Cloud Computing a Key Component for Generative AI


The emergence of generative artificial intelligence (AI) has changed a lot about the way organizations do business. These models, including the popular ChatGPT, are computationally intensive. Training and running these models require vast amounts of memory and computing power, which is causing a demand for cloud-based resources. Cloud computing platforms have become a key component in an organization adopting and maximizing generative AI solutions.

Scalability is a term that has been associated with cloud computing since its inception. Cloud computing platforms offer the scalability required to train and deploy generative AI models. The demands of AI applications change often, so having the ability to quickly scale up or down is key to efficiency. Running natural language processing, image generation, and other AI-driven functions is still a little unpredictable when it comes to computing resources.

Cloud computing services provide low-latency and high-throughput capabilities required to run AI models in real-time, which is one of the most key features to AI. They offer pay-as-you-go pricing models, so you are only paying for resources when they are needed, reducing upfront hardware costs.

Generative AI is just the next technological advancement driving the demand for cloud computing resources due to its computational intensity and scalability requirements. Just another example of how organizations need to be running their main software applications on the cloud to position themselves to take advantage of modern solutions as they become available.

Where are you with your cloud adoption journey? 2W Tech is one of Microsoft’s most innovative partners and rely on Microsoft Azure to power our innovation, not to mention keeping our large client base’s applications running smoothly. If you are interested in learning more about the partnership between generative AI and Microsoft Azure, give our team a call today.

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