Just like producing any kind of industrial product, the issue is NIH-syndrome.
Sure you won't be able to compete with the likes of GPT-3, but no one is suggesting you should. The key is to treat software as a commodity and apply it as such. This has been the case for decades (who writes their custom office suite or even OS?) and will expand to ML/AI as well.
We are already at a stage where you don't start from zero and reinvent the wheel every time you need speech- or image recognition. There are readily available off the shelf solutions and customisation is not much more involved than say customising an ERP tool; it's different expertise that's required, sure, but the effort is comparable.
A couple of years from now ML tooling and infrastructure will have caught up to ERP, CAD/CAM, and spreadsheet software - just another tool that can be brought in and provide immediate benefit without scores of consultants, developers and research.
We don't have the staff. We don't have the time. Companies don't have the money.
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