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SILX AI releases Quasar-Preview, an 18B parameter MoE foundation model with 2B active parameters and experimental 5M-token context, built on a hybrid recurrent/attention architecture and designed for decentralized training via Bittensor SN24.
HodgeCover uses higher-order topological coverage to compress sparse Mixture-of-Experts layers by addressing irreducible mergeability barriers that pairwise signals miss, matching state-of-the-art baselines on expert reduction and leading on aggressive compression.