In today’s world of Cloud Computing creating Artificial Intelligence (AI) and Machine Learning (ML)based applications is becoming a reality for organizations of all sizes. Cloud providers such as Amazon, Microsoft, Google, IBM and Oracle et. al. are providing infrastructure, Cloud-based services and in some cases even consulting services to help companies to utilize Artificial Intelligence frameworks, Machine Learning, Big Data to build smart solutions which keep on getting better with continuous use. In this post I am going to review the applications of Artificial Intelligence and Machine Learning and factors involved in getting started with these in your organization.
This infographic post describes the checklist of activities which one should consider when building Artificial Intelligence and Machine Learning based applications. It identifies the activities from Sales, Marketing, Customer Service and your company’s Process framework which maybe a good fit to use Artificial Intelligence and Machine Learning. It ends with an overview of an end-to-end process to build an AI/ML solution.
Typical Activities which can be considered for AI and ML application include high volume, repetitive, limited judgement, low cost of mistakes and following a prescribed pattern. Some examples of applications include:
A typical end to end flow for an Artificial Intelligence and Machine Learning application will include problem identification, identifying data source, building a solution using one of the Cloud providers, implementing the solution and then training it over a period of time to make it more intelligent and human-like.
For more information on how Cloud Computing is enabling both Artificial Intelligence (AI) and Machine Learning (ML) check out my blog post on how Cloud Computing is enabling Digital Transformation.
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