I like to build. Currently at @nvidia / Prev Apple, Red Hat, webAI
Austin, TX
Joined July 2008
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Congrats to @tursodatabase @glcst and the team there! Big fan of Turso! 👏 🚀
Turso is joining @supabase.
Together, we're building the database platform for the agentic era: everything agents need, from lightweight databases to Postgres at petabyte scale.
More details in thread. 👇
William Markito retweeted
Your agent got the right answer. How much work did it take to get there?
We worked with @NousResearch/@Teknium on a hands-on walkthrough of NVIDIA NeMo Relay to collect traces for Hermes Agent. Run two example scenarios, follow the agent’s calls and retries, and see the full trace in Arize Phoenix.
The blog also looks at how Nous used traces and task results to evaluate fixes across repeated runs.
TechBlog: nvda.ws/47tKxjQ
📽️ by our own @Picomoorhead:
William Markito retweeted
Introducing CUDA Rust!
CUDA Rust lets you write GPU kernels natively in Rust, not just launch them from it.
Two paths: cuda-oxide for SIMT kernels compiled to PTX, and cutile-rs for Tile-based programming on stable Rust. Both can catch aliasing errors at compile time.
Technical blog: nvda.ws/4hm1bHS
William Markito retweeted
Our new new one-click local model setup is perfect for use with NVIDIA hardware
Local AI agents should be easy to set up.
That’s why @NousResearch is bringing one-click local model setup to Hermes Agent across NVIDIA systems on Windows and Linux.
William Markito retweeted
Checkout the latest XGBoost update "Introducing the XGBoost Vector-Leaf Model" from jiamin yuan and Rory Mitchell
xgboost.ai/2026/08/25/introd…
William Markito retweeted
We benchmarked 300+ NVIDIA verified skills to see how much they actually help agents on real tasks.
Same task, same model, same setup. The only difference was whether the agent had the skill.
Across the benchmarks, skills improved correctness by 41 points, effectiveness by 39, and efficiency by 35.
SkillEvaluator is open source if you want to test your own skills before you ship them.
William Markito retweeted
really excited to see this release AND integrate it with deepagents!!
langchain.com/blog/switchyar…
William Markito retweeted
Hermes Agent is now dramatically more efficient, especially for smaller/weaker/local models!
With the help of @nvidia's Nemo Relay and several other strategies Hermes was able to identify a ton of optimizations beyond just saving tool execution time or memory - but also turns needed to complete tasks, schema improvements to reduce context load, and token efficiency gains by tracing through wasted turns and tool errors across all 250,000 conversations I've had with my Hermes.
All of the below are now in Hermes Agent, update to start saving now or wait until tomorrow for the full version update release.
Vai Brasil! 🇧🇷
Alibaba Qwen3.7 slowly fading into irrelevance at the frontier due to proprietary stance.
In it's place we have Minimax M3 and... *checks notes* Rio 3.5 397b, made by the municipal IT company of Rio de Janeiro's city government.
huggingface.co/prefeitura-ri…
William Markito retweeted
Say hello to open source deep research for your favorite agent harness.
Our AI-Q agent skill packages the work of building a research pipeline into a portable skill. Drop it into your harness, and the agent delegates a research task to a local or hosted AI-Q server and gets back a detailed report with citations. See it in Codex below 👇
William Markito retweeted
Get started with NVIDIA AI-Q here nvda.ws/4ukAabY
Let’s go! #langchain #nvidia
William Markito retweeted
“If your $500K engineer isn’t burning at least $250K in tokens, something is wrong.”
This.
Go from "hello world" to "hello claw!" 🦞
We're hosting a Build-A-Claw extravaganza in the #NVIDIAGTC Park Mon-Thur where you can BYOD or buy a DGX Spark on-site and our NVIDIA experts will help you install @OpenClaw.
See you there! 🙌
Full details 👉 blogs.nvidia.com/blog/gtc-20…
