A hosted Jupyter notebook in a sandboxed VM able to send jobs to this new silicon is something that might be possible to set up by a small team in a few months, and could turn into a billion dollar business.
As a bonus, Tesla can use revenue from that to grow this supercomputer, while using any spare/unsold capacity for themselves.
I think they said that during the first AI Day. Here's a 19 minute supercut of AI Day: https://www.youtube.com/watch?v=keWEE9FwS9o
But I think that was the wrong strategic move - they should have opened it up, together with some 'Tesla AI' demo models, in a colab environment. They can hire new employees to do that - it is separate work from that involved in making the self driving car, and will not block or interfere.
The only reason I think they might not is that they don't want to step on Googles toes - there are very close links between Musk companies and Google, and a direct competitor to Googles TPU product might hurt that relationship more than it generates in revenue.
The bottleneck isn't employees, it's chips.
Yet, building a basic colab-like interface, using opensource tools, shouldn't take more than a few people a few months.
Obviously, they might not want to launch that before their hardware is ready, but their hardware has been in production for over a year now.
Clearly something hasn't gone to plan.
There is approximately zero chance that this is a consideration.
My guess would be that, like a lot of things under the Elon Musk umbrella, what they claim they are able to do in theory diverges far from reality. We've seen similar slideshows.
[1] https://cloud.google.com/blog/products/ai-machine-learning/g...
https://blog.google/technology/ai/introducing-pathways-next-...
If you listened to their talk their silicon comes without support for access control and multi tenancy. Letting random people run on this will be an unlimited disaster.