools and data sources in a structured and persistent manner.

Mistral AI introduces a new Agents API, aiming to extend language models into intelligent agent systems for enterprise applications. This framework adds tools for task execution, context tracking, and agent orchestration to basic language models, enabling multiple AI agents not only to execute tasks independently but also to collaborate, connect to external systems, and build complete business processes. Each agent can interface with connectors and MCP (Model Context Protocol) tools to support running Python scripts, web searches, etc.