Artificial intelligence (AI) is playing a significant role in driving advancements and innovation in cloud computing. This interesting topic came to us from Barron’s in their article, “AI Is Driving an Uptick in Cloud Computing Demand. Good News for Amazon.”

AI technologies, such as machine learning and natural language processing, are used to automate various tasks in cloud computing. AI-powered automation enables intelligent resource allocation, automatic scaling and dynamic provisioning of cloud resources based on workload demands. This helps optimize resource utilization, improve efficiency, and reduce costs. These advancements are transforming the cloud computing landscape, improving efficiency, reliability, and user experience in cloud-based services.

The biggest challenge is that most organizations have little knowledge on how AI systems make decisions and how to interpret AI and machine learning results. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact, and its potential biases. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Data Harmony, harmonizing knowledge for a better search experience.