CPU vs GPU for AI: most AI applications don't need GPUs 🧠

1. 1Evaluate your AI application's requirements to determine if a GPU is necessary
2. 2Assess your existing CPU infrastructure to see if it can handle AI workloads
3. 3 Architect AI into your existing workflow to minimize extra overhead
4. 4Compare the costs of CPU vs GPU infrastructure for your specific use case
5. 5Test your AI application on CPU infrastructure to validate performance

DevOps and software engineers can benefit from this insight to optimize their AI infrastructure and reduce costs, while product managers can use it to inform their technology roadmap

💡 CPU infrastructure can handle most AI workloads, reducing the need for expensive GPU infrastructure

💡 Most AI apps don't need GPUs! Simplify deployment and reduce costs by leveraging CPU infrastructure