The Model Context Protocol (MCP) is an open standard that enables AI systems to connect seamlessly with various data sources and tools. By acting as a universal connector, MCP allows AI models to access real-time information, perform specific tasks, and integrate smoothly with existing systems without the need for custom integrations for each new tool.

Teccelerates collaboration with CCG and HKSTP as one of the tech ventures involved in harnessing the power of Generative AI. Together, we have developed cutting-edge HR Hiring AI and Marketing Generator AI solutions that prioritize operational efficiency.

As Microsoft AzureAI MVP and AI solutions consultant, I often discuss with clients how to optimize the use of Azure OpenAI Service. Azure OpenAI Service offers flexible pricing options - the Standard (On-Demand) tier, the Provisioned Throughput Unit (PTU) tier, and the Global Batch Processing tier. These billing models each have their own focus and can meet the diverse needs of different customers. Let me share some real-world cases to help you choose the most suitable model.

As large language models (LLMs) become increasingly integral across various industries, selecting the appropriate deployment model is a crucial decision.

Selecting the ideal foundation model (FM) is a critical decision that can significantly influence the success of your artificial intelligence (AI) projects. With the plethora of options available, it’s essential to weigh various factors to ensure that your chosen FM aligns with your specific needs. Here’s a quick guide to help you navigate this decision-making process: