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OpenAI's offer of credits to YC startups for equity is a strategic move. It gives them direct sight into promising AI companies, allowing them to track usage, identify breakout successes, and potentially acquire or compete with them, effectively using the ecosystem for R&D.
OpenAI embraces the 'platform paradox' by selling API access to startups that compete directly with its own apps like ChatGPT. The strategy is to foster a broad ecosystem, believing that enabling competitors is necessary to avoid losing the platform race entirely.
Investments in OpenAI from giants like Amazon and Microsoft are strategic moves to embed the AI leader within their ecosystems. This is evidenced by deals requiring OpenAI to use the investors' proprietary processors and cloud infrastructure, securing technological dependency.
The partnership where OpenAI becomes an equity holder in Thrive Holdings suggests a new go-to-market model. Instead of tech firms pushing general AI 'outside-in,' this 'inside-out' approach embeds AI development within established industry operators to build, test, and improve domain-specific models with real-world feedback loops.
To secure a foundational customer like OpenAI, capital-intensive infrastructure startups like Cerebrus may have to offer extremely generous terms, including massive, near-free equity stakes. This "deal they had to take" dynamic is necessary to overcome the cold start problem and achieve scale, demonstrating the immense leverage held by large AI model companies.
The recent surge in demo days and YC-style incubators from major VCs is a delayed reaction to the valuation boom of two years ago. These programs are a strategic play to get cheap, early-stage access to a wide portfolio of AI companies, de-risking entry into a hyped and uncertain market where good ideas are hard to differentiate.
In an unusual strategy, OpenAI provides its latest models to direct competitors. The company believes that a more competitive market accelerates learning and pushes them to improve faster. This long-term view prioritizes the overall distribution of intelligence over short-term competitive moats.
Current unprofitability in some AI applications, like subsidizing tokens for coding, is a deliberate strategy. Similar to Uber's early city-by-city expansion, AI labs are subsidizing usage to rapidly gain market share, gather data, and build a powerful flywheel effect that will serve as a long-term competitive moat.
NVIDIA funds OpenAI's compute purchases (of NVIDIA chips) with an equity investment. This effectively gives OpenAI a discount without lowering market prices, while NVIDIA gains equity in a key customer and locks in massive sales.
Massive investments, like Amazon's potential $50 billion into OpenAI, are not simple cash infusions. A large portion is structured as compute credits, meaning the money flows back to the investor's cloud services (e.g., AWS). This model secures a long-term, high-volume customer while financing the AI lab's operations.
OpenAI's deals with suppliers like Cerebrus and CoreWeave involve taking significant equity stakes in exchange for large purchase commitments. This strategy effectively turns OpenAI into a powerful venture capital entity, securing its supply chain while also building a valuable investment portfolio at an incredibly low cost basis.