These are significant claims locked behind a paid 'pro' version. Red flags.
If you don't believe the timings, I was the author of Hyperlearn https://github.com/danielhanchen/hyperlearn which makes ML faster - I also listed the papers which cite the algos.
I also used to work at NVIDIA making TSNE 2000x faster on GPUs and some other algos like Randomized SVD, sparse matrix multiplies etc.
If you have any suggestions on a more appropriate pricing strategy - I'm all ears!!
I really don't know much about pricing and the open core model, so I'm making stuff up literally.
But for now - our goal is somehow to get revenue ourselves via some cool AI products, and trying to shrink the expenses to 0 (like via our fast training methods)
That's how I would make profit from what you're doing as many big tech companies have already achieved (and more) of what you claim.
I know this as I work in such a company. However, I'd bet they'd pay a fair amount for new solutions that differ from their own.
I worked myself in the past at NVIDIA making algos faster, so it's not a done deal big tech companies have all the tips and tricks. They have the best hardware, but software not so much.
The issue with licensing code is your revenue capture is minimal - maybe a training platform which provides everyone and not just big tech companies a cheap and efficient implementation sounds much better.
The issue with licensing is how much do you charge? How do you monitor usage? Etc
You might want to get some distance from talking to language models.