> I’m not even sure whether this is possible.

Based on what's happened so far, maybe. At least that's exactly how we got to the current iteration back in 2022/2023, quite literally "lets see what happens when we throw an enormous amount data at them while training" worked out up until one point, then post-training seems to have taken over where labs currently differ.

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drob518 an hour ago | parent [-]

Right, but we played the scaling card and it worked but is now reaching limits. What is the next card? You can surely argue that we can find a new one at any time. That’s the definition of a breakthrough. I just don’t see one at the moment.

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embedding-shape an hour ago | parent | next [-]

> I just don’t see one at the moment.

Did you see the one before the current one was even found? Things tend to look easy in hindsight, and borderline impossible trying to look forward. Otherwise it sounds like you're in the same spot as before :)

	▲	drob518 32 minutes ago \| parent [-]
		That’s what I’m said. Breakthroughs happen. No doubt about it, and they are unpredictable. Hence a breakthrough. But right now we’re using up runway with nothing yet identified to take us to the next level. And while sometimes breakthroughs happen, sometimes they don’t.

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functional_dev 32 minutes ago | parent | prev [-]

better tooling and integration