ReLU, commonly used in neural networks, is not differentiable at zero but it's still able to be approximated by expressions that are efficiently FHE-evaluable. You don't truly care about differentiability here, if you're being pedantic.
Very insightful comment, though. LLMs run under FHE (or just fully local LLMs) are a great step forwards for mankind. Everyone should have the right to interact with LLMs privately. That is an ideal to strive for.
Comments
ReLU, commonly used in neural networks, is not differentiable at zero but it's still able to be approximated by expressions that are efficiently FHE-evaluable. You don't truly care about differentiability here, if you're being pedantic.
Very insightful comment, though. LLMs run under FHE (or just fully local LLMs) are a great step forwards for mankind. Everyone should have the right to interact with LLMs privately. That is an ideal to strive for.