The key to predicting technological advancement, that is so often misunderstood by technologists, is the S-curve. Laypeople tend to think everything is linear,

The key to predicting technological advancement, that is so often misunderstood by technologists, is the S-curve. Laypeople tend to think everything is linear, technologists tend to think everything is exponential; more often than not, reality tends to be sigmoidal. Technologies have exponential takeoffs followed by logarithmic plateaus. We're clearly well into the exponential phase of deep-learning ML, but it's only a matter of time before this approach hits its logarithmic phase. Of course, the hard part of sigmoidal prediction is determining where in the curve we are. Does the current paradigm have an even steeper part ahead of it? Maybe. And yet, we could just as easily be right in the middle of the function, with a leveling off coming as the state of the art gives way to incremental improvements.