The podcast episodes discuss the increasing expenses involved in developing advanced AI models and systems, citing examples from major tech firms like Meta, Nvidia, and Moderna.
These costs are driven by factors such as the computational power and data required to train large language models, as well as the specialized talent and infrastructure needed to productize AI capabilities across an organization.
The episodes explore how these financial pressures are impacting strategic decisions and investments in the AI space, highlighting the tradeoffs companies face as they seek to maximize the potential benefits of AI while managing the associated costs.