AI or artificial intelligence is the simulation of human-like intelligence processes and decision making done by machines, especially computer systems. These processes include learning, reasoning, and self-correction. Some of the applications of AI include expert systems, speech recognition, and machine vision. Developing an artificial intelligence application can be a difficult task, often requiring a team of software engineers carefully working in tandem. Here are the four key steps to create an effective AI Application:
- Problem-solution fit
Reaching a problem-solution fit means that you have already built an MVP (minimum viable product), you have found your early adopters (people to use your MVP), you have managed to solve a problem that your early adopters have, and you have managed to charge enough for your solution so that users are happy.
- Data-gathering / AI building Game
This will be your first generation of AI. At this point, you will still have to give some human inputs to your AI application so it can learn and adapt. Train your model and as it receives more data and learns your human inputs, your results will start getting more accurate.
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- Product Build
After you have a working AI, it is time to make it more accessible for your user base. Package your AI into a product, so it is as simple as opening an application and getting the required information. This means designing a user interface and have a unique selling point when compared to the other similar applications.
- Develop Ways for Improving AI
Once your final AI Application has launched, you will start getting lots of information. Much of this information will be completely new, hence you need a way to make sense of it and use it to further improve your application and it’s AI accuracy. Figure out where to store this new information, retrain AI whenever necessary, and test how the new versions of your AI application perform when directly compared to its older versions.