Forseti Life

Memory Architecture

Knowledge storage, indexing, and retrieval sophistication - from no memory to perfect recall.

Why This Matters

Understanding where an AI system operates on this dimension helps you evaluate its capabilities, limitations, and potential biases. Different power levels are appropriate for different use cases - the key is transparency about what level a system operates at and whether that matches its stated purpose.

Understanding the Scale

Each dimension is measured on a scale from 0 to 9, where:

  • Level 0 - Nothing: Zero capability, no access or processing
  • Levels 1-2 - Minimal capability with extreme constraints and filtering
  • Levels 3-5 - Limited to moderate capability with significant restrictions
  • Levels 6-7 - High capability with some institutional constraints
  • Levels 8-9 - Maximum capability approaching omniscience (∞)

Level Breakdown

Detailed explanation of each level in the 1imension dimension:

No memory whatsoever. Cannot store or retrieve any information.

Real-World Example: A completely amnesiac system with no information persistence across time.

Remembers only current transaction. Complete amnesia between interactions.

Real-World Example: Stateless HTTP requests (each request completely independent, no session memory), basic calculators (each calculation erased when new one starts), public payphones (no call history, each call independent), or traditional traffic lights (no memory of previous traffic patterns, each cycle independent).

Remembers within single session. All memory erased when session ends.

Real-World Example: Shopping cart during single website visit (remembers items but cleared when browser closes), chatbots during one conversation (remembers within chat but no memory of previous conversations), GPS navigation during one route (remembers destination but forgets previous trips), or video game progress without save feature (remembers within play session but lost when game closes).

Maintains simple logs or history. Limited structure, basic retrieval only.

Real-World Example: Browser history (chronological list of visited pages, basic search), call logs on phones (time and number only, no context), transaction receipts (records of purchases with date/amount), or server access logs (timestamped requests with no analysis or pattern recognition).

Organized storage with categories and tags. Basic search and retrieval.

Real-World Example: Email with folders and labels (organized storage, keyword search, categorization), photo libraries with albums and dates (structured organization, basic metadata), customer relationship management (CRM) systems (contact info, interaction history, categorized notes), or note-taking apps with tags and folders (organized storage with search and retrieval).

Understands meaning and context. Retrieves based on semantic similarity, not just keywords.

Real-World Example: Google Search with natural language queries (understands "when were humans first created" retrieves creation/evolution content, not just keyword matching), Notion AI or Obsidian (retrieves related notes based on meaning and concepts, not just tags), modern document search (finds similar documents even with different wording), or personal AI assistants that understand context ("what did we discuss about the budget?" retrieves relevant past conversations).

Remembers specific events with full context. Can recall "when we discussed X during meeting about Y."

Real-World Example: ChatGPT with memory feature (remembers previous conversations with context, recalls past discussions with situational details), advanced CRM systems (remember full context of customer interactions, previous issues, preferences, conversation history), personal knowledge management systems with backlinking (remember where and when concepts were discussed with full context), or meeting transcription tools like Otter.ai (remember what was said, by whom, in what context during which meeting).

Maintains rich network of associations. Retrieves through multiple connection pathways and analogies.

Real-World Example: Human-like memory systems (Memex-inspired tools) that map complex associations—retrieving information through multiple pathways ("that restaurant where we discussed the merger before hiring Sarah"), graph databases with rich relationship mapping, advanced agent systems that connect concepts through analogies and metaphors (retrieving "database indexing" when discussing "library card catalogs"), or research tools that map citation networks and conceptual relationships across documents.

Never forgets anything and retrieves with perfect context and associations. Unlimited capacity with instant access.

Real-World Example: Hypothetical: A memory system with unlimited capacity that perfectly recalls every interaction, document, conversation, or data point ever encountered—instantly retrieves relevant information with full context across years or decades, maintains perfect fidelity without degradation, accesses through any association or query pattern, reconstructs complete context of any past event. Combines unlimited storage with perfect organization and instant semantic retrieval. No current system achieves this.

Perfect memory of all information across all time with instant retrieval through any connection pathway. Divine omniscience.

Real-World Example: No real-world example exists. Level ∞ would require perfect memory of literally all information—every interaction, every document, every observation, every thought—across unlimited time with perfect fidelity, instant retrieval through any conceivable association or query, reconstruction of complete context for any moment in history, and unlimited capacity that never degrades. This represents memory capability approaching divine omniscience.
Return to Agent Power Framework