By combining MCP and A2A, we can obtain multi-agent applications that coordinate AI agents to access data and tools and communicate with each other, facilitating the efficient and dynamic execution of complex tasks.
The emergence of technologies such as Artificial Intelligence and Generative AI in education presents a unique opportunity to improve the learning process for students and optimise teachers' time.
What is the difference between AI Agents and AgenticAI? To answer this question, we must first understand what Large Language Models (LLMs) are and what Retrieval Augmented Generation (RAG) is.
By combining Property Graphs and Knowledge Graphs, we can obtain richer and more connected data models to overcome the limitations of the relational model, facilitating logical inference, exploration of complex relationships, and support for generative AI systems.
By combining Knowledge Graphs with generative AI, we can obtain formal ontologies capable of transforming information into reliable knowledge, facilitating validation with experts and reducing AI hallucinations in multiple areas of business.
