Let me be very clear: Because I have a fancy GPU in my computer, I was able to prototype algorithms in my spare time (e.g. nights and weekends), learn a lot mor

Let me be very clear: Because I have a fancy GPU in my computer, I was able to prototype algorithms in my spare time (e.g. nights and weekends), learn a lot more about the state of machine learning, and use this in production. I can think of one specific use -- processing a data set -- which allowed me to do something automatically which would have used a few hours manual time. My hourly salary times hours saved on that one use already paid for the GPU. I use Stable Diffusion many times to make images for presentations before it was mainstream (yes, there were a few months before everyone was using DALLE and SD). That had a noticeable impact which went well beyond the cost of the GPU. And so on. Yes, I could have done this at lower cost on cloud-based services with only a little bit more overhead, but: 1) I wouldn't have put in the extra work 2) If I did, I wouldn't have been able to justify the expense when things were at the half-baked stage Things like Hugging Face are at a level where this DOES increase productivity by far more than it costs, and not in the abstract hr/retention effects way, but in terms of concrete output. More critically, these tools are now part of our tool set. That means when new opportunities come up, we can leverage them.