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Evolution of Machine Learning and APIs

Evolution of Machine Learning and APIs

APIs or Application Programming Interfaces are nothing but a bunch of mechanisms that connect services, data and apps for creating modern digital experiences. For eg: if a shopper is browsing through an app then it is the API that pulling every detail together to deliver a seamless experience to the user. The same can be said while one initiates any payment online. There are certain APIs that work behind the scenes to complete the said transaction and if a person places a request for a cab or charts directions using a mapping service then still more API calls are involved in the activity. So it can be safely said a large portion of API traffic is due to some kind of human action or is based on a request-response model.

However, it has been observed that the API world is experiencing a paradigm shift. With benign programmatic API calls that are created by algorithms or machine intelligence are taking on a more crucial role in the digital ecosystem scenario. This shift can be attributed to several trends that open a plethora of new dimensions for how organizations leverage the APIs and expand the current ones.

Mainstreaming AI: Undoubtedly, AI is most beneficial when it can be leveraged into apps but then not many organizations possess the capability to do AI from scratch. So, one can expect to see API-driven AI which one business builds an excellent model in a certain domain and other organizations can leverage that work through API. Further, these organizations can then develop their own AI models, which again another team may leverage.

Automation and IoT: IoT devices integrate with each other and voice assistant through APIs. With the enthusiasm for the IoT growing, many experts estimate that there is already a number of connected devices currently in use than the total number of people on this planet. And this deluge of communication, intelligent devices and sensors aren’t going to stop. Though APIs may not be able to solve all hurdles associated with intense business logic, rather they can simplify the process making it easier for the devices to interact well with each other.

The rise of Voice Applications: With applications expanding at a rapid speed, voice-based technologies are poised to grow big and go beyond their origins on speakers and smartphones. This technology has made its presence felt in healthcare and we have witnessed a surge in new use cases emerging across the enterprises. Though this technology is potentially expensive to develop which is why many organizations have developed their own NLP(Natural Language Processing) technologies available to others via APIs. If a voice assistant hears a command, the assistant needs to understand the unstated nuances of the instructions and this task is dependant on machine learning. Hence, for the user, it may be a simple request but it results in potentially hundreds of API calls across the backend which is driven by machine intelligence figuring out things in the background. As we see more use cases integrate with voice, the underlying machine learning technologies and APIs which make those technologies leverageable is set to grow.

Posted By :Pace Wisdom