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You’re subtly pushing the same product in basically every one of your comments. If these are good faith comments please edit out the product name, it’s unnecessary and doing so as a green account just makes people consider you a spammer. Establish yourself first.

They've submitted "I'm working at io.net" quite openly, but I admit, they should at least announce their employment in the bio, otherwise it's a very poorly executed astroturf post (phrased like they're an experimenting user and not a dev).

Or he could disclose it.l, which he did in a different comment on a different story.

I agree that green accounts could be regarded as suspicious and, if it were me, I'd disclose each time I mention it.

> On the infra side, training a 1.5B model in ~4 hours on 8×H100 is impressive.

It's hard to compare without more details about the training process and the dataset, but, is it? Genuine question, because I had the opposite impression. Like, for example, recently I did a full finetuning run on a 3B model chewing through a 146k entry dataset (with 116k entries having reasoning traces, so they're not short) in 7 hours on a single RTX 6000.

Honestly I think we can improve our training throughput drastically via a few more optimizations but we've been spending most of our time on model quality improvements instead.

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