When training a model that, for example, is designed to make recursive calls and use tools, I suspect that it will need to be able to do so during training, at which point the difference between training and deployed internally is far less clear.
And it seems functionally impossible to do air-gapped training of systems that are being trained to query web data sources, ask for feedback from users, and/or write code that calls external APIs, for obvious the reason that they need to be connected to external systems.
When training a model that, for example, is designed to make recursive calls and use tools, I suspect that it will need to be able to do so during training, at which point the difference between training and deployed internally is far less clear.
And it seems functionally impossible to do air-gapped training of systems that are being trained to query web data sources, ask for feedback from users, and/or write code that calls external APIs, for obvious the reason that they need to be connected to external systems.