Ajen

You're drawing a line between progressives and catholics, but the catholics just defrocked a nazi.

I could agree that it's an abbreviation, but I wouldn't go so far as to call it "diminutive."

If they send 2 emails per subdomain per year, that could easily be 10s of millions which would make the cost per email measured in thousandths of a cent. And I could see the number of subdomains being larger by a factor of 10, maybe more.

Another angle: someone with IT experience needs to manage the system that seems emails, and other engineers need to integrate other systems with the email reminder system. The time spent on engineering could easily add up to thousands per year, if not tens of thousands.

I'm guessing their figure is based on both running costs and engineering costs.

Your CVT most like had an automatic, centrifugal clutch.

If your server goes down you'll miss incoming emails, and IMO residential ISP and power service isn't reliable enough for your main email address. If mail can't get delivered people get the impression you gave them a fake email address, which can be more than embarrassing.

It's the only service I don't self-hosted, although I do backup my email on my home server. Email protocols don't tolerate downtime, if your server is temporarily unreachable you won't get messages and people will probably assume the email address/domain isn't even valid.

It's a Linux joke though

Yep, it's the cops who don't care.

I don't know what, if any, CS background you have, but that is way off. The training dataset is used to generate the weights, or the trained model. In the context of building a trained LLM model, the input is the dataset and the output is the trained model, or weights.

It's more appropriate to call deepseek "open-weight" rather than open-source.

I used the word "source" a couple times in that post.. The first time was in a general sense, as an input to generate an output. The training data is the source, the model is the "function" (using the mathematics definition here, NOT the computer science definition!), and the weights are the output. The second use was "source code."

Weights can be changed just like a compiled binary can be changed. Closed source software can be modified without having access to the source code.

The weights aren't the source, they're the output. Modifying the weights is analogous to editing a compiled binary, and the training dataset is analogous to source code.