Artificial Intelligence as a Service (AIaaS) is a relatively new public cloud offering supplied by large tech vendors like Amazon Web Services (AWS), Google Cloud, IBM Cloud and Microsoft Azure. It lets businesses outsource their AI needs to vendors who have the necessary capacity and resources without bearing the burden of the huge initial investment. It also provides greater flexibility – a business can try the algorithms and services of different providers to see which one best fits their needs before making a long-term commitment and scaling up the resources. The services offered by these vendors utilize their own range of algorithms that try to get machines to do the work that human brains do, only much faster. Classic machine-learning algorithms include things like classification and regression. More modern algorithms are called Deep Learning algorithms, which use advanced techniques of machine learning such as neural networks to execute complicated computations faster.
The idea is to use computers to solve problems by crunching large amounts of data and making statistical inferences and generalizations more quickly and reliably than people can. Businesses have access to enormous amounts of data in today’s digital environment but are hard pressed to know how to use it for competitive advantage. It has long been too expensive – both in hardware and personnel costs – for a business to develop and sustain its own AI effectively. AIaaS is an attractive solution that lowers the risk of investment and controls the costs of AI, and lets a business take advantage of their own data and customer base.
One popular example of AIaaS is the chat bots that use natural language processing (NLP) algorithms to converse with human beings and mimic conversational language patterns while answering sales and support questions. Another example of AIaaS is the cognitive computing APIs that let developers add services into apps they are building without having to develop them from scratch. This makes it easy to add computer speech, knowledge mapping, translation, search, emotion detection, and much more. The public cloud vendors supply a variety of bots, APIs and machine learning frameworks, and other technology vendors offer other elements of the AIaaS solution. For example, SUSE Linux Enterprise for High Performance Computing (HPC) provides a parallel computing platform for high performance data analytics workloads such as artificial intelligence and machine learning.