The other thing is that stitching together other open source tools like this is simply not enough value. Who will be incentivised to buy?
Saying this as FAANG ML org person where I see the push to open source ops tooling like this.
Google certainly has made a push toward scalable AI training and deployment. However, it is not fun to use in practice, speaking from experience.
Startups beating an incumbent with substantially better UX is always a good story. Improving productivity is an easy winner for potential customers.
But calling Grid an ML Ops startup is like calling Lightning Keras... maybe at a quick blink it looks like that, but that's where the similarities end.
For what it's worth, a lot of what we're building comes from my experience at FAIR.
For us is basically integrating clouds directly into your code so the barrier disappears and the cloud providers become an extension of your laptop.
One of the professors at my lab at NYU CILVR (Kyle Cranmer) i believed was super involved with this. Will definitely sync up with him!
Thanks for the heads up!