RegIntel

Curated resources are organized by regulatory oversight, AI governance, machine learning, and AI infrastructure to assist investment advisers, portfolio managers, research analysts, fiduciaries, legal professionals, technologists, and governance teams in evaluating the opportunities, risks, and limitations associated with artificial intelligence. Artificial intelligence encompasses a broad range of technologies, including machine learning, neural networks, deep learning, computer vision, large language models, and generative AI. The resources below are organized to reflect these distinct but related disciplines and provide practical points of reference for governance, oversight, implementation, and risk management. Resources are provided solely for informational purposes and convenience and updated periodically at Traiceback's discretion. Inclusion of a resource does not constitute an endorsement by Traiceback Solutions LLC.

Last updated: June 2026

Regulatory & Legal

SEC EDGAR Search Filings Investment Adviser Registration Depository Investment Adviser Public Disclosure SEC Div of Examinations 2026 Exam Priorities NB: p.13 focus on recent advancements in AI Statutes & Regulations governing SEC registrants CFR SEC Rules & Regs SEC.gov SEC Investment Management Recent SEC speeches and statements FINRA FINRA BrokerCheck Board of Governors Federal Reserve NYDFS Guidance Risks of Frontier AI Models
Cross-Border
EU AI Act ESMA FCA CSSF Central Bank of Ireland EUR-Lex MAS AI Model Risk Managment-Information Paper Dec. 2024 MAS consultation paper proposing Guidelines for AI Risk Management - Nov. 2025 Complete guide to GDPR compliance Digital Operational Resilience Act (DORA)
Litigation & Courts
PACER Cornell Legal Information Institute

AI Governance & Security

Board & Executive Oversight
NIST AI RMF ISO 42001 Explained COSO IC Over GenAI FRB SR 26-2 — Model Risk Management OECD Due Diligence Guidance for Responsible AI
AI Threats & Security
MITRE ATLAS OWASP Top 10 for LLMs PyRIT
Cybersecurity
Center for Internet Security NIST SP 800-53 Rev. 5 MITRE ATT&CK NYDFS Guidance on Measures for Heightened Cybersecurity Threats
Model Deployment
An Intro to APIs_Brian Cooksey Python (De)Serialization Techniques Getting Started with Streamlit

Machine Learning, LLMs & GenAI

GenAI
What is generative AI?
Python & Data Science
Google Colab Kaggle Kaggle Learn Jupyter Exploratory Data Analysis Guide NumPy Pandas Matplotlib Seaborn scikit-learn
Machine Learning
Intro Bagging and Ensemble Methods Intro to Random Forest Algorithm Implementation of Random Forest Intro to Boosting Intro to Gradient Boosting Gradient Boosting with Sklearn Beginners guide to XGBoost Original paper on XGBoost -Chen, Guestrin Cross Validation in Model Building Python based article on over and undersampling Hyperparameter Optimization with Random and Grid Search Hyperparameter tuning for machine learning models XGBoost LightGBM CatBoost
Computer Vision
Fundamentals of Image Processing Hands-On-Image-Processing-with-Python

AI Engineering & Infrastructure

What is Deep Learning? Deep Learning Tutorial Multi Classification Tutorial with Keras Deep Learning Library The Illustrated Transformer Transformers Explained Transformer Attention Mechanism Attention Is All You Need by Vaswani et al. - original paper that started it all Different Transformer Models
Neural Networks
Boolean Algebra & Logic Gates Activation Functions Understanding Backpropagation Tinker with a Neural Network Training Neural Networks
Deep Learning Frameworks
PyTorch TensorFlow
LLMs & RAG
Article explaining key concepts behind RAG Vector Embedding Explained Intro to Advanced Concepts of RAG LangChain LlamaIndex ChromaDB FAISS Hugging Face Retrieval-Augmented Generation
Prompt Engineering
Prompt Engineering Guide
Open AI Infrastructure
Docker Ollama Azure OpenAI