In this episode of Disambiguation, co-hosted with Tom Pringle, we dive into the November edition of AI Pulse, where we explore the latest developments in AI, generative AI, and business automation. We discuss the current state of AI news, noting a slight decrease in dramatic headlines compared to previous cycles, which may indicate a maturation of the industry.

Tom shares insights from his recent work on language models, highlighting the emergence of industry-specific models from Microsoft and Google's new developments in large language models that mimic smaller models' efficiency. We delve into the concept of Relaxed Recursive Transformers (RPTs) and their potential to optimize resource usage.

The conversation shifts to the importance of model specificity, particularly in business processes, where tailored models can enhance productivity. We also touch on the intriguing idea of large behavior models (LBMs) that focus on understanding human emotions, which could revolutionize customer service interactions.

As we navigate through the implications of AI in business, we consider the balance between structured and unstructured activities, emphasizing the need for human creativity in decision-making processes. We also discuss the ongoing interest from venture capitalists in AI startups, with significant funding rounds indicating a robust future for AI innovation.

Overall, this episode provides a comprehensive overview of the current AI landscape, the challenges and opportunities it presents, and the critical role of human insight in leveraging these technologies effectively. Join us as we unpack these topics and more in our ongoing exploration of AI's impact on business.