Thank you Kris Murphy (@nvidia), Sally O’Malley and Mrunal Patel (@RedHat) for “AI Agents at Work: Balancing Business Value, Control and Trust” at PyTorch, Powering the Enterprise. #AIAgents #PyTorch

Thank you Christopher Nuland (@RedHat) and Kris Murphy (@nvidia) for “Path to Production AI” at PyTorch, Powering the Enterprise. #PyTorch #MLOps

Thank you Ankit Patel (@nvidia, PyTorch Board) for moderating the Agents and Inference panel and for the closing reflections at PyTorch, Powering the Enterprise. @PyTorch #AIAgents

Thank you Tailin Lyu (@Pinterest) and Kyle Kranen (@nvidia) for “Making AI Pay: A Customer Case Study in Inference Economics” at PyTorch, Powering the Enterprise. #NVIDIADynamo #PyTorch

Thank you Ugur Kaynar (@DellTech) and Maroon Ayoub (@RedHat) for “Scaling AI Services: A Customer’s Journey to Production Inference” at PyTorch, Powering the Enterprise, with llm-d as the lens. #llmd #PyTorch

Thank you Tyler Michael Smith (@RedHat), vLLM core maintainer, for “The Economics of Serving AI: What Business Leaders Should Know About vLLM” at PyTorch, Powering the Enterprise. @vllm_project #vLLM

Thank you Stephen Watt (@RedHat, PyTorch Board) for opening PyTorch, Powering the Enterprise, and Joseph Groenenboom (@RedHat) and Chris Hoge (@nvidia) for “From Models to Business Value: Navigating the PyTorch Ecosystem.” @PyTorch

Thank you @RedHat, @nvidia and @IBM for hosting PyTorch, Powering the Enterprise in San Jose, and to hosts Steven Pousty, @wescpy, @cybette, Priya Sethuraman and Saša Zelenović. Our custom networks train in @PyTorch, so this is the stack we build on. #PyTorch

Thanks Rodrigo Silva Ferreira, Pallav Anand and Josh Schneider of @pytexas for speaking at @py_bay, on scientific observatories, ML explainability at scale, and mentoring.

Thanks to the maintainers who spoke at @py_bay: Anthony Sottile of @pre_commit_ci, Brian Okken, @mkennedy of @TalkPython, and Jim Baker.

The tools we use every day are kept working by people like these.

Thanks @dbreunig for "How Contexts Fail (and How to Fix Them)" at @py_bay.

AI should be more boring and more useful.

Thanks Liz Acosta of @Vonage for "Seeking validation: An introduction to Pydantic" at @py_bay.

Thanks Noah Kantrowitz of @IKEA for "Fine Print: Intellectual Property for Engineers" at @py_bay.

Every finding should trace back to the photo it came from.

Replay the real flight over the 3D model, with the photo taken at each point shown alongside. 100% RTK fixed, 0.69 cm per pixel.

onejumpinc.com/drone-insights

Thanks Mark Thoren of @ADI_News for "Python Beyond Software: Rapid Prototyping of Hardware Systems" at @py_bay.

Thanks Christopher Ariza of @RA_Insights for "Getting Started with Free-Threaded Python Using NumPy" at @py_bay.

NumPy sits under every model we train.

Thanks Bhuvan Chetty of @PlayStation for "Turning Multiplatform Media Validation into pytest Assertions" at @py_bay.

Thanks Rohan Devasthale and Lalatendu Mohanty of @RedHat for "From Source to Wheel: Solving Python's Bootstrapping Problem" at @py_bay.

Thanks Felipe Perez of @OpenAI for "Testing the Nondeterministic: Making Safe Changes in your Agent Harness" at @py_bay.

Changing an agent without breaking what works is the question we think about most.

Thanks Emma Smith of @nvidia for "The Path to Introducing Rust in CPython" at @py_bay.

Changes at the bottom of the stack reach every Python program above it.