NVIDIA Senior Director of Product, AI, and OpenShell
San Diego CA
Joined April 2013
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Special thank-you to the OpenShell team and community partners behind today’s 0.1.0 release, and to our Sentry teammates and collaborators across NVIDIA bringing the broader platform to life. So much care and hard work went into this. Proud to be building it together ❤️
Today, with over 100 industry partners, we introduced the NVIDIA Open Agent Safety Platform, bringing together OpenShell and Sentry.
Artificial intelligence is extraordinary technology that will advance discovery, productivity, security, health, and prosperity for generations to come.
But its full promise can only be realized when people have confidence that AI is being built to be safe and deployed with wisdom and responsibility.
This is bigger than a single product. It's the beginning of an open ecosystem to build the trust layer for safe agent systems.
Together, we are building the foundation of the AI economy.
Trust and innovation are not in conflict. Safety is how trust is earned. We must build not only the most capable AI, but the most trusted AI, so that this extraordinary technology can realize its enormous promise for the world. nvda.ws/4hcoq7m
Alex Watson retweeted
“I’m a responsible optimist.”
AI’s potential comes with a responsibility to build and deploy it safely.
Our CEO @JensenHuang explains why that responsibility led us to build NVIDIA OpenShell and bring the industry together around agent safety.
🎥 from @SquawkCNBC:
Still early research from the OpenShell team at @nvidia, but we think combining fast, formal checks with AI and human judgment could be a useful direction for scaling agents nvidia.github.io/OpenShell-R…
Built a small OpenShell demo: the model can request tool access, but the shell only executes calls that pass an SMT check against policy intent.
Safe actions get auto-approved because they come with a proof, not a vibe.
Recorded a quick demo of agent-driven policy approvals in OpenShell 🤖
OpenAI Codex starts in a sandbox with read-only GitHub access, gets blocked when it tries to write, proposes a narrow policy update, waits for review, then retries successfully after OpenShell hot-reloads
Run Autonomous, Self-Evolving Agents More Safely with NVIDIA OpenShell | NVIDIA Technical Blog developer.nvidia.com/blog/ru…
Alex Watson retweeted
Been so much fun cooking OpenShell and NemoClaw with the @NVIDIAAI folks! 🙏🦞
Huge step towards secure agents you can trust.
What’s your OpenClaw strategy?
Alex Watson retweeted
🚨 BREAKING: 4OGS Racing enters the professional motorsport arena after extensive R&D program. Sears Pointless 2026 marks our championship assault. Very racy. Questionably pacey. #4OGSRacing #VeryRacy #QuestionablyPacey #24HoursOfLeMons #MotorsportNews
Alex Watson retweeted
synthetic data is also a big feature of our Nemotron 3 Nano pre & post-training. Gretel joined Nvidia in April, and it's been an amazing ride to bring SDG & Data Designer to help build our latest SoTA Nemotron.
here are some datasets we worked on 🧵
🚀 @nvidia just open-sourced NeMo Data Designer, the Python framework we use to generate synthetic data for Nemotron.
Structured outputs ✅ LLM columns ✅ Dependency-aware fields ✅ Validators ✅ LLM-as-judge ✅
Jump in & build your own pipelines: github.com/NVIDIA-NeMo/DataD…
Psyched!
Alexander Skarsgård is Murderbot.
#Murderbot — Streaming May 16 on Apple TV+
ALT Murderbot (played by Alexander Skarsgård) looks menacingly at someone off screen. It is wearing its suit, with the helmet removed.
ALT Murderbot (played by Alexander Skarsgård), in its suit with its helmet on, stands outside the ship.
📊 Excited to share how teams are using @gretel to evaluate RAG systems! Here's our guide to:
- Generate diverse test scenarios
- Evaluate different configs
- Find edge cases automatically
Something we've learned from lots of customer convos. Check it out ⬇️
🧵What we’re seeing emerge with models like DeepSeek R1, @MSFTResearch Phi-4, @Meta's self-play and now as OSS with @huggingface Open-R1 is a data pipeline as sophisticated and original as the models themselves- and I’m here for it
2/ The new blueprint for building AI: keep it lean, iterative, and guided by the best ideas both humans and machines can collectively generate
The future of AI customization won't need armies of labelers - just synthetic data and expertise 🚀
@AIatMeta's ALMA paper just proved this: matching Llama3-Instruct performance with synthetic data + just 9k examples (vs. millions!)
Paper: arxiv.org/abs/2412.04305
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