Basically it learns to call specific private APIs to insert data into a completion at inference-time. The framework is expecting to call out to the internet based on what's specified in the model's text output. It's a very small jump to go to more generic API connectivity. Indeed I suspect that's how OpenAssistant is thinking about the problem; they would want to build a generic connector API, where the assistant can call out to any API endpoint (perhaps conforming to certain schema) during inference.
Or, put differently: ChatGPT as currently implemented doesn't hit the internet at inference time (as far as we know?). But Toolformer could well do that, so it's not far away from being added to these models.
For a short-term plausible case, consider the recently-published Toolformer: https://pub.towardsai.net/exploring-toolformer-meta-ai-new-t...
Basically it learns to call specific private APIs to insert data into a completion at inference-time. The framework is expecting to call out to the internet based on what's specified in the model's text output. It's a very small jump to go to more generic API connectivity. Indeed I suspect that's how OpenAssistant is thinking about the problem; they would want to build a generic connector API, where the assistant can call out to any API endpoint (perhaps conforming to certain schema) during inference.
Or, put differently: ChatGPT as currently implemented doesn't hit the internet at inference time (as far as we know?). But Toolformer could well do that, so it's not far away from being added to these models.