Getting Started
What is an AI Agent? How can we use them with NEAR?
What we will cover in this workshop today
- What is an AI Agent?
- How LLMs work and how they are used in AI Agents.
- Deploying to NEAR
- Build on NEAR AI challenge
Resources that we will cover in this workshop
BAF+NEAR AI Learning Hub
This is the repo for all the material we will cover in this workshop.
What is an AI Agent?
What is an AI Agent?
Under the hood of LLMs?
How LLMs work and how they are used in AI Agents.
Deploying to NEAR
Deploying to NEAR
Artificial Intelligence (AI) has come a long way. From rule-based systems to machine learning, AI has evolved into a powerful tool for processing information and generating responses. However, despite these advancements, most AI models still function as reactive systems—they respond to inputs but don’t truly act on their own.
This limitation is now being addressed with AI Agents, a new paradigm that introduces autonomy, adaptability, and proactive decision-making. Unlike traditional AI, which waits for commands, AI Agents can plan, execute, and refine tasks independently. They don’t just process information—they act on it.
Imagine an AI that doesn’t just suggest flight options but books your tickets, adjusts schedules in real-time, and handles cancellations automatically. Or an AI system that optimizes logistics, monitors supply chains, and negotiates with suppliers—all without human intervention.
AI Agents are no longer theoretical. They are already transforming industries, taking automation beyond simple data analysis and into real-world decision-making.