9 Go - AI implementation strategy
This chapter covers:
- Understanding the trade-offs involved in building an AI algorithm, buying from a provider, or leveraging open-source components
- Developing a Lean AI Strategy, a process to minimize risk when building AI solutions
- Taking advantage of the “Virtuous Cycle of AI”: a pattern that allows you to benefit from the performance boost that additional data can bring you.
The previous two chapters gave you all the building blocks you need for the definition and implementation of an AI project. It’s now time to put everything together. In this chapter, you’ll learn how to decide which components to build in-house or buy from a third-party, and how to manage the implementation phase. You’ll also get familiar with the most typical bumps in the roads faced by inexperienced AI builders. By the time you reach the end of the chapter, you’ll feel confident to kick-start the project tomorrow.
9.1 Buying or building AI
Paraphrasing what a wise man once said, sometimes the best way to complete a project successfully is never to start it in the first place. As an AI evangelist, one of the most impactful decisions you can make is to rely on products and services offered by AI providers and avoid building some or all of the technology needed for an AI project. This decision applies to all three of the components of the project: data, model, and infrastructure.