How Critical Is Infrastructure In Llmops
Infrastructure is the backbone of LLMOps, providing the necessary computational power and storage capacity to train, deploy, and maintain large language models efficiently.
Areas of application
- Computer Vision
- Natural Language Processing
- Speech Recognition
- Recommendation Systems
- Predictive Analytics
Example
For instance, a company might invest in high-performance computing clusters or cloud-based services to support their LLMOps operations. These infrastructure investments enable them to handle massive datasets, train complex models quickly, and deliver real-time insights to users.