5 levels of AI agents: From basic to superintelligence

The 5 levels of AI agents model clearly outlines their crucial progression in our evolving digital landscape. These agents are transforming how we interact with technology and tackle complex challenges, evolving from simple rule-based automation to sophisticated, autonomous entities with remarkable intellectual capacity. This journey showcases their development from basic tools to near-superintelligence, marking significant AI advancement.

Level 0: No AI – Tools and Rules

This is the most fundamental level, where systems operate entirely based on tools and rules pre-programmed by humans.

• Techniques: Tools (Intent + Rules + Actions)
• Performance: No AI
• Capabilities: No AI
• Key Characteristics: No AI (Operates on rigid, pre-programmed commands and rules, with no ability to learn or adapt).
• Use Cases: No AI
• Narrow Domain: Narrow Non-AI UI Driven Software.
• General Wide-Range Domain: General Non-AI Human-In-The-Loop Computing, Mechanical Turk.

At this level, the “intelligence” lies entirely with the human designer and user. The system merely executes predefined instructions.

Level 1: Rule-Based AI – Simple Automation

This level marks the emergence of AI, albeit in its most nascent form, based on predefined rules.

• Techniques: Rule-Based AI + Tools (Intent + Actions)
• Performance: Emerging – Equal to Unskilled Humans.
• Capabilities: Simple Step Sequence.
• Key Characteristics: Agents complete tasks following exact steps, pre-defined by users or developers.
• Use Cases: User: “Open Messenger,” User: “Open the first unread email in my mailbox and read its content,” User: “Call Alice.”
• Narrow Domain: Emerging Narrow-AI Single Rule-based systems, SHRDLU, GOFAI.
• General Wide-Range Domain: Emerging AGI ChatGPT, Gemini, Llama 2, etc. (considered emerging at the AGI level for basic applications).
  Despite having an AI element, these agents are still limited in their ability to adapt and understand complex contexts.

Level 2: IL/RL-based AI – Competent Automation

AI agents at this level begin to demonstrate basic learning and decision-making capabilities.

• Techniques: IL/RL-based AI + Tools (Intent + Actions) + Reasoning & Decision Making.
• Performance: Competent – Equal to 50% of Skilled Adults.
• Capabilities: Deterministic Task Automation of Skilled Adults.
• Key Characteristics: Based on user description of deterministic task, agent auto-completes steps in predefined action.
• Use Cases: User: “Check the weather in Beijing today.”
• Narrow Domain: Competent Narrow-AI Conversational AI build frameworks with LLM, RAG, etc.
• General Wide-Range Domain: Competent AGI – Not yet achieved.

Here, AI can understand slightly more complex requests and autonomously perform the necessary steps, but still within a defined framework.

Level 3: LLM-based AI – Strategic Automation

This is where Large Language Models (LLMs) truly shine, offering greater autonomy and planning capabilities.

• Techniques: LLM-based AI + Tools (Intent + Actions) + Reasoning & Decision Making + Memory & Reflection.
• Performance: Expert – Equal to 90% of Skilled Adults.
• Capabilities: Strategic task Automation.
• Key Characteristics: Using user-defined tasks, agents autonomously plan, execution steps using tools, iterates based on intermediate feedback until completion.
• Use Cases: Agents autonomously plan and execute steps based on intermediate feedback.
• Narrow Domain: Expert Narrow-AI Purpose build, specific task orientated Agents.
• General Wide-Range Domain: Expert AGI – Not yet achieved.

The ability to remember, learn from feedback, and self-correct helps AI agents at level 3 perform complex and strategic tasks. Understanding the 5 levels of AI agents highlights the significant progress at this stage.

Level 4: Advanced LLM-based AI – Contextual Awareness and Proactivity

AI at this level not only executes but also deeply understands and proactively assists users.

• Techniques: LLM-based AI + Tools (Intent + Actions + Reasoning & Decision Making + Memory & Reflection + Autonomous Learning + Generalisation).
• Performance: Virtuoso – Equal to 99% of Skilled Adults.
• Capabilities: Memory & Context Awareness.
• Key Characteristics: Agent senses user context, understands user memory, and proactively provides personalised services at times.
• Use Cases: A personalised virtual assistant enhances UX by understanding context & memory while acting proactively.
• Narrow Domain: Virtuoso Narrow-AI AlphaGo, Deep Blue.
• General Wide-Range Domain: Virtuoso AGI – Not yet achieved.

Autonomy, generalization capabilities, and contextual awareness transform AI into a truly intelligent partner.

Level 5: Transcendent LLM-based AI – True Digital Persona

This is the pinnacle of AI agent development, where machines can surpass human capabilities.

• Techniques: LLM-based AI + Tools (Intent + Actions + Reasoning & Decision Making + Memory + Reflection + Autonomous Learning + Generalisation + Personality (Emotion + Character) + Collaborative behaviour (Multi-Agents)).
• Performance: Superhuman – > 100% of Skilled Adults.
• Capabilities: True Digital Persona.
• Key Characteristics: Agent represents the user in completing affairs, interacts on behalf of user with others, ensuring safety & reliability.
• Use Cases: Agent acts on behalf of user to complete tasks, interacting with others while ensuring safety & reliability.
• Narrow Domain: Superhuman Narrow-AI AlphaFold, AlphaZero, StockFish.
• General Wide-Range Domain: Artificial Super Intelligence (ASI) – Not yet achieved.

At level 5, AI is not only intelligent but may also possess “personality” and high-level collaborative abilities, approaching the concept of Artificial Super Intelligence (ASI).

The 5 levels of AI agents framework illuminates AI’s path to advanced capabilities. Grasping this progression is essential for anticipating AI’s future impact. Follow The Best Crypto TradingBot for the latest insights as we explore developments across these crucial 5 levels of AI agents.