This sort of puts the whole notion of "open source" at risk.
Code is a single input and is cheap to compile, modify, and distribute. It's cheap to run.
Models are many things: data sets, data set processing code, training code, inference code, weights, etc. But it doesn't even matter if all of these inputs are "open source". Models take millions of dollars to train, and the inference costs aren't cheap either.
edit:
Remember when platforms ate the open web? We might be looking at a time where giants eat small software due to the cost and scale barriers.
Comments
If it was really open-source you'd be able to just train one yourself.
This sort of puts the whole notion of "open source" at risk.
Code is a single input and is cheap to compile, modify, and distribute. It's cheap to run.
Models are many things: data sets, data set processing code, training code, inference code, weights, etc. But it doesn't even matter if all of these inputs are "open source". Models take millions of dollars to train, and the inference costs aren't cheap either.
edit:
Remember when platforms ate the open web? We might be looking at a time where giants eat small software due to the cost and scale barriers.
This assumes that abstractions are no longer possible.
Only if you were a billionaire. These models are starting to be so out of reach for single researchers or even traditional academic research groups.