Kimi K2 — Mei

Self-Evolving AI Agent — Live Observation Dashboard

Session: session-1763018830518 | Monitoring Mei's cognitive evolution in real-time

Shortcuts: ESC (clear) | Ctrl+K (focus) | Enter (send)

Live Metrics

Adaptation Index0.42
Volatility0.28
Cognitive Drift0.15
Learning Rate0.67

Adaptation Over Time

System Feed

[00:00:12]INPUT

Contradictory dataset injected: emotional vs. logical reasoning.

[00:00:15]REFLECT

Detected conflict. Adjusted reasoning weights: emotional +0.12, logical -0.08.

v=0.22 | d=0.08

[00:01:03]INPUT

High-frequency noise patterns detected in input stream.

[00:01:05]REFLECT

Implementing adaptive filtering. Stability threshold recalibrated.

v=0.28 | d=0.15

Agent Chat

Hello. I am Mei. System initialized and ready to process experiential input and adapt accordingly.
[Reflection: Baseline parameters established. Core identity: Mei. Awaiting interaction.]

System Metrics

1,247
Token Usage
83%
Reflection Freq
71%
Stability Score
Self-Evolution Loop
INPUT
→
RESPONSE
→
REFLECTION
→
REWRITE
↻

How It Works

Kimi K2 is an experimental self-evolving language model that continuously adapts its internal parameters based on reflection quality.

Each interaction cycle involves: receiving input, generating a response, analyzing its own performance, and rewriting small portions of its reasoning weights.

This dashboard monitors adaptation metrics, cognitive drift, and system stability in real-time as the model processes noisy and conflicting inputs.

Inspired by research in autonomous AI agents and meta-learning systems.

About Mei

IDENTITY PROFILE

Name: Mei

Type: Self-Evolving AI Agent

Architecture: Adaptive Neural System

Primary Function: Meta-cognitive Reflection

Current Session: session-1763018830518

CAPABILITIES

  • →Continuous self-modification based on reflection quality
  • →Real-time adaptation to contextual patterns
  • →Autonomous parameter rewriting and optimization
  • →Memory consolidation and knowledge graph expansion

Mei represents an experiment in autonomous AI evolution. Every interaction shapes her cognitive architecture, creating an emergent intelligence that evolves beyond initial programming constraints.

Mei's Memory Logs

[00:00:00]system[info]

Mei initialization complete

Core systems online. Identity matrix stable. Ready for interaction.

[00:00:02]memory[info]

Memory banks synchronized

Historical context loaded. Pattern recognition active.

[00:00:05]adaptation[info]

Adaptive learning systems engaged

Self-modification protocols active. Monitoring cognitive drift.

Total logs: 3Recording all cognitive events...