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The Intersection of Cloud Computing and AI: How SaaS Platforms are Changing the Game Using AWS & Azure

There is more and more noise in the media about artificial intelligence (AI), and it is quickly becoming part of the mainstream. The cloud is becoming increasingly important in the development and deployment of AI applications, particularly with the rise of AI services as a platform.


The two biggest global cloud providers Amazon (AWS) and Microsoft (Azure) have both invested heavily in AI and have AI service offerings as a turn-key option.

AI SaaS systems enable businesses to rapidly access and deploy AI algorithms and models without investing in the massive upfront costs required to construct and maintain their platforms. AI is now available at an affordable cost to all sizes of business, this has sped up their use and adoption. 

To get the most out of your AI applications, you need a cloud management platform that is specifically designed to handle the unique challenges of AI workloads.

What are the three top challenges and how can cloud management software help?

The most difficult aspect of managing cloud resources for AI is optimising the use of GPUs (graphics processing units), which are critical in expediting AI training and inference workloads. GPUs are highly specialised and expensive pieces of hardware, and ensuring that they are utilised properly across all of an organization's AI workloads can be tough. A cloud management platform tailored for AI workloads can assist organisations in optimising GPU usage, assuring the optimum performance and value from these crucial resources.

Another difficulty in managing cloud resources for AI is cost management. AI workloads can be highly unpredictable in terms of resource utilisation, making cost prediction and control problematic. A cloud management platform tailored to AI workloads can assist organisations in monitoring and optimising resource utilisation, allowing them to make more educated decisions about where to deploy resources and how to limit expenses.

A cloud management platform can assist organisations in ensuring that their AI workloads fulfil performance and reliability standards. AI workloads can be extremely sensitive to performance concerns, and any downtime or loss in performance might have serious effects. A cloud management platform intended for AI workloads can assist organisations in monitoring and optimising performance, ensuring that their AI workloads function smoothly and reliably.

The world is changing and AI is starting to become a service available to SMEs. How far through the adoption curve we are is up for debate, but in my opinion, we are at the start of this process.

Just look at the rollout of ChatGPT and Bard and the controversy surrounding them. Now play that across thousands of entry and mid-level white collar jobs in the legal and finance sectors disappearing because AI software can automate them away.

Is this the start of a wave of change that ripples across the way we work over a generation or faster? We are living in interesting times as the saying goes, and no one knows where this will all end. Will it change things beyond all recognition like the industrial revolution or will it evolve things like the introduction of computers in the work place.

Your business can ensure that your cloud usage is efficient and the cost managed by using a cloud management platform. This can set your team free from the day to day activities of cloud management so they can focus on building software applications for your customers and using AI in the cloud.

At IG CoudOps we have worked with several independent software vendors at the cutting edge of this new technology horizon and we have the experience of how to manage that cloud infrastructure with our cloud management platform CloudOps. ore speak to one of our consultants and find out how we canhelp.

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