Artificial Intelligence As a Product
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Artificial Intelligence As a Product

SUMIT PANDEY

AI has been considered by many as a "solution" for all their problems. AI is not a solution, but rather a tool that can be used to solve the problem. The key to success of any AI application is the problem understanding, i.e., identifying the problem and envisioning how AI can solve it.

This article will provide you with some tips on how to identify the need for an AI powered application and how to decide whether you need machine learning or deep learning or both. It will also outline some performance indicators of your current application and provide you with some suggestions on how to improve the performance of your application.

Identifying the Need and the Technology to Solve it

When you decide to build an application using AI technology, you have to make sure that you have identified the problem that needs solving. Many businesses have started using AI without identifying their problems initially, which could lead them to building an application that may not solve their problems at all, or may solve other problems in addition to the one they set out to solve.

Identifying the business problem that needs solving is essential in ensuring that the outcome of your application is what you had envisioned it to be. The other part of your solution should be identification of the technology used in building it. This article will focus on how you can identify which technology would best suit your business needs.

Here are six features to look out for in an AI solution:

1. Machine Learning:  

Machine learning is a subset of AI where computers learn on their own without being explicitly programmed on how to behave or what data they should collect.

This applies well in cases where there are large quantities of data available or where data elements are changing so fast that algorithms cannot be updated fast enough to respond effectively. You should always consider machine learning as a solution whenever you have large quantities of data available, because it will allow computers to process data faster than any traditional programming could allow it to do.

2. Automation:  

Automation enables your business to run faster without having to hire more employees. This is accomplished by allowing the application to make decisions on its own, without human intervention. This feature is much more effective when you combine it with machine learning, because it allows the application to learn how to make decisions on its own.

3. Bot Design and Deployment:  

The bot design and deployment feature is what determines the success of your AI application. If you want your application to be truly useful, then it should be designed in such a way that it can respond to any requests from the users or customers.

In addition, your AI solution should be designed in such a way that it can assist users across different channels, including voice and text based interfaces.

4. Natural Language Processing (NLP) and Natural Language Understanding (NLU):  

The ability for computers to understand human language has been one of the key features that have allowed computer technology to advance so rapidly over the past 50 years.

NLP and NLU refers to the part of AI where computers are taught how to understand human language and respond accordingly.

NLP allows computers to process text based requests from humans while NLU allows computers to process voice based requests from humans, thus allowing computers to interact with humans in a more natural way.

5. Cloud Infrastructure:  

Cloud computing has been one of the most important technological advancements in recent times because it allows businesses to scale up their applications when needed, without having to worry about buying extra hardware or upgrading existing hardware capacity.

Using cloud infrastructure allows businesses to focus on the development of their business problem rather than focusing on purchasing hardware or managing data storage. This also allows businesses to use specialized hardware that may be too expensive for them if they were required to purchase it independently.

6. Price:

This is probably one of the most important features to consider when looking for an AI solution. The price of an AI solution should depend on many factors including but not limited to; what technology will be used, number of data available for training, complexity of the problem and training time required among others.

You should always consider the cost of your AI solution after considering all other aspects of the solution before making a decision on whether or not you need an AI solution for your business problem.

Conclusion

While there are many ways on how you can ensure that your AI solution will meet your expectations, the two most important factors you should consider are identifying your business problem and identifying which technology will solve it best.

Identifying these two factors will help you build a better AI solution that can improve your business operations and make your business more productive while reducing your costs at the same time.