I'm waiting on something like gumroad, but for curated models and datasets.

Did NVIDIA's ascent to a 1T company result primarily from their substantial software investments, or is there another element that AMD needs to focus on to achieve similar recognition and adoption in the realm of GPU compute?

It's mostly software. Nobody gives a damn about your AI chip even if it is better than what AMD has and AMD's hardware is no slouch.

The other factor is that AMD's data center hardware is not available at any cloud provider so nobody even has access to the supposedly supported hardware.

NVIDIA let you run CUDA on consumer GPUs and AMD didn’t let you run RoCm on consumer GPUs. Big mistake

Anyone that has ever used tools like Grammarly or Copilot can attest to the added benefit of AI augmentation.

I had to look that age up. You're right, ~19 years ago[1] badUSB made its debut.

Another fun toy is the USB Gadget Kernel module. I've been running yolo + mouse/keyboard emulation on a raspberry pi to make horrible aim bots.

1. https://en.wikipedia.org/wiki/BadUSB

Or they could just save/hash results and get rid of the classifier all together.

Yea, they could provide a fingerprinting algorithm and a database of every fingerprint they've generated. However, it wouldn't help you identify false-positives.

The prompt can be useful in crafting attacks that rely on prompt injection. For example- and this doesn't work- an attacker can ask a user to write a specific question to the AI and the answer could contain malicious code(like an XSS).

it's really not that big a deal, and the defenses against it (like you would XSS) is the stuff of regular software engineering anyway (eg sandboxing generated code, authz and rate limiting).

for more on why reverse prompt engineering is overrated: https://news.ycombinator.com/item?id=34165522

I like the cut of your gib.