#opg $OPG I opened a small test position $OPG this week, not because I think AI needs another model, but because I keep returning to a different question: how do we verify what AI is really doing?
What caught my attention about OpenGradient is that it focuses on inference and verification together. Most discussions about AI stop at model quality, but if AI ends up making financial decisions, automating, or handling critical workflows, performance alone won't cut it.
The interesting part is that verification becomes more valuable as systems become more capable. A powerful model that can't demonstrate where its results come from creates a trust bottleneck. That's a problem that blockchain has been trying to solve for years in transactions.
In fact, I refrained from adding more to my position last week because I'm still unsure how decentralized verification scales in practice. But the idea still intrigues me.
Perhaps the biggest opportunity here isn't a smarter AI. It could be making AI results independently verifiable, so trust doesn't rely entirely on assumptions.
What caught my attention about OpenGradient is that it focuses on inference and verification together. Most discussions about AI stop at model quality, but if AI ends up making financial decisions, automating, or handling critical workflows, performance alone won't cut it.
The interesting part is that verification becomes more valuable as systems become more capable. A powerful model that can't demonstrate where its results come from creates a trust bottleneck. That's a problem that blockchain has been trying to solve for years in transactions.
In fact, I refrained from adding more to my position last week because I'm still unsure how decentralized verification scales in practice. But the idea still intrigues me.
Perhaps the biggest opportunity here isn't a smarter AI. It could be making AI results independently verifiable, so trust doesn't rely entirely on assumptions.