I get wary the moment a smaller project claims to fix something about a much bigger player. OpenAI's API runs at massive scale, and vulnerability claims against it need to be specific, not just a marketing angle.
The real issue with centralized APIs isn't an exploit. It's trust. You send a prompt, get an output, and have no way to verify which model actually ran. OpenGradient's zkML approach targets that exact gap, attaching cryptographic proof to inference in a way a centralized API doesn't offer.
What bothers me is the framing. This isn't patching a vulnerability in OpenAI's infrastructure. It's proposing a different trust model entirely. Calling that a "fix" oversells what's actually happening.
The trust gap is real. The vulnerability framing is a stretch.
#opg $OPG @OpenGradient
The real issue with centralized APIs isn't an exploit. It's trust. You send a prompt, get an output, and have no way to verify which model actually ran. OpenGradient's zkML approach targets that exact gap, attaching cryptographic proof to inference in a way a centralized API doesn't offer.
What bothers me is the framing. This isn't patching a vulnerability in OpenAI's infrastructure. It's proposing a different trust model entirely. Calling that a "fix" oversells what's actually happening.
The trust gap is real. The vulnerability framing is a stretch.
#opg $OPG @OpenGradient