Artificial Intelligence (AI)
Artificial Intelligence (AI) and Machine Learning (ML) are transforming technology strategy, product capabilities, and engineering practices. A Chief Technology Officer (CTO) must establish effective AI governance, manage model risks, evaluate framework portability, and guide the deployment of autonomous agent workflows.
- AI Model Comparison Guide: Framework for evaluating models across capability, latency, pricing, context, and benchmark platforms.
- AGENTS.md: Defining operational context, constraints, and instructions for AI coding assistants and autonomous agents.
- EU AI Act: Navigating the European Union's risk-based legal framework for AI compliance and governance.
- UK AI Principles: Understanding the UK's sector-led, principles-based approach to regulating AI.
- MIT AI Risk Repository: Categorising and managing AI failure modes, safety risks, and operational harms.
- Model Collapse: Mitigating the risks of synthetic data feedback loops and model degradation.
- ONNX (Open Neural Network Exchange): Open standards for model portability and framework-agnostic runtime execution.