Getting Started With Azure AI Services

By Ashwin Venugopal -

 





What is Artificial Intelligence (AI)?

In general terms, AI can be considered as a software that exhibits one or more human-like capabilities described below:

  • Visual Perception- It is the ability to use computer vision capabilities to accept, interpret, and process input from images, video streams, and live cameras.

  • Text Analysis and Conversation- It is the ability to use Natural Language Processing (NLP) to not only "read", but also generate realistic responses and extract semantic meaning from text. 

  • Speech- It is the ability to recognize speech as input and synthesize spoken output. 

  • Decision Making- It is the ability to use past experiences and learned correlations to assess situations and take appropriate actions. 

These kind of capabilities are increasingly within the reach of everyday software applications making them more useful in a wide variety of scenarios.

AI-related Terms

It is necessary to understand clear definitions of other AI related terms.

Data Science

Data Science is a discipline that focuses on the processing and analysis of data by applying statistical techniques to uncover and visualize relationships as well as patterns in the data, and defining experimental models that help explore those patterns. 

Machine Learning

Machine Learning is a subset of data science. It deals with training and validation of predictive models. Generally, a data scientist prepares the data and then uses it to train a model based on an algorithm that exploits the relationships between the features in the data to predict values for unknown labels. 

Artificial Intelligence

Artificial Intelligence usually builds on machine learning to create a software that can mimic one or more characteristics of human intelligence. 

Considerations For AI Engineers

Software engineers must know how to integrate AI capabilities into their applications and services. They can use its services to create applications and agents that use the underlying AI functionality, using them as building blocks to create intelligent solutions. Hence, they can apply their existing skills in programming, testing, working with source control systems, and packaging applications for deployment, that too without having to become data scientists or machine learning experts. However, they still require at least a conceptual understanding of core AI and machine learning principles to fully take advantage of  AI. 

Conclusion

 We have successfully learnt about AI and its considerations. 











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