@OpenGradient The Progress Bar Moved Backward and That Changed What I Was Looking At

While I was testing OpenGradient I found something that was actually more interesting, than uploading files.

One of the nodes just stopped working.

The client tried again. The progress bar really moved backward. It did not move back a lot. It was enough that I stopped looking at the upload and started looking at the network traffic instead.

I thought the hard part was going to be storing the model. This is because bigger files need computer power, more equipment and more infrastructure. This seems simple.

What really caught my attention was everything that was happening around storing the model.

Most systems do not show you when something goes wrong. If something breaks, you. Do not see it or you get a general error message.. Here the client trying again showed me something different. The network was still trying to find a way to work when one part of it stopped working.

This makes me wonder something.

When people talk about OpenGradient and decentralized AI infrastructure are they thinking about conditions or real conditions?

A network is not good when every node works perfectly. A network is good when one node stops working or when it takes a time to get a response or when data comes in out of order.

The interesting thing is not that the client tried again. The interesting thing is that OpenGradient seems to be designed to expect that it will have to try

Maybe that is the problem.

Not storing the model. Dealing with the moments when the network reminds you that it is a network.
#OPG @OpenGradient $OPG $LAB $NES