Information embedded in a pre-trained model (Google isn't given out that data, just access to an artifact) is helpful if your application lines up to goals of the model. I think it's an open question how broad that…
Say you are an insurance company and you want to use build a model that uses damage photos and meta data about car as a backstop to make sure that your repair shops aren't ripping you off. In this case you already have…
I guess that's kind of my point about Ben's argument. Are pre-trained models going to be the "sustainable advantage" against AWS. I don't think so.
I think Ben (who I generally think is right on) in this post misapprehends the effectiveness of generalized data for machine learning services and thus the effectiveness of this approach in Google’s strategy here.…
An interesting code name for this project - slightly ominous given the novel of the same name?
Information embedded in a pre-trained model (Google isn't given out that data, just access to an artifact) is helpful if your application lines up to goals of the model. I think it's an open question how broad that…
Say you are an insurance company and you want to use build a model that uses damage photos and meta data about car as a backstop to make sure that your repair shops aren't ripping you off. In this case you already have…
I guess that's kind of my point about Ben's argument. Are pre-trained models going to be the "sustainable advantage" against AWS. I don't think so.
I think Ben (who I generally think is right on) in this post misapprehends the effectiveness of generalized data for machine learning services and thus the effectiveness of this approach in Google’s strategy here.…
An interesting code name for this project - slightly ominous given the novel of the same name?