Training the model would be computationally intensive, but deploying that to use Tensorflow.js and predicting a single datapoint in the browser shouldn't be as much, right?
There are ML models that are so computationally intensive that they can't reasonably run on the edge. AI accelerator chips obviously help move the line, but AI accelerators benefit the cloud, too. Furthermore, Models can be tens to hundreds of megabytes in size. Okay for the cloud, not okay for wasm running in the browser.