I have noticed something interesting whenever a new AI product starts gaining traction.
Most people immediately focus on the model itself. Is it smarter? Faster? Cheaper? Investors compare capabilities, users compare outputs, and the conversation quickly turns into a race to identify who has the best intelligence.
That's also the obvious way to look at projects like @OpenGradient .
But the longer I think about it, the less I believe intelligence is the thing that will be hardest to find.
The hidden variable might be trust.
Imagine a future where AI models are everywhere. Every app has one. Every business uses several. Agents are constantly generating analysis, making decisions, and interacting with markets. Intelligence becomes abundant.
What doesn't become abundant is certainty.
How do you know where an output came from? How do you verify that a model actually produced what it claims? How do strangers coordinate around information they can't directly inspect?
That's the thought experiment I keep coming back to.
If AI infrastructure eventually reduces the cost of creating intelligence, then the economic value may start shifting toward systems that reduce uncertainty around that intelligence.
Viewed through that lens, @OpenGradient feels less like an AI hosting story and more like a question about verification in a world flooded with machine-generated information.
And if trust becomes scarcer than intelligence, are we measuring the wrong thing today?
#opg $OPG @OpenGradient
Most people immediately focus on the model itself. Is it smarter? Faster? Cheaper? Investors compare capabilities, users compare outputs, and the conversation quickly turns into a race to identify who has the best intelligence.
That's also the obvious way to look at projects like @OpenGradient .
But the longer I think about it, the less I believe intelligence is the thing that will be hardest to find.
The hidden variable might be trust.
Imagine a future where AI models are everywhere. Every app has one. Every business uses several. Agents are constantly generating analysis, making decisions, and interacting with markets. Intelligence becomes abundant.
What doesn't become abundant is certainty.
How do you know where an output came from? How do you verify that a model actually produced what it claims? How do strangers coordinate around information they can't directly inspect?
That's the thought experiment I keep coming back to.
If AI infrastructure eventually reduces the cost of creating intelligence, then the economic value may start shifting toward systems that reduce uncertainty around that intelligence.
Viewed through that lens, @OpenGradient feels less like an AI hosting story and more like a question about verification in a world flooded with machine-generated information.
And if trust becomes scarcer than intelligence, are we measuring the wrong thing today?
#opg $OPG @OpenGradient