What are gradient inversion attacks, and why do they threaten federated learning?
Federated learning transmits gradients, not raw data. The catch: a gradient is derived from the data, so it carries the data. The signal is knowing why 'we only share gradients' is not a privacy guarantee. Here is the answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Federated learning transmits gradients, not raw data. The catch: a gradient is derived from the data, so it carries the data. The signal is knowing why 'we only share gradients' is not a privacy guarantee. Here is the answer.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
