NVIDIA has launched the Nemotron 3 family of open models—Nano, Super, and Ultra—that feature a hybrid mixture-of-experts architecture, offering high efficiency and accuracy for building scalable, transparent agentic AI systems across industries. The models support advanced reinforcement learning, large parameter sizes, and are designed to reduce inference costs while enabling multi-agent collaboration. Accompanied by new datasets and open-source libraries, Nemotron 3 aims to accelerate innovation in AI workflows and applications.
China is leveraging open-source AI models like DeepSeek R1 and Moonshot AI's Kimi K2 to expand its global influence and challenge U.S. dominance in AI, using soft power strategies that promote accessibility and customization, especially in developing countries. The U.S. must adapt by fostering open AI ecosystems and recalibrating export controls to maintain its leadership and influence in the evolving AI landscape.
Google has launched Gemma, a new family of lightweight open-weight models, including Gemma 2B and Gemma 7B, inspired by its Gemini models. These dense decoder-only models are available for commercial and research usage, with access to ready-to-use Colab and Kaggle notebooks, as well as integrations with Hugging Face, MaxText, and Nvidia’s NeMo. While not open-source, developers can use the models for inferencing and fine-tune them at will. Google also released a responsible generative AI toolkit and a debugging tool to provide guidance and essential tools for creating safer AI applications with Gemma.
