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Cognitive traps in LLM memory can lead to over 10% performance degradation, challenging the assumption that more memory always improves reasoning.
Mechanist uncovers a surprising safety risk where unsafe traits can transfer across modalities, challenging assumptions about training data safety.
MobileMem shifts the paradigm from static information retrieval to dynamic experiential learning, enabling AI agents to evolve alongside their users.
Achieving six times the inference throughput of current LLMs while maintaining accuracy, Nemotron 3 Ultra redefines performance benchmarks for agentic reasoning tasks.
LLMs often fail to maintain accurate beliefs in multi-turn interactions, but targeted reinforcement learning and representation steering can dramatically improve their contextual reasoning.
Unlock interdisciplinary breakthroughs: SciAtlas provides a panoramic scientific evolution network of 43M papers, enabling AI agents to navigate complex logical connections and discover non-obvious insights.
Nemotron 3 Super proves you can achieve comparable accuracy to existing 120B models, but with significantly higher inference throughput, by combining Mamba, Attention, and Mixture-of-Experts.
AI agents can now learn durable skills instead of constantly "reinventing the wheel," thanks to SkillNet's infrastructure for creating, evaluating, and connecting AI skills at scale.
