From the course: AI Product Development: Technical Feasibility and Prototyping

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"Must knows" for feasibility

"Must knows" for feasibility

From the course: AI Product Development: Technical Feasibility and Prototyping

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"Must knows" for feasibility

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- Before we move to analyzing feasibility, I want you to get familiar with several AI technology-related elements you need to be aware of. First, options for AI implementation. Second, the idea behind proof of concept. And third, the core AI architecture concepts. I'll explain everything in simple terms, so even without a technology background, you'll be able to understand it. These concepts will help you benefit more from the next chapter, so I strongly encourage you to go through them and dig deeper. If any of the presented concepts are new to you, I cover them in my other LinkedIn Learning course, The new AI Tech Stack: AI Literacy for Tech Leaders, so feel free to check it out. Now let's start with options for AI implementation. You see each option brings different challenges to the table, so, naturally, the visibility for each one will be conducted in a slightly different way. For example, with the buy option, you want to check licensing. While for the build, you will be…

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