Artificial Intelligence (AI) had become more prevalent in our daily life. From virtual assistance to electrical appliances and automated vehicles, the application of AI can be seen everywhere. Now, AI is widely used in every industry and with the rise of AIaaS, its adoption is expected to expand in the future. There are various example of AIaaS platforms that can be adopted based on the need of organisation. Therefore, what are the example of AIaaS platforms available and its contributions?
Businesses need to ensure that their websites are able to answer inquiries instantly as customers are now online at all time. The use of bots are most common in customer service. AIaaS platforms offer bots particularly chatbots apply Natural Language Processing (NLP) algorithms to mimic natural conversations between humans. Additionally, NLP and machine learning (ML) are use to program these chatbots to understand customer’s queries and reply with relevant answers to the customers.
API or short for Application Programming Interface is a software that links two applications to communicate with each another. AIaaS platforms offer API for
- Natural Language Processing
- Computer speech
- Computer vision
- Knowledge mapping
Significantly, APIs that are available as-a-service make them able to be adopted and implemented immediately.
3. Machine Learning (ML)
Today, ML are crucial for developers in building models as well as companies in finding patterns in massive amounts of data, making predictions and streamlining processes. AIaaS platforms make it easy for companies to adopt ML frameworks and technology. Pre-trained models or customise tools in the platform allow them to adopt the most suitable option for their business requirement, even without the need for an AI expertise or machine learning skills.
4. Data classification
With the increased connectivity of devices and online services, the volume of generated data has become overwhelming. AIaaS platforms enable large-scale data classification and analysis using AI techniques, including content-based, context-based, and user-based specifications.
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