Generative Now | AI Builders on Creating the Future

Sarah Guo and Elad Gil: The Future of AI Investing

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1. Investing in early machine learning companies that were ahead of their time can lead to success with proper timing and patience, as seen in investments like Base 10 and Inflection.
2. The evolution of AI is characterized by waves of human capital, transitioning from foundational models to infrastructure experts to B2B app developers, with future waves focusing on consumer apps and enterprise adoption.
3. The trend of funding for large AI models peaked in 2023, leading to potential shifts in venture funding towards more unique and innovative companies in 2024.
4. Software democratizes capabilities in the AI industry and beyond, with a focus on collaborative workflows catering to individual contributors within large enterprises.
5. The modern AI stack presents significant opportunities for enterprise growth, enabling new applications and workflows, particularly beneficial for small businesses targeting SMBs.
6. AI automation can lead to significant growth for small businesses with minimal employees and presents growth opportunities for startups catering to SMBs by providing AI tools or tailored products and services.
7. Automating data analytics processes through natural language queries faces resistance in some segments, with differing levels of interest in automation based on organizational structures and incentives.
8. Founders in the AI industry are dedicated but should maintain realistic expectations of AI's impact on reducing engineering team sizes in businesses.
9. AI is expected to impact certain verticals in SMBs, displacing jobs and expanding markets, although the current impact on areas like code generation may be overstated.
10. Efficient communication with executives involves brief calls and texts, emphasizing the importance of simplifying communication and the rising demand for communication automation.

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