Reflection AI releases Beam open-weight model
The 501-billion-parameter mixture-of-experts model claims to match Chinese rivals on reasoning benchmarks while using 3-4x less inference compute.
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The 501-billion-parameter mixture-of-experts model claims to match Chinese rivals on reasoning benchmarks while using 3-4x less inference compute.
A novel mixture-of-experts architecture promises to make protein structure prediction both faster and more accurate, with potential implications for AI-driven drug discovery.
Researchers propose an entropy-driven routing mechanism for mixture-of-experts models that could reduce compute overhead while maintaining accuracy.
A new pure-C, dependency-free system pools CPU and disk from any machines on a network to serve massive MoE models, with byte-identical output and no upfront downloads.
A 12.3GB MoE quant packs a 35B model onto consumer cards, with quality within noise of FP8 on most benchmarks.
Amos Labs' experimental Metal runtime proves oversized sparse MoE checkpoints can fit in constrained Apple Silicon memory without sacrificing functional capability, even if interactive speeds remain out of reach.
New research proposes sticky routing for mixture-of-experts models, keeping tokens on the same expert across layers to cut communication overhead and improve throughput.