|
CONCEPT_MAP_JSON = """ |
|
{ |
|
"central_node": "Artificial Intelligence (AI)", |
|
"nodes": [ |
|
{ |
|
"id": "ml_fundamental", |
|
"label": "Machine Learning", |
|
"relationship": "is essential for", |
|
"subnodes": [ |
|
{ |
|
"id": "dl_branch", |
|
"label": "Deep Learning", |
|
"relationship": "for example", |
|
"subnodes": [ |
|
{ |
|
"id": "cnn_example", |
|
"label": "CNNs", |
|
"relationship": "for example" |
|
}, |
|
{ |
|
"id": "rnn_example", |
|
"label": "RNNs", |
|
"relationship": "for example" |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "rl_branch", |
|
"label": "Reinforcement Learning", |
|
"relationship": "for example", |
|
"subnodes": [ |
|
{ |
|
"id": "qlearning_example", |
|
"label": "Q-Learning", |
|
"relationship": "example" |
|
}, |
|
{ |
|
"id": "pg_example", |
|
"label": "Policy Gradients", |
|
"relationship": "example" |
|
} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "ai_types", |
|
"label": "Types", |
|
"relationship": "formed by", |
|
"subnodes": [ |
|
{ |
|
"id": "agi_type", |
|
"label": "AGI", |
|
"relationship": "this is", |
|
"subnodes": [ |
|
{ |
|
"id": "strong_ai", |
|
"label": "Strong AI", |
|
"relationship": "provoked by", |
|
"subnodes": [ |
|
{ |
|
"id": "human_intel", |
|
"label": "Human-level Intel.", |
|
"relationship": "of" |
|
} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "ani_type", |
|
"label": "ANI", |
|
"relationship": "this is", |
|
"subnodes": [ |
|
{ |
|
"id": "weak_ai", |
|
"label": "Weak AI", |
|
"relationship": "provoked by", |
|
"subnodes": [ |
|
{ |
|
"id": "narrow_tasks", |
|
"label": "Narrow Tasks", |
|
"relationship": "of" |
|
} |
|
] |
|
} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "ai_capabilities", |
|
"label": "Capabilities", |
|
"relationship": "change", |
|
"subnodes": [ |
|
{ |
|
"id": "data_proc", |
|
"label": "Data Processing", |
|
"relationship": "can", |
|
"subnodes": [ |
|
{ |
|
"id": "big_data", |
|
"label": "Big Data", |
|
"relationship": "as", |
|
"subnodes": [ |
|
{ |
|
"id": "analysis_example", |
|
"label": "Data Analysis", |
|
"relationship": "example" |
|
}, |
|
{ |
|
"id": "prediction_example", |
|
"label": "Prediction", |
|
"relationship": "example" |
|
} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "decision_making", |
|
"label": "Decision Making", |
|
"relationship": "can be", |
|
"subnodes": [ |
|
{ |
|
"id": "automation", |
|
"label": "Automation", |
|
"relationship": "as", |
|
"subnodes": [ |
|
{ |
|
"id": "robotics_example", |
|
"label": "Robotics", |
|
"relationship": "Example"}, |
|
{ |
|
"id": "autonomous_example", |
|
"label": "Autonomous Vehicles", |
|
"relationship": "of one" |
|
} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "problem_solving", |
|
"label": "Problem Solving", |
|
"relationship": "can", |
|
"subnodes": [ |
|
{ |
|
"id": "optimization", |
|
"label": "Optimization", |
|
"relationship": "as is", |
|
"subnodes": [ |
|
{ |
|
"id": "algorithms_example", |
|
"label": "Algorithms", |
|
"relationship": "for example" |
|
} |
|
] |
|
} |
|
] |
|
} |
|
] |
|
} |
|
] |
|
} |
|
""" |
|
|
|
|
|
SYNOPTIC_CHART_JSON = """ |
|
{ |
|
"central_node": "AI Project Lifecycle", |
|
"nodes": [ |
|
{ |
|
"id": "phase1", |
|
"label": "I. Problem Definition & Data Acquisition", |
|
"relationship": "Starts with", |
|
"subnodes": [ |
|
{ |
|
"id": "sub1_1", |
|
"label": "1. Problem Formulation", |
|
"relationship": "Involves", |
|
"subnodes": [ |
|
{"id": "sub1_1_1", "label": "1.1. Identify Business Need", "relationship": "e.g."}, |
|
{"id": "sub1_1_2", "label": "1.2. Define KPIs", "relationship": "e.g."} |
|
] |
|
}, |
|
{ |
|
"id": "sub1_2", |
|
"label": "2. Data Collection", |
|
"relationship": "Followed by", |
|
"subnodes": [ |
|
{"id": "sub1_2_1", "label": "2.1. Source Data", "relationship": "from"}, |
|
{"id": "sub1_2_2", "label": "2.2. Data Cleaning", "relationship": "includes"} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "phase2", |
|
"label": "II. Model Development", |
|
"relationship": "Proceeds to", |
|
"subnodes": [ |
|
{ |
|
"id": "sub2_1", |
|
"label": "1. Feature Engineering", |
|
"relationship": "Comprises", |
|
"subnodes": [ |
|
{"id": "sub2_1_1", "label": "1.1. Feature Selection", "relationship": "e.g."}, |
|
{"id": "sub2_1_2", "label": "1.2. Feature Transformation", "relationship": "e.g."} |
|
] |
|
}, |
|
{ |
|
"id": "sub2_2", |
|
"label": "2. Model Training", |
|
"relationship": "Involves", |
|
"subnodes": [ |
|
{"id": "sub2_2_1", "label": "2.1. Algorithm Selection", "relationship": "uses"}, |
|
{"id": "sub2_2_2", "label": "2.2. Hyperparameter Tuning", "relationship": "optimizes"} |
|
] |
|
} |
|
] |
|
}, |
|
{ |
|
"id": "phase3", |
|
"label": "III. Evaluation & Deployment", |
|
"relationship": "Culminates in", |
|
"subnodes": [ |
|
{ |
|
"id": "sub3_1", |
|
"label": "1. Model Evaluation", |
|
"relationship": "Includes", |
|
"subnodes": [ |
|
{"id": "sub3_1_1", "label": "1.1. Performance Metrics", "relationship": "measures"}, |
|
{"id": "sub3_1_2", "label": "1.2. Bias & Fairness Audits", "relationship": "ensures"} |
|
] |
|
}, |
|
{ |
|
"id": "sub3_2", |
|
"label": "2. Deployment & Monitoring", |
|
"relationship": "Requires", |
|
"subnodes": [ |
|
{"id": "sub3_2_1", "label": "2.1. API/Integration Development", "relationship": "for"}, |
|
{"id": "sub3_2_2", "label": "2.2. Continuous Monitoring", "relationship": "ensures"} |
|
] |
|
} |
|
] |
|
} |
|
] |
|
} |
|
""" |
|
|
|
|
|
RADIAL_DIAGRAM_JSON = """ |
|
{ |
|
"central_node": "AI Core Concepts & Domains", |
|
"nodes": [ |
|
{ |
|
"id": "foundational_ml", |
|
"label": "Foundational ML", |
|
"relationship": "builds on", |
|
"subnodes": [ |
|
{"id": "supervised_l", "label": "Supervised Learning", "relationship": "e.g."}, |
|
{"id": "unsupervised_l", "label": "Unsupervised Learning", "relationship": "e.g."} |
|
] |
|
}, |
|
{ |
|
"id": "dl_architectures", |
|
"label": "Deep Learning Arch.", |
|
"relationship": "evolved from", |
|
"subnodes": [ |
|
{"id": "cnns_rad", "label": "CNNs", "relationship": "e.g."}, |
|
{"id": "rnns_rad", "label": "RNNs", "relationship": "e.g."} |
|
] |
|
}, |
|
{ |
|
"id": "major_applications", |
|
"label": "Major AI Applications", |
|
"relationship": "applied in", |
|
"subnodes": [ |
|
{"id": "nlp_rad", "label": "Natural Language Processing", "relationship": "e.g."}, |
|
{"id": "cv_rad", "label": "Computer Vision", "relationship": "e.g."} |
|
] |
|
}, |
|
{ |
|
"id": "ethical_concerns", |
|
"label": "Ethical AI Concerns", |
|
"relationship": "addresses", |
|
"subnodes": [ |
|
{"id": "fairness_rad", "label": "Fairness & Bias", "relationship": "e.g."}, |
|
{"id": "explainability", "label": "Explainability (XAI)", "relationship": "e.g."} |
|
] |
|
}, |
|
{ |
|
"id": "future_trends", |
|
"label": "Future AI Trends", |
|
"relationship": "looking at", |
|
"subnodes": [ |
|
{"id": "agi_future", "label": "AGI Development", "relationship": "e.g."}, |
|
{"id": "quantum_ai", "label": "Quantum AI", "relationship": "e.g."} |
|
] |
|
} |
|
] |
|
} |
|
""" |
|
|