Deep Research Personality Analysis AI Agent
AI model and agent trained on neurotypology and facial feature analysis for deep understanding of personality, behavioral tendencies, and risk assessment
The deep learning-based system extracts subtle facial cues to predict personality traits. The model is trained and continuously re-trained on neuroimaging and facial analysis data.
Neural Data Collection
MRI-scanning from three angles to collect comprehensive brain structure data
Facial Analysis
Analysis of 82 specific facial points for correlation with neural structures
Personality Testing
Character traits assessment based on 34 polar theses
Key Scientific Findings:
- Amygdala size and personality: Smaller amygdalae linked to less aggression and calmer demeanor
- Parietal lobes and thinking: Enhanced development correlated with superior associative thinking
- Frontal lobes and control: Pronounced frontal lobes indicated better goal-setting and social norm adherence
1. Data Acquisition
User selfie upload (frontal and side photos increase accuracy). Quality control for resolution, format, angle, lighting.
2. Preprocessing
Face detection, standardization, histogram equalization, noise reduction.
3. Landmark Detection
Proprietary ensemble of regression trees identifies 68 facial landmarks with 5.5 normalized error.
4. Feature Extraction
19 core facial features calculated: jaw asymmetry, eyebrow height, eye slant, lip fullness, head shape.
5. Face Frontalization
GAN-based approach (StyleGAN2, Pix2Style2Pixel) transforms non-frontal poses to frontal faces.
6. Deep Learning Analysis
Ensemble of CNNs (ResNet-50) outputs 137 personality traits and 42 social interaction styles.
Personality Type Analysis
Socionics
Categorizes personality into 16 distinct types based on Carl Jung's theories. Provides detailed descriptions of interpersonal relationships and compatibility.
MBTI (Myers-Briggs)
Identifies 16 personality types based on four dichotomies: Extraversion/Introversion, Sensing/Intuition, Thinking/Feeling, Judging/Perceiving.
Behavioral and Cognitive Assessments
The system assesses a wide range of behavioral and cognitive aspects:
Dataset Scale
Priority is given to the ethical use of biometric data and fair matching. The system includes:
Consent Management
Granular opt-in for facial analysis with clear explanations of data usage
Data Anonymization
Irreversible conversion of facial data to 1024-dimensional vectors, with zero retention of original images
Security Measures
AES-256 encryption, TLS 1.3, multi-factor authentication
Fairness in Matching
Regular audits to ensure no demographic group is systematically disadvantaged
Regulatory Compliance
Adherence to GDPR, CCPA, and BIPA
This is one of 25 AI agents within Talents. It serves as an active assistant to meta-AI agents that build a child's talent tree.
Free Access
To quickly get the initial filling of a child's talent tree, we have made its use absolutely free for everyone, regardless of the tariff plan. This AI agent works in conjunction with 25 other AI agents, each performing its own role.