
NVIDIA Expands Nemotron 3.5 Lineup With High-Efficiency Agentic Models
The new 120B Super VL and Bolt edge models leverage hybrid architectures to optimize multimodal reasoning and local deployment.
Published results, including the ones that show where models fail.
Papers read closely: physics-informed networks for photonic design, diffusion models completing crystal structures, graph architectures for link prediction, and perception experiments exposing what frame-based vision cannot resolve.

The new 120B Super VL and Bolt edge models leverage hybrid architectures to optimize multimodal reasoning and local deployment.

Researchers have developed a deep learning framework to quantify nuclear structural changes, offering a new path for screening regenerative therapies.

Researchers are deploying reinforcement learning agents to optimize quantum-noise-limited parametric amplifiers, aiming to eliminate manual calibration bottlenecks.

Researchers utilize raw network protocol data to enable autonomous agent navigation in World of Warcraft without visual rendering.

A new multimodal 4D dataset from the Institute of Science Tokyo enables AI to interpret and generate canine movements in response to human cues.
The latest Gemini iteration utilizes synchronized neural networks to process visual and auditory inputs, enabling responsive, human-like facial expressions.

Researchers have developed a trajectory-optimization method that allows pretrained generative models to adhere to strict safety requirements without sacrificing output quality.

The new adaptive retrieval architecture reduces computational overhead for AI agents by dynamically adjusting search steps based on query complexity.
Researchers have developed a novel network architecture that enhances video clarity by optimizing inter-frame motion alignment and feature fusion.

The new open-source model integrates vision-language capabilities with 3D perception and trajectory planning for autonomous driving systems.
Applied machine learning, filed daily.
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