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A.I. Start-Ups Face a Rough Financial Reality Check

Apr 29, 2024 - news.bensbites.com
The artificial intelligence (AI) boom is proving to be a costly endeavor for tech start-ups, with several high-profile companies struggling to balance their enormous expenses with modest sales. Inflection AI, Stability AI, and Anthropic are among the companies that have faced financial pressure, with the former folding its original business and the latter two laying off employees and parting ways with executives. The development of generative AI, the technology behind chatbots like ChatGPT, requires billions of dollars, and even that might not be enough to compete with tech giants like Google, Microsoft, and Meta.

The cost of building AI systems has surprised industry veterans, with the cutting-edge chips required being expensive and in short supply. Over the past three years, investors have poured $330 billion into approximately 26,000 AI and machine-learning start-ups, according to PitchBook. This is two-thirds more than the amount spent funding 20,350 AI companies from 2018 through 2020. The AI revolution is expected to come with a hefty price tag, and tech companies are scrambling to figure out how to close the gap between their expenses and potential profits.

Key takeaways:

  • Several high-profile artificial intelligence start-ups are facing financial pressure, with some folding their original business, laying off employees, or struggling to close the gap between sales and expenses.
  • The development of generative A.I., the technology behind chatbots, requires billions of dollars, and competing with tech giants like Google, Microsoft, and Meta may not be feasible for many start-ups.
  • Investors have poured $330 billion into about 26,000 A.I. and machine-learning start-ups over the past three years, two-thirds more than the amount spent funding 20,350 A.I. companies from 2018 through 2020.
  • The cost of building A.I. systems has shocked tech industry veterans, with generative A.I. models costing billions to create and maintain due to the need for cutting-edge chips and the high cost of each A.I. system query.
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