20VC: Perplexity's Aravind Srinivas on Will Foundation Models Commoditise, Diminishing Returns in Model Performance, OpenAI vs Anthropic: Who Wins & Why the Next Breakthrough in Model Performance will be in Reasoning
This podcast episode explores the challenges and potential breakthroughs in the AI industry, with a focus on data curation, reasoning quality, models with memory, commoditization of foundation models, competition, talent retention, monetization strategies, building enterprise products, and startup challenges. The speakers acknowledge the importance of data curation in achieving optimal model performance and challenge the viewpoint on model verticalization. They discuss the trajectory of reasoning improvement and the value of advanced reasoning AI models. The section also delves into the potential commoditization of foundation models and the challenges of competing in the AI market. The speakers highlight the significance of talented individuals and the limitations of cash flow in poaching talent. They discuss building a business, monetization engines like ads, and the value of enterprise products beyond just the model itself. The section concludes with insights into the challenges and opportunities in building a company in the AI space, and the potential profitability of advertising. The impact of AI presentation, user intent, and contradictions in app design are also explored. Overall, the episode provides valuable insights into the AI industry and offers perspectives on various aspects of AI development and deployment.
