Of course, one Of The Most Interesting And Newest Titles To The World Of Cloud Computing, And Relatively New Compared To Other Examples, Is Artificial Intelligence As A Service (Aiaas).
Artificial intelligence helps businesses improve product quality and customer experience, make data-based decisions, and automate time-consuming tasks.
From text analytics chats and software to more sophisticated analytics and forecasting tools, in all of these cases, artificial intelligence is used in a variety of ways. So today, you will not find any major industry in the world that has not used artificial intelligence algorithms to advance business goals.
However, implementing an internal AI solution does not make sense for most jobs, as it is a long and complex process with high initial costs. This is why businesses often turn to the AIaaS paradigm, or AI as a service, third-party solutions that can use immediately.
What is AIaaS?
AIaaS stands for artificial intelligence as a service and refers to the field of activity of companies that offer artificial intelligence solutions. By artificial intelligence, we mean computer systems that can perform human-like tasks.
These tasks can be reasoning, learning from past experiences, and solving problems. In other words, machines can act and think like humans. Artificial intelligence is a broad term that includes various technologies such as machine learning, robotics, natural language processing (NLP), and computer vision.
If you have heard terms such as software as a service (SaaS) or infrastructure as a service (IaaS) in the past, you are somewhat familiar with the functionality of AIaaS.
Here, AIaaS refers to a set of solutions developed and hosted as a service by a third-party provider and is a cost-effective alternative to developing in-house intelligent software.
AIaaS makes artificial intelligence technology accessible to all people. The above paradigm uses APIs and visual and minimal coding tools. Users can use the power of artificial intelligence without writing a single line of code or the least line of code.
In addition, instead of spending months launching smart solutions, AIaaS can build an efficient model for consumers in just a few weeks.
What are the benefits of artificial intelligence as a service?
It is an external solution: AIaaS can be set up and ready in the shortest time.
Affordable: Outsourcing AI is the best solution if you do not have the resources to develop in-house smart software.
No need for specialists: There is no need to hire a team of specialists or developers of complex infrastructure in the above paradigm.
Mntf of: flexible feature on AIaaS is often a good option that customizes your business needs with artificial intelligence tools.
It is clear: in the above model, you only pay for the use you have.
Scalable: You can increase or decrease the requirements based on your needs and the growth of your business.
Types of artificial intelligence as a service
There are several types of AI services. When you are ready to buy or rent a service, you have probably done good research in this field and evaluated the strengths and weaknesses of the services correctly. However, before implementing such services in Iran, it is important to have a general understanding of the three popular paradigms in this area:
Chats use artificial intelligence algorithms to simulate human conversations. They combine NLP and machine learning capabilities to understand users’ questions and provide relevant answers. Bats try to satisfy customers by reducing the response rate. Not bad to know that bats have been able to revolutionize the provision of pre-and after-sales service to customers.
They help businesses automate routine tasks and spend precious time on more complex tasks. In addition, bots can serve customers 24 hours a day, 7 days a week, and answer most questions without human intervention.
Application Programming Interfaces (APIs)
Many AIaaS solutions are provided through application programming interfaces. The API acts as an intermediary and allows two software to interact with each other. Suppose you want to arrange customer support tickets automatically based on the topic in the guide.
You can connect an AI tool like MonkeyLearn to your favorite customer service software to do this automatically and intelligently through the API.
You can use APIs to process natural language, analyze emotions, and extract entities from text and other tasks. When application programming interfaces are provided as a service, they are instantaneous, and you can reap their potential benefits with just a few lines of coding.
Companies use machine learning algorithms to find patterns in large amounts of data, predictions, and process simplifications. AIaaS simplifies the application of machine learning technology for simple jobs. You can use pre-trained models or customize tools to suit specific business needs. All this can do without the need for machine learning expertise.
Which AIaaS solutions companies are active and performing better?
When deciding on AI services, it is important to consider the goals, the size of the business, and the budget available. In addition, you need to evaluate the technical capabilities of your teams and the amount of data you need to process.
The following are some of the most important companies in the field of AIaaS services:
Google Cloud ML
MonkeyLearn is an artificial intelligence platform that simplifies text analysis through visual tools without code. The platform allows the consumer to begin their journey with a pre-trained model, such as a survey analyzer, to categorize customer feedback on a specific topic, or allows custom machine learning models to identify emotions, keywords, and Create topics in the data and then integrate the models with your favorite applications through point-and-click integrations or the API. Finally, run your models in MonkeyLearn Studio to build powerful dashboards and provide practical insights.
2. IBM Watson
IBM Watson is hosting a suite of artificial intelligence tools to help large companies better use their data. This efficient suite provides access to various pre-built applications such as Watson Assistant (for building virtual assistants) and Watson Natural Language Understand (for advanced text analysis tasks).
Developers can use IBM Watson Studio to build, train, and deploy machine learning models in any cloud. It is necessary to explain that no specialization in machine learning or data science is required in this field.
3. Microsoft Azure
Azure is Microsoft’s public cloud computing platform. As one of the giant players, AIaaS offers developers a range of AI and machine learning solutions. With Azure Cognitive Services, you can add various AI capabilities (such as computer vision or text extraction) to your applications using the API.
In addition, you may want to use the Azure Bot Service, which allows you to create any bot visually. This bot can be a responsive or virtual assistant for your brand.
4. Google Cloud ML
Google Cloud ML Engine Google’s artificial intelligence platform is a powerful infrastructure for creating and deploying machine learning projects. The platform helps data scientists and developers work with big data easily. With AutoML, you can teach custom machine learning models for text analysis, image classification, translation, and more.
You can visualize your dataset to see how your model performs using a wat-if-tool and get performance metrics. One of the advantages of using this platform is that you can easily integrate your models with the Google Cloud ecosystem.