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Anthropic, an American startup focused on generative artificial intelligence, recently announced the launch of a new feature called "Artifacts," which allows users to create personalized applications. Users can create by means of simple conversations without any programming knowledge. This feature's release marks an important step for Anthropic in the field of artificial intelligence application development. The Artifacts feature was initially launched last June and became available to all users in August. Users can access it next to the conversation window.

Artificial intelligence company Anthropic has announced a major new feature for its Claude chatbot, allowing users to build AI-powered applications directly within the app. This feature is a comprehensive upgrade based on the Artifacts function launched last year and is now officially available. Conversation as Development, the Barriers to Programming Are Gone Completely. In their official blog, Anthropic stated: By enabling this new interactive feature, users can start building their own applications within the Claude app. Just simply describe what you want to create inside

Recently, Volc Engine officially announced the launch of the enterprise AI mid-platform HiAgent 2.0, aiming to address real-world business needs and pain points in the development of Agent applications, helping enterprises achieve efficient delivery of intelligent bodies from development to operations. HiAgent 2.0 is positioned as an enterprise AI mid-platform, and compared to its predecessor HiAgent 1.0, it has expanded in four dimensions of functionality. Upwardly, HiAgent 2.0 provides more industry scenario templates and a rich plugin market, significantly lowering the barrier to building intelligent bodies; towards

Based on the Harmony Intelligent Body, the interaction mode between consumers and the Harmony system and applications will undergo a fundamental transformation. The Harmony Intelligent Body features system-level security, trustworthiness, and personalized controllability. It can achieve efficient collaboration among multiple intelligent bodies and natural transitions between multiple devices, thereby truly transforming the interaction mode from the traditional instruction-centered model to an intention-centered model.

On June 18th, the artificial intelligence research institute OpenAI officially open-sourced its customer service agent framework, marking an important step in the company's layout of enterprise-level AI solutions. This framework aims to promote the practical commercial application of intelligent agent systems from laboratory environments to real-world scenarios by providing transparent toolchains and clear implementation examples.

Artificial intelligence research company Anthropic recently announced its latest progress in explainable AI (Interpretable AI) technology, which aims to make the decision-making process of large language models more transparent. This breakthrough may have a profound impact on how enterprises formulate strategies for applying large language models. The core technology breakthrough developed by Anthropic allows researchers to understand the model's thinking process and trace the underlying logic leading to specific conclusions.

An artificial intelligence research company, Anthropic, is developing AI systems with 'explainability' that enables users to understand the decision-making processes of large language models (LLMs). This breakthrough research may have a profound impact on enterprises' strategies for applying large language models. Breakthrough Technology: Peering into the AI 'Black Box' Anthropic's research focuses on solving the 'black box' problem of current generative AI systems.

OpenAI Reaches Significant Cooperation with the Pentagon. OpenAI has recently received a contract worth $200 million from the U.S. Department of Defense, marking a major breakthrough in the collaboration between this leading artificial intelligence company and a government agency. According to the agreement, during a one-year pilot project, OpenAI will assist the U.S. Department of Defense in exploring the applications of artificial intelligence in administrative management and security tasks.

Learn how AICosts.ai helps businesses manage the costs of AI services like ChatGPT and Claude, addressing core issues such as fragmented billing management across multiple platforms, cost anomaly monitoring, and cross-platform optimization.

In-depth analysis of this revolutionary AI hardware design tool, Enzzo PM, unveiling how its two core modules, TORQUE and AMPLIFY, shorten tasks like generating product requirement documents and competitor analysis from weeks to mere hours. The article also features practical test cases and business value assessments. It is especially suitable for hardware development teams, start-ups, and manufacturers.

This comprehensive review of the Solar AI development tool examines how it generates complete applications via natural language input, reducing 83% of development time. Explore Solar's core features, use cases, and comparisons with mainstream tools to determine if it can truly deliver on its 'light-speed development' promise.

A comprehensive analysis of MCP Stack's open-source marketing cloud platform functions, detailing its technical advantages in multi-channel integration, AI automated marketing, real-time data analysis, and providing implementation suggestions for enterprise-level marketing automation solutions.

Recently, an open-source RAG (Retrieval-Augmented Generation) engine called RAGFlow has attracted significant attention in the industry. This enterprise-level AI tool, based on deep document understanding, provides companies with a brand-new solution for processing complex documents and achieving precise question answering through its powerful multimodal data processing capabilities and efficient workflows. RAGFlow: The Pioneer of Deep Document Understanding RAGFlow is a fully open-source RAG engine that focuses on deep document understanding, aiming to help businesses and individuals extract valuable information from massive amounts of unstructured data.

According to the latest prediction from Gartner, by 2028, 80% of generative AI business applications will be developed on existing data management platforms. This shift is expected to reduce development complexity and cut delivery time in half. Currently, the development of generative AI business applications mainly relies on combining large language models (LLMs) with corporate internal data, as well as evolving technologies such as vector search, metadata management, prompt design, and embedding techniques. However, without a unified management approach, companies may...

Recently, researchers at the University of Tokyo found that the application of artificial intelligence (AI) tools in taxi drivers, especially for those with lower skills, helps improve their work efficiency. This study revealed a surprising trend: AI can not only help high-skilled workers but, in some cases, can significantly enhance the performance of low-skilled workers and narrow the skill gap. Image source notes: The image was generated by AI, and the image authorization service provider is Midjourney. The research team focused on taxi drivers in Yokohama City, Japan, analyzing...