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This article is about Artificial Intelligence
Everything You Need To Know About AI As A Service (AIaaS)
By NIIT Editorial
Published on 19/10/2021
7 minutes
With Artificial Intelligence, businesses improve products and experiences for customers, make data-driven decisions, and automate time-consuming tasks. The range of AI applications that companies are implementing varies in different fields, from chatbots and text analysis tools to more sophisticated predictive analytics tools.
Most businesses won't benefit from building their artificial intelligence solution. There are significant upfront costs associated with this long and complex process. That's why enterprises and cloud providers often prefer AIaaS (Artificial Intelligence as a Service), third-party solutions, or cloud services that can be used immediately.
Several online DevOps & cloud computing courses give you a detailed overview and knowledge on the fundamentals of AI as a Service (AIaaS)
What is AIaaS?
The term "artificial intelligence as a service" describes tools readily available off-the-shelf that permit companies to scale AI techniques for a fraction of the cost of hiring an entire AI department.
Because of being the cloud provider, everything as a service refers to any software that can be accessed over a network. The software is readily available for purchase. If you buy it from a vendor, tweak it a little, and you can practically begin using it right away, even if it hasn't been entirely customized for your system.
Artificial intelligence has been prohibitively expensive for most companies for a long time:
The Machines Were Massive And Cost A Lot Of Money.
Programmers specializing in machines like these were in short supply (which meant their wages were high). Many companies lacked the data for assessing and studying. But the answer to this was Artificial Intelligence as cloud services. With a perfect cloud service becoming more accessible, AI has become more accessible: companies can gather and store an infinite amount of data.
Here's a brief detour into AIaaS so you can set the right expectations when interacting with it.
Using AIaaS Platforms Offers Many Benefits
- Using sophisticated technology is not required
- A no-code AIaaS infrastructure makes it possible to integrate AIaaS even if you don't have a programmer on staff. With setting up AIaaS, companies that provide it rarely require any coding or technical skill from any DevOps online training, best cloud training online, online cloud computing course.
Despite these facts, implementation complexity can vary when dealing with legacy software, even when some AIaaS solutions do not require coding skills from the best DevOps or cloud computing training online.
Advanced And Fast Infrastructure
For AI and machine learning models to run successfully, powerful GPUs were needed before AIaaS. For most SMEs, developing software in-house is not an option.
You can use a few rules of thumb that could help you in the world of artificial intelligence - the first one is to feed your model good quality data to be effective.
Due to the customization capabilities of AIaaS', businesses can create their custom-designed task-oriented models based on their wealth of data.
List Of AI As A Service Platform And The Problems They Solve
Since you're here, this article will shed some light on the most common types of tools available.
Bots
Whether you visit a government website or a clothing store today, you are likely to encounter bots - most likely, chatbots, their most common form. The algorithms emulate natural conversations between humans using natural language processing (NPL). In a customer service context, these types of bots provide relevant answers to the most common questions from customers.
Because of the 24/7 availability of these services, employees can focus their time on more complex tasks, saving valuable time and resources. 92% of each of the millions of customer conversations they handle each year can be automated by leveraging a chatbot, according to one of Europe's fastest-growing parcel delivery service providers.
APIs
APIs (Application Programming Interfaces) are the software "middle-men" that allows two programs to exchange information with eachother. For example, third-party airline booking websites such as Expedia, CheapOair, or kayak use airline databases to provide all their deals in a single, readable place.
Another everyday use of APIs is:
- Natural Language Processing (e.g., sentiment or urgency analysis)
- Computer vision
- Conversational AI
- APIs are used to connect apps across platforms, and most AIaaS providers build their integrations on top of them.
Machine Learning
Data analysis and pattern-finding are performed using Machine Learning by companies. Data analysis using this method operates without human intervention. It makes predictions it wasn't taught to do, and it learns as the process progresses.
The AIaaS concept allows companies to take advantage of Machine Learning to have no technical expertise. There are tons of solutions ranging from pre-trained models to building custom models from a data center (just don't forget the rule of thumb!).
In A Nutshell
Artificial Intelligence as a Service results from combining the 'as a service' model with advances in Artificial Intelligence usage. It makes Artificial Intelligence and cloud services available to everyone.
While AI has already been used in automation solutions from companies like IBM, Microsoft, Google, and Amazon, those solutions were too complex and required too much learning for many businesses. The same is even for a cloud provider. The rise of AIaaS for SMEs is thus no mean feat, as it truly opens up a world of possibilities.
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