The author concludes by stating that while it's interesting to theorize about the future of AI, the only way to truly understand its potential is to build AI companies. The author invites feedback and thoughts on the ideas presented in the article and expresses excitement about partnering with founders in the AI space.
Key takeaways:
- The author discusses the potential of large language models (LLMs) and the opportunities they present for startups. She believes that while not all incumbent companies will be disrupted by new startups, some are more likely to be disrupted than others.
- She highlights several areas where LLMs could have a significant impact, including developer tooling platforms, augmenting knowledge workers, digital asset generation, personal assistant & coach, and SaaS replacements. However, she expresses skepticism about the potential of LLMs to disrupt incumbent companies in areas like general consumer search and running large models locally.
- The author also discusses the potential of infrastructure-related startups, such as those providing compute & software for model training/fine-tuning/inference, new ML frameworks and/or chips, observability, vector databases, and privacy or quality-related middleware.
- She concludes by emphasizing the importance of building and trying out new AI companies to truly understand their potential and invites feedback on her thoughts.