Image created with gemini-3.1-flash-image-preview with claude-sonnet-4-5. Image prompt: Photorealistic 4K nature documentary shot of a giant NVIDIA GPU chip die emerging from a partially frozen winter bay at dusk, circuit patterns etched in crystalline ice and frost, half-submerged in dark water with floating ice chunks, golden sunset light catching geometric transistor grids, steam wisps rising, deep blue to orange gradient sky, landscape format with bold NVIDIA text overlay.
How Nvidia became the first $5 trillion company, in 4 charts | CNN Business https://edition.cnn.com/2026/02/07/business/nvidia-trillion-valuation-ai-chips-vis
Launching mini-SWE-agent 2.0, the simplest coding agent. Near SoTA performance, with the agent/model/environment only ~100 lines each. Powering benchmarks and RL training at NVIDIA, Anyscale, Stanford and many more!”” https://x.com/KLieret/status/2021606142699356215
3 years ago, we emailed Jensen with requests for Blackwell. Today, we released GPT-5.3-Codex, a SOTA model designed for GB200-NVL72. Nitpicking ISA, simming rack designs, and tailoring our arch to the system has been a fun experience! I’m grateful to our collaborators at NVIDIA.”” https://x.com/trevorycai/status/2019482450855096440
At @nvidia, we use a lot of AI coding tools. Codex with GPT-5.3-codex is particularly impressive. The engineers I know here are big codex power users. The capabilities of these coding agents are advancing quickly, it’s quite exciting. With 5.3, I’m particularly impressed with”” https://x.com/benklieger/status/2021707684211569033
VS Code gives you extremely powerful building blocks with custom agents, parallel subagents, and slash commands to compose your own workflows. Here is /review command that uses Opus 4.6 fast mode, GPT-5.3-Codex, and Gemini 3 Pro to independently review changes and grade each”” https://x.com/pierceboggan/status/2021094988205969465
Not the flashiest demos, but what’s under the hood represents a foundational shift for general-purpose robotics. World models are the next-gen foundation of Physical AI, not the VLM backbones found in typical VLAs. DreamZero is a 14B-parameter World Action Model (WAM) by NVIDIA”” https://x.com/TheHumanoidHub/status/2019460701811851593
Robots usually fail for one simple reason: they don’t understand what will happen next. [📍Paper, code & task gallery at the end] > 14B “World Action Model” from @nvidia: DreamZero… Instead of copying motions or replaying demonstrations, this model predicts how the world”” https://x.com/IlirAliu_/status/2019418751976800520
Leading Inference Providers Cut AI Costs by up to 10x With Open Source Models on NVIDIA Blackwell | NVIDIA Blog https://blogs.nvidia.com/blog/inference-open-source-models-blackwell-reduce-cost-per-token/
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