#37 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 3, Lesson 13] | Summary and Q&A

TL;DR

This content discusses a process for scoping AI projects by first identifying business problems before brainstorming AI solutions, assessing feasibility and value, and then fleshing out milestones and budgeting resources.

Key Insights

• 👨‍💼 It is important to first identify business problems before brainstorming AI solutions.
• ❓ Feasibility and value of AI solutions should be assessed before committing resources.
• 💡 One problem can have multiple possible AI solutions, and additional ideas may be brainstormed.
• 🤔 Engaging in both divergent thinking (considering many possibilities) and convergent thinking (narrowing down to the most promising projects) is beneficial.

Transcript

i'd like to share with you a process for scoping projects that hope will be valuable for how you decide what to work on when i'm speaking with a company for the first time about their ai projects this is the process that i use as well let's dive in when brainstorming projects work on the first thing i do is usually get together with a business or p... Read More

Questions & Answers

Q: Why is the initial focus on identifying business problems rather than AI problems?

The focus on business problems helps in coming up with better solutions, as engineers tend to be good at finding solutions but may not fully understand the underlying problems they are trying to solve.

Q: Can all problems be solved by AI?

No, not all problems can be solved by AI. Some problems may require non-AI solutions or may not have feasible AI solutions available.

Q: What does diligence mean in the context of scoping AI projects?

Diligence refers to double-checking the technical feasibility and value (return on investment) of an AI solution. It involves validating if the solution is truly feasible and valuable.

Q: Why is it important to separate the identification of problems from solutions?

Separating problems from solutions helps in generating a wider range of possible solutions. By first understanding the problem clearly, better solutions can be devised.

Summary & Key Takeaways

• The first step in scoping AI projects involves brainstorming with a business or product owner to identify their business problems, not AI problems.

• Once business problems are identified, the focus shifts to brainstorming possible AI solutions using machine learning algorithms.

• Feasibility and value of the solutions are then assessed before fleshing out project milestones and budgeting for resources.