AI AGENT & LLM (Syllabus GS Paper 3 – Sci and Tech)
Context: The recently launched GPT-4o by OpenAI and Project Astra by Google have one thing in common: both are capable of processing the real world through audio and visual inputs and provide intelligent responses and assistance.
AI Agent
- About: These are sophisticated AI systems that can engage in real-time, multi-modal (text, image, or voice) interactions with humans.
- Multi-Modal Interaction: Unlike conventional language models, which solely work on text-based inputs and outputs, AI agents can process and respond to a wide variety of inputs including voice, images, and even input from their surroundings.
- Environmental Perception: AI agents perceive their environment via sensors, then process the information using algorithms or AI models, and subsequently, take actions.
- Applications: Currently, they are used in fields such as gaming, robotics, virtual assistants, autonomous vehicles, etc.
Difference Between AI Agent and Large Language Model
- Interaction Capabilities
o LLMs: Only generate human-like text.
o AI Agents: Make interactions more natural and immersive with voice, vision, and environmental sensors.
- Real-time Conversations
o LLMs: Not designed for instantaneous, real-time conversations.
o AI Agents: Provide real-time, human-like responses.
- Contextual Awareness
o LLMs: Lack contextual awareness.
o AI Agents: Understand and learn from the context of interactions for more relevant and personalized responses.
- Autonomy
o LLMs: Do not have autonomy; only generate text output.
o AI Agents: Can perform complex tasks autonomously, such as coding and data analysis.
