Topics In Demand
Notification
New

No notification found.

Maximising Cost Efficiency in AI Deployments
Maximising Cost Efficiency in AI Deployments

February 23, 2024

AI

28

0

For any business, finding ways to reduce costs while maintaining high performance is crucial. This is especially important for AI, where finding ways to optimise efficiency and reduce expenses without sacrificing output quality is key to staying competitive and innovative. Here's an overview of how leveraging versatile AI solutions can lead to genuine cost savings.


Cloud Flexibility and Cost-Effectiveness

These AI solutions are engineered for versatility, allowing deployment on-premises, in the cloud, or at the edge. In contrast to typical cloud providers, the emphasis isn’t on driving up your infrastructure costs. The solutions are validated for peak performance, with extensive benchmarking showing considerable cost and time reductions in training with CPUs and GPUs This flexibility ensures you’re not locked into expensive infrastructure, making your AI journey both efficient and cost-effective.

 

Accelerated Productivity of Data Science Teams

One of the key challenges in AI development is the extensive manual effort required from data science teams. This challenge is met by integrating best-in-class open-source frameworks and tools, streamlining the development process. AI platform features like one-click deployment and easy access to distributed computing resources, like Dask or Ray, reduce what used to take months into mere seconds. This not only saves time but also drastically cuts down on provisioning and operational costs.

 

Consumption-Based Billing

The billing model is designed around your usage patterns, allowing you to start and stop services as needed. This approach means you only pay for what you use, avoiding charges for idle resources. This stands in stark contrast to traditional cloud services, which often charge for resources regardless of actual usage.

 

GPU Sharing and Auto-Scaling

A Kubernetes-native platform facilitates efficient GPU sharing within an organisation, allowing multiple notebooks to utilise a single GPU. This, combined with autoscaling for both GPUs and CPUs, ensures resources are optimally used without incurring unnecessary costs. Unlike other cloud services, where GPU sharing can be restricted or complicated, this approach simplifies resource allocation, providing both flexibility and cost savings.

 

Seamless Deployment and Monitoring

Deploying AI models using this approach offers the flexibility of horizontal or vertical scaling with the ease of starting and stopping services as required. The system automatically provisions additional GPUs when demand exceeds supply and releases them when no longer needed. This level of automation extends to monitoring, offering detailed insights into resource consumption at the node level, enabling precise optimisation of deployment strategies.

 

Conclusion

An AI platform is a comprehensive solution designed to maximise cost efficiency and operational productivity for organisations at any scale. By leveraging cloud flexibility, accelerated productivity, consumption-based charges, GPU sharing, and auto-scaling, businesses can achieve significant cost savings and efficiency gains. Begin your AI journey with this approach to revolutionise how you deploy, monitor, and scale your AI and ML projects, ensuring that your investments are as effective as they are efficient.


That the contents of third-party articles/blogs published here on the website, and the interpretation of all information in the article/blogs such as data, maps, numbers, opinions etc. displayed in the article/blogs and views or the opinions expressed within the content are solely of the author's; and do not reflect the opinions and beliefs of NASSCOM or its affiliates in any manner. NASSCOM does not take any liability w.r.t. content in any manner and will not be liable in any manner whatsoever for any kind of liability arising out of any act, error or omission. The contents of third-party article/blogs published, are provided solely as convenience; and the presence of these articles/blogs should not, under any circumstances, be considered as an endorsement of the contents by NASSCOM in any manner; and if you chose to access these articles/blogs , you do so at your own risk.


Katonic AI is an end-to-end enterprise AI solution for businesses. Its no-code Generative AI Platform built on top of its highly awarded Katonic Machine Learning Operations (MLOps) platform allows businesses to manage the entire process of data preparation, model training, model deployment, model monitoring, and end-to-end automation with high accuracy,reliability, and efficiency.

© Copyright nasscom. All Rights Reserved.