Did you know that “85% of Americans use at least one of six products with AI elements” according to a Gallup survey? Whether you’re catching an Uber ride from the airport or listening to music on Spotify at the gym, you’re using applications with built-in AI technology. In addition, many of these AI applications also operate using cloud computing technology. Some of the world’s largest cloud providers implement AI in their SaaS offerings for enterprises to use for strategic business purposes.
What is Artificial Intelligence?
Artificial intelligence (AI) is often a buzzword people toss around and use for multiple different meanings. According to Data Science Central, artificial intelligence is defined as “when machines carry out tasks based on algorithms in an ‘intelligent’ manner, that is AI.” But to completely understand AI, one must know two key components of AI – machine learning and deep learning.
The Relationship Between AI and Machine Learning
One common misconception is that AI and machine learning are the same thing. Machine learning is rather a subset of AI. Data Science Central defines machine learning as, “the ability of machines to receive a set of data and learn for themselves, changing algorithms as they learn more about the information they are processing.” Keep in mind that an algorithm is simply just a set of rules that are followed when trying to solve a problem. Cloud providers use machine learning to differentiate their SaaS products with deeper insights into customer behavior and richer user experiences.
Introduction of Deep Learning
Then there’s the concept of deep learning, which is a subset of machine learning. AWS defines deep learning as “a branch of machine learning that involves layering algorithms in an effort to gain greater understanding of the data.” Deep learning is also described as “deep neural networks” that contain many layers of artificial neurons, mimicking biology. Large amounts of historical data are required in order for deep learning algorithms to be able to identify relationships between the historical data and accurately recognize new data. Like machine learning, deep learning is relied upon in SaaS to find increasingly sophisticated patterns in increasingly large quantities of data.
Examples of Cloud Providers and Their AI Services
Four of the biggest cloud providers — AWS, Google Cloud, Alibaba Cloud, and Azure — all use artificial intelligence across multiple different SaaS offerings. In addition, all of these providers offer similar types of SaaS technology used for the same functionalities. Let’s preview a few of these cloud providers and how they use AI for their SaaS.
Amazon Web Services (AWS)
AWS uses AI as a service for businesses looking to save valuable time with customer inquiries. For example, AWS offers Amazon Polly, which is a service that turns text into lifelike speech. With Amazon Polly, customers can call a contact center to check for a variety of things such as an account balance, service status, address, and contact information. Through an algorithm, Amazon Polly records the customer’s response and through machine learning, it gathers the data that the customer was inquiring about. Then, the contact center relays a voice audio response back to the customer and provides the answer they were looking for. You’ve probably encountered this type of technology when calling your bank or a doctor’s office.
Google cloud offers their own AI tools and machine learning services for businesses. One example is their Dialogflow Enterprise Edition, which allows companies to deploy “chatbots” as a customer service tool when users browse on their website. Powered by Google machine learning, Dialogflow Enterprise Edition can “build conversational interfaces that can perform tasks such as following-up on past orders, scheduling appointments, answering common questions, or assisting a user with simple requests.” The implementation of Google Cloud’s Dialogflow can save a company and employees much needed time by having a bot answer simple questions or even used as a marketing tool to help complete customer purchasing orders.
The Azure cloud platform contains a large variety of tools companies can use for strategic business purposes. Azure’s AI cognitive services, similar to the other cloud providers, uses machine learning across the following APIs: vision, knowledge, language, speech, and search. For example, Azure’s vision API excels at face, person, and emotion recognition in images. Cloudinary, a SaaS cloud-based image and video management company, allows users to upload, store, manage, and deliver images and video for different websites or apps. Cloudinary uses Azure’s AI vision cognitive service to “accurately deliver face-based images and add precise facial detection capabilities.” Cloudinary allows companies to focus on their main operations without the need to have to build their own image and video management technology. With Cloudinary, companies can streamline the process of identifying facial images. Today, Cloudinary services are used by “over 120,000 web and mobile applications developers at more than 3,000 companies.”
Finally, Alibaba Cloud provides their own AI elements within their cloud computing technology. For example, Alibaba Cloud’s ET Brain offers their own suite of AI tools for businesses such as voice interaction; facial, image, and text recognition; and natural language processing. Alibaba’s ET City Brain is a deep learning system that “uses big data computing and deep neural networks to process massive logs, videos, and data streams from systems and sensors across an urban center.” With Alibaba Cloud’s ET City Brain, city officials can analyze real-time live streams from traffic cameras to monitor motor accidents and even improve daily commutes with the automation of traffic signals. Alibaba Cloud’s ET City Brain proves to be a driving force and an important one in an exponentially growing and dense population in China.
All of the largest cloud providers incorporate AI technology in their SaaS applications, many of whom offer similar APIs for businesses. Due to the phenomenon of machine and deep learning, these SaaS applications provide better solutions for businesses looking to operate more efficiently and strategically. Whether it’s streamlining time spent on customer inquiries or using precise facial recognition when dealing with massive amounts of images, AI is an important feature of cloud computing technology. As a cloud consulting firm, DoubleHorn offers companies support, migration, and a discount when looking to migrate to the cloud.