OpenAI Releases a Technical Playbook for Enterprise AI Integration [English]

OpenAI’s new report, “AI in the Enterprise,” outlines seven key lessons for effective AI integration in organizations. It emphasizes structured evaluation, embedding AI in core products, and empowering employees to develop custom applications, showcasing how disciplined experimentation and robust tooling can drive successful enterprise AI adoption.

Model Context Protocol (MCP) vs Function Calling: A Deep Dive into AI Integration Architectures [English]

The blog post explores the Model Context Protocol (MCP) and Function Calling, two methods for integrating Large Language Models (LLMs) with external systems. It highlights their architectural differences, use cases, and security features, emphasizing MCP’s robustness for complex integrations and Function Calling’s flexibility for dynamic task execution.

SKT, establishing a network AI foundation through the commercial network demonstration of next-generation virtualized base stations [Korean]

SK Telecom has successfully demonstrated next-generation virtual base stations in collaboration with global manufacturers like Samsung, Ericsson, and Nokia. This innovation enhances service quality, capacity, and energy efficiency, marking a significant advancement in network AI technology. SK Telecom aims to lead future network developments through ongoing research and global partnerships.

OpenAI’s new GPT-4.1 models can process a million tokens and solve coding problems better than ever. [English]

OpenAI has launched its new GPT-4.1 models, which can process up to one million tokens and significantly enhance coding capabilities while reducing costs. The models, designed for enterprise applications, offer improved instruction following and performance, making them a practical choice for businesses integrating AI into their operations.

Revolutionizing Databases: The Quantum Leap in Query Processing [English]

Quantum computing is revolutionizing database technology by enabling faster query processing through principles like superposition and entanglement. This advancement enhances efficiency in pattern matching, graph traversal, and data storage, paving the way for innovative applications in fields such as genomics, finance, and network analysis, despite existing scalability challenges.

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