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Huang at AI’s Biggest Stage

How to Create Canva Designs Instantly Using ChatGPT

Author

Alamin Hossain
March 16, 2026

Advertise here | 6-min Read

Welcome to our Monday edition!

In today’s menu:

  • AI Inspirational Quote

  • Huang at AI’s Biggest StageH

  • Avocado Stuck; xAI in Trouble

  • Today's AI Radar

  • Daily AI Byte

  • Social Media

  • Trending AI Tools

Stanford–Princeton’s AI-XR Clinical Co-Pilot Enters Real Hospital Deployment

MedOS combines smart glasses, cobots, and AI. Source: Stanford University)

AI Just Entered the Hospital.

Meet MedOS, a next-generation AI-XR-Cobot system built by the Stanford mm        Princeton AI Coscientist Team.

Now featured at NVIDIA GTC 2026 and already deployed at the Stanford Blood Center and Stanford Department of Pathology.

MedOS works as a real-time clinical co-pilot:

→ Multi-agent AI reasoning
→ XR smart glasses for live insights
→ Collaborative robots assisting clinicians
→ Intelligent gloves enabling precise actions

Recent upgrades:

• 2× more medical disciplines supported
• Near real-time XR response

AI is no longer just research.

It’s entering real hospitals.

👉 Learn more: https://ai4medos.com/

❝

Work hard enough that luck has somewhere to land.”

— Sam Altman

🔥 Today's Biggest Story

This is the AI industry's Super Bowl. 30,000 people inside SAP Center. Hundreds of thousands streaming. Jensen Huang in his black leather jacket, about to announce chips the world has never seen. Here's why today matters more than most GTC keynotes.

The mystery chip: Weeks ago, Huang sat at dinner with 30 Nvidia and SK Hynix engineers in Santa Clara and told the Korean Economic Daily: "We've prepared several new chips the world has never seen before. A chip that will surprise the world will be unveiled at GTC.

NemoClaw — the software that matters more than the chip: Wired broke the story first. Nvidia has quietly built NemoClaw, an open-source enterprise AI agent platform that lets companies deploy autonomous agents across internal systems — without depending on any specific cloud vendor or model provider. This is Nvidia's answer to OpenAI's operator framework and Anthropic's MCP.

Vera Rubin + AI Factories: The first Vera Rubin chips shipped in early 2026. Today's keynote will include shipping timelines, pricing signals, and possibly first benchmarks. The rumored Rubin Ultra — 576 GPUs, 14.4x the performance of Grace Blackwell — was a 2027 roadmap item. If Huang pulls it forward to today, that reshapes every enterprise AI infrastructure budget for the next 18 months. Beyond chips.

BOTTOM LINE : Nvidia already owns 80% of the AI training chip market. Today is about owning the next two layers: inference (Feynman) and agent infrastructure (NemoClaw). If it lands, Nvidia doesn't just sell the picks and shovels of the AI gold rush — it becomes the operating system every company runs AI on. That's worth watching not just for the chips, but for what it means for every developer building with Claude, GPT, and Gemini right now

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📡 Today's AI Radar

Social media

Perplexity Announced Personal Computer.

Trending AI Tools

Daily AI Byte

Monday Skill — Tool: Claude Code · Agent Teams Mode

Everyone is watching Jensen Huang today. Here's what to actually do with what he announces.

GTC keynotes move markets but rarely tell you what to build next. Jensen Huang will announce NemoClaw (Nvidia's open-source agent platform), Vera Rubin chip updates, and a roadmap for agentic AI across enterprise. By 2pm PT, every developer thread will be full of hype. Here's the smarter play: use Claude Code right now to audit your stack for where agents could actually help — before everyone else starts copy-pasting prompts from the keynote slides.

Claude Code's Agent Teams feature (now in research preview) runs multiple agents in parallel — one reviewing security, one mapping tech debt, one finding automation opportunities. It's exactly the multi-agent workflow Huang is about to show on stage. 

Run this in Claude Code before the keynote ends →

"Scan my codebase and find the top 3 workflows a developer
does manually every day that an AI agent could automate.
For each: explain the task, estimate hours saved per week,
and write a one-paragraph agent spec I could build with NemoClaw or n8n."

By the time the keynote finishes, you'll have a real action plan — not just keynote FOMO.
👋 THAT’S A WRAP

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