Gemma

Google DeepMind released the Gemma 4 E4B assistant model using Multi-Token Prediction (MTP) architecture that accelerates inference by up to 2x through speculative decoding. The 4.5B effective parameter model supports 128K context windows and handles text, image, and audio input with pricing not yet disclosed.

NVIDIA engineer Asier Arranz demonstrated Gemma 4 running as a vision-language agent (VLA) on a Jetson Orin Nano Super with 8GB RAM. The model autonomously decides when to access a webcam based on user queries, with no hardcoded triggers—performing speech-to-text, vision analysis, and text-to-speech entirely locally.

NVIDIA released Nemotron-Personas-Korea, a dataset containing 7 million demographically accurate synthetic personas grounded in official Korean statistics from KOSIS, Supreme Court of Korea, and the National Health Insurance Service. The dataset includes 26 fields per persona covering demographics, geography, and occupation across all 17 Korean provinces, with zero personally identifiable information under CC BY 4.0 license.

Google released Gemma 4, an open-weights model family that runs directly on edge devices with multi-step planning and autonomous workflow capabilities. The Apache 2.0 licensed model bypasses traditional cloud security controls by executing entirely on local hardware, creating a governance blind spot for enterprise security teams.