Silicon Data’s Pitch to Make AI Costs Predictable

When Chinese AI startup DeepSeek claimed it had trained a GPT-4-class model for just $6 million, the AI community was quick to express skepticism. A 67-billion-parameter model developed for a fraction of what OpenAI or Google might spend? Unlikely, many, including Elon Musk, argued. Yet whether the number was accurate or inflated almost didn’t matter. The deeper problem was that no one could say with certainty what a model like that should cost to build in the first place. AI has become one of the most resource-intensive technologies in history, but the financial infrastructure underpinning it remains opaque and unstructured. As companies pour billions into training frontier models and building out data center infrastructure, there's a fundamental lack of transparency around core inpu