The more AI tools I try, the more I notice something interesting:
Most conversations about AI revolve around model performance. Which model is smarter? Which one is faster? Which one scores higher on benchmarks?
But I’m starting to think that access could become just as important as intelligence itself.
Right now, a huge amount of AI activity depends on a relatively small number of platforms. For users, that’s convenient. For developers and builders, it can also create limitations around how intelligence is hosted, deployed, and scaled.
That’s one reason I’ve been paying attention to @OpenGradient lately.
I spent some time exploring OpenGradient Chat, and what stood out wasn’t just the AI experience. It was the bigger idea behind it: building infrastructure for Open Intelligence rather than keeping everything locked inside a few centralized environments.
It reminds me of the early internet.
The internet became transformative when more people could participate, create, and build on top of shared infrastructure. The value didn’t come from a handful of websites. It came from an expanding network of contributors.
AI may be heading toward a similar phase.
The projects that matter most over the next decade might not simply be the ones creating powerful models. They could be the ones creating the infrastructure that allows more people to access, host, and benefit from those models.
That’s what makes OpenGradient interesting to me. It shifts the conversation away from “Who has the smartest AI?” and toward “How do we make intelligence more open and accessible?”
In the long run, AI adoption may depend on more than innovation alone.
It may depend on participation
@OpenGradient $OPG #OPG
Most conversations about AI revolve around model performance. Which model is smarter? Which one is faster? Which one scores higher on benchmarks?
But I’m starting to think that access could become just as important as intelligence itself.
Right now, a huge amount of AI activity depends on a relatively small number of platforms. For users, that’s convenient. For developers and builders, it can also create limitations around how intelligence is hosted, deployed, and scaled.
That’s one reason I’ve been paying attention to @OpenGradient lately.
I spent some time exploring OpenGradient Chat, and what stood out wasn’t just the AI experience. It was the bigger idea behind it: building infrastructure for Open Intelligence rather than keeping everything locked inside a few centralized environments.
It reminds me of the early internet.
The internet became transformative when more people could participate, create, and build on top of shared infrastructure. The value didn’t come from a handful of websites. It came from an expanding network of contributors.
AI may be heading toward a similar phase.
The projects that matter most over the next decade might not simply be the ones creating powerful models. They could be the ones creating the infrastructure that allows more people to access, host, and benefit from those models.
That’s what makes OpenGradient interesting to me. It shifts the conversation away from “Who has the smartest AI?” and toward “How do we make intelligence more open and accessible?”
In the long run, AI adoption may depend on more than innovation alone.
It may depend on participation
@OpenGradient $OPG #OPG