I used to think verified execution was the biggest challenge in decentralized AI. Now I believe it's only part of the story.
My view is simple: proving a model ran correctly is valuable, but it doesn't automatically prove the model is accurate or reliable. Trust comes from both correct execution and strong evidence behind the results.
OpenGradient now supports more than 2,000 AI models, giving developers plenty of choice. That growth is encouraging, but it also makes transparency around model quality even more important.
The network has processed over 2 million inferences, which shows meaningful usage. Still, inference volume isn't the same as high-quality training data or proof that a model generalizes well across different tasks.
OPG Token currently has around 190 million tokens in circulation out of a fixed maximum supply of 1 billion. As adoption grows, both network activity and future token distribution will remain important factors to watch.
For me, the long-term opportunity is clear: verified computation builds confidence, but transparent evidence of model performance is what ultimately builds lasting trust in the OpenGradient ecosystem.
#opg @OpenGradient $OPG
My view is simple: proving a model ran correctly is valuable, but it doesn't automatically prove the model is accurate or reliable. Trust comes from both correct execution and strong evidence behind the results.
OpenGradient now supports more than 2,000 AI models, giving developers plenty of choice. That growth is encouraging, but it also makes transparency around model quality even more important.
The network has processed over 2 million inferences, which shows meaningful usage. Still, inference volume isn't the same as high-quality training data or proof that a model generalizes well across different tasks.
OPG Token currently has around 190 million tokens in circulation out of a fixed maximum supply of 1 billion. As adoption grows, both network activity and future token distribution will remain important factors to watch.
For me, the long-term opportunity is clear: verified computation builds confidence, but transparent evidence of model performance is what ultimately builds lasting trust in the OpenGradient ecosystem.
#opg @OpenGradient $OPG