Artificial Intelligence & Machine Learning / Specialized AI applications

AI agents are autonomous systems that gather both structured and unstructured data from various sources such as databases, documents, and real-time inputs to build a contextual understanding of tasks. They then use reasoning and decision-making processes, often involving advanced techniques like natural language processing and large language models, to plan and take actions autonomously. This enables them to automate complex tasks by effectively utilizing APIs, databases, and other resources.

The Model Context Protocol (MCP) is a framework designed to standardize and enhance the interaction between AI models and external tools or data sources. It enables continuous and informed context exchanges, allowing AI agents to access relevant, up-to-date information from various systems such as content repositories and business tools. This protocol is crucial for improving the accuracy, adaptability, and coordination of autonomous AI agents in real-world applications.

Narrow (Weak) AI refers to artificial intelligence systems designed and trained for specific tasks, operating within a limited context and unable to perform beyond their predefined capabilities. In contrast, Strong AI (or Artificial General Intelligence) is a theoretical concept that would possess human-level intelligence, self-awareness, and the ability to solve a wide range of problems, but it does not currently exist.

Narrow (Weak) AI is widely used in everyday applications such as virtual assistants (e.g., Siri, Alexa), image recognition software, recommendation algorithms on streaming platforms, and automated closed captioning for videos. These systems excel at specific tasks but lack general understanding or the ability to adapt to new, unrelated challenges.