Two Key Elements of AI

Go back to the [[Main AI Page]] See the [[Week 1 - Introduction]] AI contents page

#AIBusinessCase

Componentry

• A unified, modern data fabric.
  • Data must be prepared for the AI to use.
  • Logical representation of all data assets.
• A development environment and engine.
  • A place to build, train, and run AI models.
  • End-to-end, input-to-output.
  • models help find patterns and strctures in data that are inferred rather than explicit.
• Human features
  • HUman features.
    • UI/UX attached to the AI’s IO with features like voice, language, vision, and reasoning.
• AI management and exploitation.
  • Enables you to insert AI into any application or business process.
  • Make sure you can test, bench-test, improve, check what has changed, and measure variance.
  • This is how you manage AI lifecycle, proof, and explain-ability of decisions.

Process

• Identify the Right Business Opportunities for AI.
  • Customer service (chatbots)
  • Employee/company productivity << Reference for Proposal
  • Manufacturing defects
  • supply chain spending
  • If it can be described >> It can be programmed >> Ai can make it better
• Prepare the Organization for AI.
  • [[The AI Job Replacement Axiom]]
  • All technology is useless without the talent to put it to use
  • Repetitive and manual tasks will be automated
• Select Technology & Partners.
  • Corporate culure should drive the choice of AI technology mix.
  • Adopt many technologies and learn which ones work and which ones don’t.
  • Pick and handful of partners that have the skills and tech to get the job done.
• Accept Failures.
  • [[AI’s Ratchet effect]]
  • If you try 100 AI projects, 50 will probably fail.
  • But, the 50 that work will be more than compensate for the failures.
  • The culture you create must be ready and willing accept failures, learn from them, and move onto the next.
  • Fail-fast, as they say.