RapidFire AI is a new way to build and customize AI for your use cases—faster, cheaper, and more accurately. We call it rapid experimentation: run 10x more model configurations to optimize for accuracy, cost, and latency—at half the GPU spend. With RapidFire AI, you can train multiple models in parallel across your entire cluster, exploring multiple configuration knobs together—hyperparameters, model architectures and even data tensorizations. Real-time controls let you kill, clone, or modify configurations on the fly. You get full visibility and control over every experiment, while the system automatically optimizes GPU usage. RapidFire fits seamlessly with your existing tools—like PyTorch, Jupyter, and Hugging Face—with no disruption or complex setup. Just smarter, faster AI development.
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The Outer Loop: The Real Driver of AI Success
June 27, 2025
This blog post was originally published in expanded form at RapidFire AI’s website. It is reprinted here with the permission of RapidFire AI. When people talk about deep learning, they usually talk about the inner loop—the elegant dance of forward passes, backpropagation, and gradient descent. This is the part that’s been endlessly refined over the […]
