Krutrim Offers "GPU as a Service" for Enterprises and Developers

Krutrim, the AI company founded by Bhavish Aggarwal has launched a GPU-as-a-service (GaaS) offering as a part of its comprehensive AI solutions. This offering is particularly beneficial for enterprises and developers who need GPU resources for training and fine-tuning machine learning models. And, it also aligns with the broader goal of Krutrim to develop an indigenous computing stack for India, including semiconductors and GPU levels, to create Large Language Models (LLMs and innovative AI applications. 

Krutrim has enabled users to access powerful computational resources without the need to invest in dedicated hardware by offering GPUs as a service,. This flexibility can significantly accelerate model development and experimentation.

What is GPU as a Service (GaaS)?

GPU as a Service is a cloud-based solution that offers on-demand access to high-performance graphics processing units (GPUs) for various applications. It is useful for applications that require significant computational power such as machine learning, deep learning, data processing, high-performance computing, gaming, and virtual reality.

Some of the benefits of using GPU as a Service (GaaS) include:

• Users can easily adjust GPU resources based on their project requirements.
• Allows organizations to only pay for the GPU resources they consume, eliminating the need for costly upfront investments in hardware
• GaaS platforms typically feature intuitive web interfaces, making it simple for users to set up their GPU resources.
• GaaS providers implement robust security measures to safeguard customer data and ensure compliance with industry regulations.

Conclusion

With its offerings, Krutrim plans to provide cost-effective and accessible AI solutions by training models on Indian datasets. Krutrim’s GPU as a service offering is a strategic move to enhance computing capabilities, support AI research and development, and empower Indian developers, startups, and research institutions with affordable GPU resources.