In this episode of the Invest Like the Best podcast, Chetan Puttagunta and Modest Proposal delve into the evolving landscape of Large Language Models (LLMs). They explore the shift from pre-training to test-time compute as a new scaling strategy, highlighting its implications for investment in both public and private sectors. This transition not only reduces capital costs but also aligns expenses with revenue, making it easier for smaller teams to compete with larger labs in AI development. While they recognize the uncertainties that come with fast-paced technological changes, the conversation ends on a hopeful note, emphasizing the potential for ongoing innovation in application development and the exciting possibility of nearing Artificial General Intelligence (AGI) in the near future.
