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Early days of AI

Aug 21, 2023 - blog.eladgil.com
The article discusses the evolution of AI and machine learning, highlighting the author's experience working with early ML systems at Google and Twitter. The author notes that until the rise of new AI architectures, most machine learning startups failed, with value going to incumbents over startups. However, the launch of GPT-3 in June 2020 marked a significant step up from prior models, suggesting the potential of what was to come. The author identifies four waves of AI adoption, including GenAI native companies, early startup adopters and fast mid-market incumbents, the next wave of startups currently being founded, and the first big enterprise adopters.

The author emphasizes that true enterprise adoption of AI is still many quarters or years away, as large enterprises are still trying to understand what AI means for them. Despite this, the author remains optimistic about the future of AI, citing Google’s MedPaLM2 model as an example of the potential impact of AI on industries such as healthcare. The author concludes by stating that we are only in the early days of AI, with both peak hype and peak impact still in the future.

Key takeaways:

  • The author argues that the rise of new AI architectures, particularly transformer-based and diffusion-model based approaches, marks a significant shift in the field of technology, akin to the invention of the airplane after cars.
  • There are likely at least four waves of AI adoption, starting with GenAI native companies and ending with the first big enterprise adopters around 2024/2025.
  • The launch of GPT-3 and GPT-4 marked significant advancements in AI, with GPT-3.5 solidifying the perception of transformer-based models as the future.
  • Despite the advancements, true enterprise adoption of AI is still many quarters/years away, as large enterprises are still trying to understand what "AI" means for them.
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