Tryolabs, a machine learning consultancy, writes about deep learning, computer vision, NLP, Python libraries, and ML conferences.
HN links it for computer vision and vision-language model explainers, and for its collaboration with Google on the Temporian library.
What enabled the ML revolution we're witnessing now is mostly the advent of powerful and low-cost GPGPUs and the abundance of training data, as you mentioned. Of course, there are theoretical breakthroughs and interesting new applications [1], but it wasn't the deciding factor. Even ConvNets aren't new. For example, AlexNet is basically a much larger reimplementation of the original Lenet idea [2] from 1998.
This is not to discredit any new work that's being done. I think it's awesome to see so much progress in a field that's certainly on its way of defining an era. I'm just pointing out that we have known about most of the fundamentals for a long time.
[1]: https://tryolabs.com/blog/2016/12/06/major-advancements-deep-learning-2016/
[2]: http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf
Given your objectives -- assuming no restrictions during your earn-out period. Go find another early-stage company or two that you can help. Industry conferences should prove a target rich environment to find them > https://tryolabs.com/blog/machine-learning-deep-learning-conferences/
You would use a VLM (vision language model). The model analyzes the image and outputs text, along with general context, that can drive intelligent decisions. https://tryolabs.com/blog/llms-leveraging-computer-vision
Looks like it is a collaboration with Tryolabs: https://tryolabs.com/blog/tryolabs-google-introducing-temporian