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Zeroth-order fine-tuning can be sped up by over 8x by reframing it as an inference workload and executing it within a serving runtime.
LLMs can now leverage a hierarchical graph structure for memory retrieval, enabling global reasoning and boosting performance on long-term memory benchmarks beyond what's achievable with similarity search alone.
