Training Data Fireworks Founder Lin Qiao on How Fast Inference and Small Models Will Benefit Businesses
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Aug 13, 2024 
Lin Qiao, founder and CEO of Fireworks and former head of the PyTorch team at Meta, shares insights on the evolving landscape of generative AI. She discusses how her platform aims to democratize access to AI with fast, cost-effective inference using smaller models. Lin explains the challenges B2C companies face with latency and operational costs. She also predicts the convergence of open and closed-source models and highlights the importance of simple API access for diverse AI applications. Her vision could transform how businesses utilize AI technology.
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PyTorch Simplification
- At Meta, Lin Qiao simplified three machine learning frameworks (Caffe2, ONNX, PyTorch) into one.
- Initially, integrating frameworks proved too complex, leading to rebuilding PyTorch's backend for simplicity.
Embrace Backend Complexity
- Focus on simplifying the user experience by absorbing complexity on the backend.
- Fireworks aims to handle complex infrastructure so developers can focus on application innovation.
Scaling and Bankruptcy
- Scaling a successful AI product quickly can lead to bankruptcy if the cost structure isn't sustainable.
- Controlling Total Cost of Ownership (TCO) is vital for businesses, especially with GPU-based Generative AI.