#openledger $OPEN I keep seeing this idea of a “secondary market for underperforming AI models” and honestly, it feels like I’ve watched versions of this same story too many times with different names on top.
OpenLedger is framing it like we can take AI models that don’t perform well and still give them a second life, like there’s some hidden value waiting to be unlocked somewhere down the chain.
But the more I think about it, the more it feels less like a breakthrough and more like a rebranding of something that already happens quietly in the background. Models don’t usually “fail” in a clear way. They just slowly stop being useful. They get replaced, forgotten, or quietly removed from production without any real drama. No one calls it a market event. It’s just… moving on.
And I keep asking myself, if something is already being replaced because it’s not working, who exactly is going to come in and buy that “failure”? Not in theory, but in real life. What does that buyer actually do with it that the original team couldn’t?
For this whole idea to work, you need really stable definitions. You need agreement on what “underperforming” even means. You need trust in evaluation systems that, in reality, are always a bit messy, always slightly biased, and always changing depending on context. A model that looks bad in one environment can still be useful somewhere else. So how do you even price that cleanly?
What makes me a bit skeptical is how quickly everything in tech starts turning into a “market.” Even things that feel operational or internal somehow get transformed into tradable assets. And once that happens, behavior changes. People stop thinking only about usefulness and start thinking about what can be listed, what can be resold, what can be positioned as “value” later on.
@OpenLedger #OpenLedger $OPEN
OpenLedger is framing it like we can take AI models that don’t perform well and still give them a second life, like there’s some hidden value waiting to be unlocked somewhere down the chain.
But the more I think about it, the more it feels less like a breakthrough and more like a rebranding of something that already happens quietly in the background. Models don’t usually “fail” in a clear way. They just slowly stop being useful. They get replaced, forgotten, or quietly removed from production without any real drama. No one calls it a market event. It’s just… moving on.
And I keep asking myself, if something is already being replaced because it’s not working, who exactly is going to come in and buy that “failure”? Not in theory, but in real life. What does that buyer actually do with it that the original team couldn’t?
For this whole idea to work, you need really stable definitions. You need agreement on what “underperforming” even means. You need trust in evaluation systems that, in reality, are always a bit messy, always slightly biased, and always changing depending on context. A model that looks bad in one environment can still be useful somewhere else. So how do you even price that cleanly?
What makes me a bit skeptical is how quickly everything in tech starts turning into a “market.” Even things that feel operational or internal somehow get transformed into tradable assets. And once that happens, behavior changes. People stop thinking only about usefulness and start thinking about what can be listed, what can be resold, what can be positioned as “value” later on.
@OpenLedger #OpenLedger $OPEN