NVIDIA

Jensen Huang announced at GTC Taipei 2026 that the Agentic AI era has arrived, shifting AI from content generation to autonomous task execution. NVIDIA launched infrastructure products like Vera Rubin and Vera CPU, driving a computing paradigm shift where AI becomes a direct generator of profit and GDP.

NVIDIA Cosmos 3 is the first open-source omni-model for physical AI, integrating world generation, physical reasoning, and action generation into one unified system. Built on MoT architecture, it supports robotics, autonomous driving, and synthetic data pipelines via Hugging Face and Diffusers.

NVIDIA releases Cosmos 3, the first Omni model integrating vision, language, sound, and action, built on Mixture-of-Transformer architecture, achieving top scores across multiple physical AI benchmarks with open weights for customization and edge deployment.

NVIDIA launches Cosmos 3, the first unified multimodal model integrating language, video, sound, and action inputs/outputs, built on Mixture of Transformer architecture, open-sourced with weights available on Hugging Face, achieving top scores across physical AI benchmarks including Robo Lab, PiBench, and Vintage.

Gamma-World systematically solves architectural gaps in multi-agent world modeling via simplex agent encoding and sparse hub attention, achieving >40% average FVD reduction, zero-shot generalization from 2 to 4 agents, and 24 FPS real-time rollout.

Gamma-World systematically solves multi-agent world modeling via simplex agent encoding and sparse hub attention, enabling zero-shot generalization from 2-player training to 4-player inference and 24 FPS real-time rollout, with average FVD reduction >40%.

NVIDIA introduces Nemotron-Labs Diffusion, a diffusion-based language model family supporting AR, diffusion, and self-speculation modes, enabling parallel multi-token generation and iterative refinement for higher throughput and flexibility.

AI infrastructure is undergoing an unprecedented systemic重构 in capitalist history, with power and wafers as the core bottlenecks; Anthropic's $11B monthly ARR surge reveals explosive demand, while TSMC, NVIDIA, and SpaceX are reshaping the global geopolitics of compute.

AWS provides a comprehensive technical stack for large-scale foundation model training and inference, integrating high-performance compute, networking, storage, and open-source software to support NVIDIA's 'three scaling laws'.

OpenAI, in collaboration with AMD, NVIDIA, and others, introduces MRC—a new networking protocol that enhances performance and reliability for large-scale AI training, now open-sourced via OCP to advance industry standards.

NVIDIA advocates for cost per token as the core economic metric for AI infrastructure, replacing traditional measures like compute cost or FLOPS per dollar, emphasizing full-stack optimization to reduce inference costs and enhance business value.

OpenAI, together with AMD, Intel, NVIDIA and others, has open-sourced MRC, a new networking protocol that improves reliability and efficiency in large-scale AI training clusters.

NVIDIA launches Cosmos 3, an open omni-model for physical AI based on a novel mixture-of-transformers architecture, capable of generating physics-accurate synthetic video, serving as a world model and simulator, and enabling training for robotic and mobile intelligent systems.

OpenAI built a 131,000 GPU training network using the MRC protocol with counterintuitive design choices that significantly improve training efficiency.

Anna Goldie and Azalia Mirhoseini founded Recursive Intelligence, which uses AI to automate chip design, applied in multiple generations of Google TPUs, and plans to democratize chip design through three phases.

NVIDIA today launches Nemotron 3 Ultra, a 550B-parameter open model built on the same architecture as Nemotron 3 Super, optimized for long-running AI agents. It employs LatentMoE to quadruple the number of experts at the same inference cost, introduces multi-token prediction to boost single-user inference speed, and is released under the Linux Foundation’s Open MDW license to enable enterprise deployment.

NVIDIA introduces the 550B-parameter Neotron 3 Ultra, a mixture-of-experts agent model trained for task orchestration, outperforming many trillion-parameter open agents on benchmarks, with full data and recipe transparency to enable enterprise on-prem deployment and fine-tuning.

Recursive self-improvement is driving AI models into a 'new Moore’s Law' era; SpaceX is building a trillion-dollar 'Elon Web Services' ecosystem via Starlink and Colossus compute; American fear of AI stems from job displacement anxiety, CEO communication failures, and regulatory misalignment—not the technology itself.

Richard Socher announces Recursive, a new company focused on recursive self-improving superintelligence to automate scientific discovery and accelerate progress toward superintelligence.

Based on 297k Hugging Face users, this analysis reveals top AI hardware configurations, showing NVIDIA, Apple, and Intel dominance in their respective categories and the importance of VRAM for AI workloads.

OpenAI推出新模型Astra并强调对齐重要性，讨论其在AI价值链中的定位及与微软、Nvidia的竞争关系。

Meta的AIRA₃系统在NVIDIA组织的Kaggle竞赛中表现优异，以第8名的成绩超越人类竞争者。

Weaviate通过多向量检索技术实现PDF图像级搜索，无需OCR和文本提取即可定位图表信息。

NVIDIA 技术博客提出通过 Speculative Decoding 优化大模型推理的五项指南，可使推理速度提升 2-5 倍。

NVIDIA的Nemotron模型在IOI 2026竞赛中以535.4分超越人类顶尖选手，但文章未深入技术细节。

OpenAI发布自研Jalapeno芯片性能超NVIDIA 104倍，同时NVIDIA被曝收购Hugging Face，AI芯片与开源生态竞争加剧。

Hugging Face宣布以129亿美元被NVIDIA收购，旨在推动开源AI成为AI开发的主流方式。

Helix为每个编码代理分配独立桌面，但Mac上共享物理GPU可能导致4个以上会话死锁，Linux+NVIDIA实现更彻底的资源隔离。

人类识别AI生成文本能力有限，NVIDIA的AVO工具在长期任务中表现良好，AI正在重塑CI流程假设。

Weaviate提出Late Interaction RAG方法，通过多向量模型直接解析PDF图表，解决传统RAG无法提取图表信息的缺陷。