Analysis of the "tidal waves" sweeping over the VC landscape. The post examines how some of the macro trends + rapid advancements in AI are reshaping the venture & startup ecosystem, which include:
- The impact of increasing fund sizes on returns (and why a $500M fund might need to generate $17.5B in exit value to 3X).
- Novel strategies in which data science and AI can be applied in the VC investment process.
- How VC, traditionally a “cottage industry”, is becoming more high-frequency
As well as some predictions on where the industry might be headed:
- How Solo GPs and smaller/nimbler firms could harness AI to rival much larger investment platforms.
- The transformation of VC into a more traditional asset class (but with a twist!)
- The potential re-emergence of ‘calm funds’ in a world of capital-efficient, AI-native startups
- The changing role of CVCs and cloud hyperscalers in startup investing, and why massive funding rounds in foundation model startups probably won’t continue
Would love thoughts & feedback from the community!
Excited to share my thoughts on "model collapse". As the internet becomes increasingly filled with machine-generated data, I explore whether we are at “Peak Data”, how that might affect the efficacy of large language models & applications like ChatGTP going forward, as well as possible solutions that players at the foundation model & data layer might use to adapt to this new world.
Assuming startups like Etched (with its recent massive funding) could shrink CapEx quite a bit (and make it not such a large revenue shortfall)