A CPU-based RL controller optimizes adaptive sampling during test-time scaling, reducing computational overhead and latency compared to heuristic methods.
The disparity between machine-IDs and human accounts is growing so dramatically in cloud-native environments that traditional IAM processes are failing, creating security gaps.
VaSE achieves higher accuracy than existing sparse-attention methods at 4x KV-cache compression, thereby reducing the memory bottleneck of reasoning models.
NVIDIA’s OmniDreams generates complex vehicle simulations in real time, generalizes better to rare scenarios, and can serve as a foundation for more efficient driving policy models.
Successful domain specialization of LLMs requires careful tuning of learning rate, data-mixing ratios, and checkpoint selection to avoid catastrophic forgetting.
Anthropic is opening its cyber-capable Mythos model to approximately 150 new organizations across more than 15 countries, including EU member states for the first time, with strict security requirements.
