A Quick Survey of Cloud Service Providers' AI offerings
Taking a closer look at some cloud AI and ML services from the top cloud computing vendors
The market research firm Fortune Business Insights projected that the worldwide AI market will reach a size of over 1.39 trillion U.S. dollars by 2027. Just last year, 2021, the global market size was USD 328.34 billion. The research also suggested that the market will grow to over 1.5 trillion U.S. dollars by 2030.
Indeed, we see a growing number of cloud providers providing the building blocks of artificial intelligence and machine learning services. They offer AI- and ML-based services that firms, or third-party technology companies, can build into their applications. These AI modules include image recognition, image processing, document processing, translation, analysis, and classification.
It's common for AI services to not need to be end-to-end processes, and many don't. Instead, they provide functionality that may be costly or complex for a firm. However, many processes could involve large-scale migration of data which could be subject to privacy policy or regulation, but now they can be performed without compromising the firm’s security or regulatory requirements as well.
“General-purpose” technologies are ones that you can share with others. Business applications have numerous uses, including financial management, project management, human resource management, business analysis, project planning, sales forecasting, and supply chain management. Most focus on back-office operations. But the AI industry becomes increasingly mature, and the range of AI services offered in the cloud is wide and growing.
Microsoft Azure offers Azure AI, which includes vision, speech, language, and decision-making AI models that you can use with AI calls. Microsoft has a wide variety of offerings for Artificial Intelligence Services, Cognitive Services, Machine Learning, and AI Infrastructure.
Google offers Vertex AI, which includes artificial intelligence, virtual assistant, machine learning platforms, data science services, speech-to-text, and voice search, to name a few. Google Cloud Inference API gives companies a way to work with large datasets that are stored in Google’s cloud. The firm, unsurprisingly, provides cloud GPUs.
Amazon Web Services (AWS) provides a wide range of AI-based services, including image recognition and video analysis, translation, conversational AI for chatbots, natural language processing, and a suite of services for developers. Amazon Web Services also promotes its health and industrial modules.
NVIDIA has released a cloud-based metaverse platform - NVIDIA Omniverse Cloud. It is an infrastructure-as-a-service that connects Omniverse applications running in the cloud, on-premises, or on edge devices. You can create and collaborate on 3D workflows without the need for local computing power. And you can use AI to train, simulate, test, and deploy intelligent machines. Autonomous vehicle engineers can generate physically based sensor data and simulate traffic scenarios to test a variety of road and weather conditions for safe self-driving deployment.
Despite Nvidia's deep learning relying on GPU acceleration, Intel's AI solutions look beyond the GPU with Intel Xeon Scalable processors. While GPUs are impactful for training, AI deployment requires more.
Oracle offers enterprise software and cloud services that help you develop conversational AI applications. They also provide AI technologies and services for developing conversational AI applications. You've never used a virtual assistant before? Well, if you do want to see how it works, check out Oracle Digital Assistant. This fully native, cloud service runs on Oracle Cloud Infrastructure (OCI). Oracle also offers out-of-the-box chatbots for enterprise horizontal business processes, such as CRM, ERP, SCM, HR, eCommerce, customer service, and field service.
SaaS companies and enterprise software vendors have their own AI offerings. Salesforce, Oracle, and IBM have a wide variety of tools, from ML and predictive analytics to computer vision and NLP. These are some of the most powerful cloud-based tools. IBM has even created a specific set of AI-powered tools (Watson Studio and Watson Services) to help organizations understand their environmental risk.
Conclusion
The demands for AI services rise in all sectors of business. According to the research, the worldwide market for contact center software reached about $27 billion in 2021, a figure expected to nearly triple to $79 billion by 2029, according to Fortune Business Insights. This increase is due to the benefits that customized voice applications offer businesses of any size, in almost every industry — from global enterprises to original equipment manufacturers delivering speech AI-based systems and cloud services, to systems integrators and independent software vendors. Integration of various AI services would be the next challenge for the years to come.
About the Author
Arthur Wang