40 Trillion Tokens a Day (Yes, More Than OpenAI) | Lin Qiao, CEO of Fireworks
The discussion centers on the industry shift from general-purpose AI models (like those from OpenAI/Anthropic) toward specialized intelligence. Lin Qiao of Fireworks argues that true innovation lies in leveraging proprietary, locked-in enterprise data—the 'alpha'—to build customized models. She asserts that this specialization is necessary because generalized models cannot capture a company's unique knowledge or judgment. Technically, the conversation details advanced training methods (SFT, DPO, KTO, RL) and emphasizes platform control, noting that Fireworks achieves bitwise equivalence between training and inference results to ensure maximum quality while optimizing for cost and speed.
Key takeaways
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The Rise of Specialized Intelligence
1:08:55
Lin Qiao argues that the future belongs to specialized intelligence—customized models built on private company data—rather than general-purpose AGI. She believes every company is unique, making it difficult for a single general model to capture proprietary knowledge (41:35).
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Fireworks' Scale and Focus
22:16
Fireworks claims to process over 40 trillion tokens daily, stating that 95% of this traffic comes from customized model inference deployment, not off-the-shelf APIs. This volume surpasses both OpenAI API and Gemini API usage (13:36).
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Open vs. Closed Models for Security
1:18:20
Lin Qiao suggests that open models are better suited to strike a balance in the security debate, encouraging broader community participation to increase defensive complexity against potential cyber threats (47:00).