Sparse models of that size use about 40-60 gb and are fast enough for me (but dense models of that size I agree there bare too slow)
COMPUTING
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Training a Mythos model requires noticeable amounts of compute
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And by regulatable amounts of compute, I mean training a Mythos class model uses enough power and chips that national governments will obviously notice. No ine is training a model of that size without permission
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NVIDIA GB300 outperforms H200 by 20x in agents per megawatt
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Among other findings the benchmarks shows that NVIDIA's GB300 outperforms H200 by a whopping factor of 20 in terms of running concurrent agents per megawatt. 3/4
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China scaling Huawei chips, mythos model expected in 12 months
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you underestimate exponentials. Its probably true that they dont have a mythos level model yet. but even amodei expects such model to be created in china in about 12 months. China is scaling huawei ascend chips by an insane amount and they have all the energy they need.
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Gigatron for Linear Algebra in Machine Learning! @gp_pulipaka
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