AI App Development Guide for Business Owners

A Guide to AI Application Development for Business Owners
To properly begin exploring the AI ​​app development process, it’s important to first understand how these projects differ from regular app development projects. When it comes to AI, each problem requires a unique solution, even if the company has done similar projects before. On the one hand, there are various pre-trained models and proven methods of building AI. AI is also unique because it is based on different data and business cases. For this reason, AI engineers often begin their journey by diving deep into the business case and actionable data, exploring existing methods and models. The top tier has ready-made products suitable for AI use – such as third-party libraries or proven enterprise solutions. A good example is Google’s solutions for fraud detection, face recognition, and object detection.

The second level consists of new niches that describe business challenges. We may have a suitable model to solve the problem, but the technology needs a little change or adaptation to prove its effectiveness during implementation. A model must be specialized for its particular use, leading to a new niche in the use of AI. Scientific research forms the lower level layer. Here we will find papers and new models – as an example, we will mention GPT-3. Scientific research is not ready for production because we do not know what the results of such models show. This is a deep-level AI system, although we can go in that direction.