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AI Infrastructure PODs play a vital role in addressing the challenges and opportunities presented by the increasing adoption of AI. They offer a comprehensive, scalable, and performance-optimized solution that simplifies AI deployments and empowers organizations to unlock the full potential of AI across various applications and industries.
Specifically focused on Inferencing, 💡AI inferencing is the process of using a trained artificial intelligence model to make predictions or decisions based on new, unseen data. So after you train a model you need to use the model. That is inferencing.
Cisco’s AI Infrastructure PODs are pre-configured, validated bundles designed for various AI and ML use cases. These PODs offer different CPU, GPU, and memory resource configurations to meet specific workload requirements. Here’s a breakdown of the four configurations and their intended use cases:
Cisco’s AI Infrastructure POD Configurations and Use Cases (Comparison Graph)
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Factors Influencing POD Selection
The choice of POD configuration depends on several factors, including:
- Model Size and Complexity: Larger, more complex models require more computational resources, typically provided by higher-end GPUs and more memory.
- Performance Requirements: Applications requiring real-time responsiveness necessitate PODs with optimized performance characteristics, such as low latency and high throughput.
- Scalability Needs: Organizations anticipating growth in AI workloads should opt for PODs that can scale dynamically by adding or removing resources as needed.
- Use Case Specificity: Different use cases, such as edge inferencing, 💡Retrieval-Augmented Generation (RAG), which leverages knowledge sources to provide contextual relevance during a query, or large-scale model deployment, have distinct requirements that influence POD selection.
Cisco’s AI Infrastructure PODs provide a flexible and scalable foundation for diverse AI workloads. By understanding each POD’s specific configurations and intended use cases, organizations can choose the optimal solution to accelerate their AI initiatives and unlock the potential of this transformative technology.
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Sources:
AI PODs for Inferencing Data Sheet
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