# AI For Everyone Andrew Ng, lead of Google Brain, Baidu AI, ... ## AI Venn Diagram [[AI Venn Diagram]] ## AI Companies - Strategic data acquisition - Unified data warehouse - Pervasie automation - New roles: ML Engineer (MLE), etc - New vision of labor ## What ML can and cannot do [[What Machine Learning can and cannot do]] ## Workflows [[Machine Learning Project Workflow]] [[Data Science Project Workflow]] ## How to choose an AI project [[How to choose an AI project]] ## Build vs buy - ML projects can be in-house or outsourced - DS projects are more commonly in-house - Some things are industry standard, and building in-house doesn't make much sense ## Data Sets [[AI Data Sets]] ## Working with an AI team - First, define your acceptance criteria - Example: detect defects with 95% accuracy - Provide the team with a test set - Don't expect 100% accuracy - Limitations of ML - Insufficient Data - Mislabeled data - Ambiguous labels - ... ## Others [[Complex AI product examples]] [[Roles and responsibilities in an AI team]] [[AI Transformation Playbook]] [[AI Pitfalls to avoid]] [[How to dive into AI]] [[AI Major Applications]] [[AI Major Techniques]] ## AI and society - Hype about AI - [[AI Limitations]] - AI and Ethics - AI, developing economies and jobs - [[Goldilocks rule for AI]] - Discrimination / Bias - [[How to limit AI Bias]] - Adversarial attacks on AI - Adverse uses of AI - AI and developing economies - Possibility of "leapfrog" for developing economies - They can build AI by... - Focusing on AI to strenghten their country's vertical industries - Establish public-private partnerships to accelerate development - Invest in education - [[AI and Jobs]]