If large language models are so powerful, why can they still get basic things wrong? In this episode, we take a practical look at how AI systems actually work, why hallucinations happen by design, and what’s being done to reduce them. We break down core concepts like probabilistic prediction, chain-of-thought reasoning, RAG systems, context windows, API orchestration, and cost structures. Not from a tech hype lens, but from a business one. Most importantly, we explore what this means for seafood companies integrating AI into real workflows: how to think about reliability, data access, governance, and long-term cost before plugging models into sensitive systems. This isn’t about whether AI will matter but about how to use it responsibly at scale. 

For more aquaculture insights head to our Fish n’ Bits blog.