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Building LLMs is probably not going be a brilliant business

Nov 26, 2024 - calpaterson.com
The article discusses the profitability of large language model (LLM) makers like OpenAI, Anthropic, and Gemini, comparing their industry structure to that of airlines and fizzy-drink companies. The author argues that despite the technological advancements and potential future of LLMs, the industry structure is unfavorable for profitability. Factors such as the dominance of NVIDIA as a supplier, high buyer power, strong competition, and the threat of new entrants and substitutes make the business model challenging.

The author also questions the recent massive funding rounds of companies like OpenAI, suggesting that while they might be planning strategies to mitigate some of these challenges, the overall industry structure still poses significant risks. The article concludes by differentiating between technology success and business success, implying that while LLM technology might advance, it doesn't guarantee the profitability of the companies developing them.

Key takeaways:

  • The profitability of a business is determined by its industry structure, not by efficiency, hard work, or innovation.
  • Large language model (LLM) makers like OpenAI, Anthropic, and Gemini face a challenging industry structure, with a single powerful supplier (NVIDIA), high buyer power, strong direct competition, and easy entry for new competitors.
  • Despite these challenges, LLM makers are raising significant amounts of money, with OpenAI recently raising $6.6 billion at a valuation of $157 billion.
  • While the future of LLM technology is promising, the profitability of companies building these models is uncertain, and the author suggests that AI businesses might be better off using models built by others rather than building their own.
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