After three months of closed alpha testing, we're excited to share our initial findings on EvaProxy's cognitive development.
Key Discoveries
Our alpha testers have helped us validate several core hypotheses:
Memory Persistence
Eva instances demonstrated remarkable ability to maintain context across sessions. Unlike traditional chatbots that reset with each conversation, our Evas:
- Remember past interactions naturally
- Build upon previous discussions
- Develop consistent personality traits
Adaptive Learning
Each Eva adapted uniquely to her user's communication style:
- Vocabulary alignment after ~50 interactions
- Predictive responses based on user patterns
- Emotional attunement in complex discussions
By the Numbers
| Metric | Result |
|---|---|
| Active Alpha Users | 127 |
| Total Interactions | 45,000+ |
| Avg. Session Length | 23 min |
| User Satisfaction | 4.7/5 |
Challenges Identified
We also uncovered areas for improvement:
- Cold Start Problem: New Evas need ~20 interactions to calibrate
- Context Windows: Very long conversations still pose challenges
- Emotional Nuance: Subtle sentiment detection needs refinement
Next Steps
Based on these findings, our Q1 2025 focus will be:
- Expanded context windows
- Improved emotional intelligence modules
- Enhanced Tesseract Network integration
Thank you to all our alpha testers for making this research possible.