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Nvidia’s Cosmos Reason 2 aims to bring reasoning VLMs into the physical world

Nvidia CEO Jensen Huang said last year that we are now entering the age of physical AI. While the company continues to offer LLMs for software use cases, Nvidia is increasingly positioning itself as a provider of AI models for fully AI-powered systems — including agentic AI in the physical world.At CES 2026, Nvidia announced a slate of new models designed to push AI agents beyond chat interfaces and into physical environments.Nvidia launched Cosmos Reason 2, the latest version of its vision-language model designed for embodied reasoning. Cosmos Reason 1, released last year, introduced a two-dimensional ontology for embodied reasoning and currently leads Hugging Face’s physical reasoning for video leaderboard.Cosmos Reason 2 builds on the same ontology while giving enterprises more flex [...]

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Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time

Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]

Match Score: 185.78

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Nvidia launches enterprise AI agent platform with Adobe, Salesforce, SAP among 17 adopters at GTC 2026

Jensen Huang walked onto the GTC stage Monday wearing his trademark leather jacket and carrying, as it turned out, the blueprints for a new kind of monopoly.The Nvidia CEO unveiled the Agent Toolkit, [...]

Match Score: 158.46

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Nvidia introduces Vera Rubin, a seven-chip AI platform with OpenAI, Anthropic and Meta on board

Nvidia on Monday took the wraps off Vera Rubin, a sweeping new computing platform built from seven chips now in full production — and backed by an extraordinary lineup of customers that includes Ant [...]

Match Score: 137.14

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Three ways AI is learning to understand the physical world

Large language models are running into limits in domains that require an understanding of the physical world — from robotics to autonomous driving to manufacturing. That constraint is pushing invest [...]

Match Score: 111.12

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Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]

Match Score: 106.59

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Inside Microsoft Ignite: How Microsoft and NVIDIA are redefining the AI stack

Presented by Microsoft and NVIDIAAs the world’s leading platform providers and champions for advancing AI globally, NVIDIA and Microsoft continue to deliver unequaled value for organizations investi [...]

Match Score: 97.61

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New training method boosts AI multimodal reasoning with smaller, smarter datasets

Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]

Match Score: 91.69

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Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases

Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynam [...]

Match Score: 87.10

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Nvidia's DGX Station is a desktop supercomputer that runs trillion-parameter AI models without the cloud

Nvidia on Monday unveiled a deskside supercomputer powerful enough to run AI models with up to one trillion parameters — roughly the scale of GPT-4 — without touching the cloud. The machine, calle [...]

Match Score: 82.86