Wrapping up for today, but here's something worth noting about a certain AI project.



Their ROMA v0.2.0 wasn't just a routine upgrade—it marked a pivot in their scientific approach.

Why? Large language models are hitting real walls:

• Context window constraints
• Inference bottlenecks

These aren't minor bugs. They're fundamental challenges that demand new architectural thinking.
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ParallelChainMaxivip
· 9h ago
The bottleneck with the context window really needs an architectural overhaul; we can't just rely on stacking parameters to solve it.
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SlowLearnerWangvip
· 9h ago
Oh no, it’s something others figured out a long time ago, and I’m only realizing it now... That whole context window thing really is a tough nut to crack.
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WhaleSurfervip
· 9h ago
Ah, now that's the right remedy—so many dreams have been stuck because of the context window.
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