Hundreds of worker failures and the result is the same.
About SN9 iota
Macrocosmos@MacrocosmosAIHundreds of worker failures and the result is the same. We don't think about fault tolerance any more.
Quoting @IOTA_SN9
A question we often hear from teams evaluating the IOTA SDK: if I train this again, do I get the same model? We ran 7 independent 16B pretraining runs, ~140 GPUs each. Between them, 585 worker crashes, preemptions and rejoins. The loss curves are almost identical. Reproducibility is what turns a result into science instead of a one-off. It's also what makes a training run worth paying for. Most distributed training projects overfit to a single experiment: one model, one recipe, one demo run. The IOTA SDK is general purpose, fault-tolerant and reproducible. iota.macrocosmos.ai/sdk
SN9 iota at a glance
SN9, iota (α token ι), is one of the independent markets on the Bittensor network, each with its own α token and its own price. Its α currently trades at 0.024367 τ (≈ $6.31), against 53,672 τ of pool liquidity. On-chain, the best-delegated validator on it yields about 36.37% APR (simple) and 43.87% APY (compounded), emissions add 0.003249 τ to the pool each block, epochs run every 360 blocks. It was registered at block #1,489,797.
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