Eiso Kant
speaker
1,158 appearances
1 recordings
1 series
first heard Jul 2026
last heard 23 Jul
Eiso Kant’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.
Appearances
Because ultimately, our bottleneck on compute is a MapMole bottleneck and a networking bottleneck.
And the moment you start doing those things,
So I'm excited about that.
We're not doing any, I mean, we're doing the usual, like Laguna S was trained in FP8.
Only thing that in this run I have to admit that wasn't FP8 was the all-to-all.
In the new run we just started yesterday, the FP8 was all-to-all.
That was just like cutoff day.
Like, oh, we're not perfectly comfortable wanting to
do it uh you've got amazing work by nematron and nvf before training like i think it's underrated what they've done there uh i'm excited to get to nvf before training uh doesn't make sense yet because we're still training on hoppers right we're like relatively small we're 10k h200 cluster company right now we'll be scaling to a lot more soon
But, and really a lot more, someone is thinking about applying for a job.
But like the, yes, I think it's, there's so much more juice to squeeze out of this.
And hopefully Laguna Edge shows people that a model at this size works.
can get a lot more.
And we did this thing in eight weeks.
We think there's a lot more juice to squeeze out at any model size.
We're now scaling up because it's the most optimal thing to do for us as a company.
But if I had infinite time, I would love to push more the capabilities at other model sizes.
So Laguna S, Laguna Small, 118, 118 billion total parameters, 8B active.
So very sparse.
It's a scale up of the XS architecture.
Showing 541–560 of 1,158 · page 28 of 58
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