This podcast episode explores the differences between small language models (SLMs) and large language models (LLMs) and discusses the advantages of leveraging SLMs for specific tasks. It delves into the concept of SLMs and LLMs, highlighting the trade-offs between the two types of models. The implementation of AI chips and the open-source nature of SLMs are also discussed. The conversation emphasizes the importance of metrics in evaluating AI models and suggests that engineers should use AI as a complementary tool to enhance the user experience. The episode concludes with discussions on the transformative experience of transitioning from an engineer to a team leader and the impact of AI tools in various fields. Overall, this podcast provides insights into the potential of SLMs and AI in different domains.
