This episode explores the evolving landscape of AI model training data acquisition and talent assessment, featuring Brendan Foody, CEO of Mercor. Against the backdrop of Mercor's rapid growth in recruiting individuals to train AI models, the discussion delves into the skills currently sought by leading AI labs—ranging from software engineering to specialized expertise in various fields. More significantly, the conversation highlights Mercor's use of LLMs to predict job performance more effectively than human recruiters, identifying outliers and high-performing individuals across diverse industries. For instance, the power law distribution of talent in fields like investing is contrasted with more evenly distributed skills in other sectors. As the discussion pivoted to the future of work, concerns regarding job displacement due to AI automation were raised, along with potential solutions involving retraining and adaptation to new roles. Finally, the episode concludes with insights into the importance of developing robust evaluation methods for AI models, particularly as they approach superhuman capabilities, and the crucial role of human expertise in creating and validating these evaluations. This means that the future of work will likely involve a hybrid model of human and AI collaboration, with humans focusing on tasks requiring nuanced judgment and creativity.
