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How the Cloud is Powering the Growth of Artificial Intelligence Featured

How the Cloud is Powering the Growth of Artificial Intelligence "Powerful man"

The convergence of public cloud providers and artificial intelligence (AI) innovation is responsible for the development of powerful new applications and services. Some of these products, such as personal assistants Siri or Alexa, are designed to be used by individuals to streamline daily activities. They demonstrate some of the power inherent in AI in apps backed by the big data resources available in the cloud.

More complex AI solutions are appropriate for use by data-driven businesses intent on increasing productivity and thriving in a competitive market. Several factors make the cloud a logical choice for the development and implementation of these products and services. These factors are driving growth for both cloud and AI solutions. 

  • Availability of affordable hardware resources - Cloud service providers (CSPs) have the storage, compute, and network capacity required by data-intensive AI applications. Training machine learning systems requires extensive resources not available at most companies. An example is the use of the Graphical Processing Units (GPUs) which are necessary for deep learning solutions. These expensive items may be difficult to justify in the IT budgets of many businesses that can benefit from machine learning solutions.  
  • Scaleability - The availability of virtually unlimited resources without capital expenditures is appealing to businesses interested in taking advantage of AI. Companies can test solutions on a limited basis and rapidly scale them up after determining if they address business objectives. Cloud vendors provide fertile ground for developing business-oriented AI applications. 
  • Experienced technical resources - Many companies lack the in-house technical expertise to implement productive AI systems. Using the CSP’s personnel enables companies of any size to investigate the benefits of AI for their business.  

AI as a Service (AIaaS)

Cloud providers are interested in technical innovation as well as increasing their profitability. Vendors have flourished by offering customer-tailored solutions that effectively address business issues. AI as a Service (AIaaS) is one way CSPs are bringing the power of AI to anyone. 

Following are a few AIaaS offerings currently available from major cloud providers. 

  • Google Cloud Machine Learning offers a variety of AI solutions designed to enable customers to quickly build, deploy, and scale effective models. The company recently introduce Vertex AI which offers a unified machine learning platform that includes all the tools organizations needed to develop productive applications. 
  • Microsoft Cognitive Services provides users with customizable, pre-trained models that put AI within reach of every developer and data scientist. Advanced decision-making capabilities can be embedded in customer applications via an API call. 
  • Amazon Machine Learning provides the support necessary for small businesses to reap the benefits of machine learning solutions. Industry-specific solutions are available to personalize and enhance the customer experience. 
  • Alibaba’s Machine Learning Platform for AI makes AI accessible to any customer by providing end-to-end machine learning services. Some uses of the platform include the ability to perform news classification, product recommendation, and financial risk management.  

The emergence of AIaaS allows virtually any organization to reap the benefits of AI, democratizing the technology and paving the way for accelerated innovation. As more users become familiar with the potential of AI, we can expect a steady flow of new products and services built around machine learning and artificial intelligence. 

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 Robert Agar

I am a freelance writer who graduated from Pace University in New York with a Computer Science degree in 1992. Over the course of a long IT career I have worked for a number of large service providers in a variety of roles revolving around data storage and protection. I currently reside in northeastern Pennsylvania where I write from my home office.

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