Hear talks from experts on cutting-edge topics in AI, ML, and computer vision on June 26 at Microsoft NERD

A broad array of applications, ranging from search and rescue to self-driving vehicles, require robots to perceive and understand the geometry of objects in the environment. Object perception needs to reliably work in a variety of scenarios and preserve a desired level of performance in the face of outliers and shifts from the training domain. Obtaining such a level of performance requires robust estimation algorithms that are able to identify and reject outliers, as well as techniques to continually improve performance of learning-based perception modules during test-time. In this talk, I discuss my three projects on this topic: (1) solvers and a graph-theoretic framework that together help achieve state-of-the-art pose estimation performance even under high outlier rates, (2) self-supervised object pose estimators that can improve performance during test-time with accuracy comparable to state-of-the-art supervised methods and (3) a test-time adaptation method for both object shape reconstruction and pose estimation without the need for CAD models.

I built Pixie out of a desire to replace my ChatGPT workflows with a local alternative. This project runs parallel to projects like LLMStudio, caters more towards Ollama models, and thus allows us to optimize for the user experience for Ollama workflows. I will go through the different philosophies at play here, design choices and how to create a system that can substitute for the "ChatGPT experience" while remaining local and open source.

The Agentic Era is here — and it runs on APIs. In today’s AI revolution, success isn’t about who has the biggest model, but who builds the highest-quality, AI-ready APIs.
From powering intelligent agents to enabling seamless orchestration, APIs are the backbone of modern AI systems. At Postman, we see how collaboration, testing, and documentation are essential to delivering APIs that truly support AI innovation.
This talk explores why robust APIs are the foundation of the AI future—because in this new era, you simply can’t do AI without APIs.

Nothing is driving physical AI forward faster than autonomous vehicles. In this talk, I'll walk through how to build cutting-edge AV datasets using synthetic data, NeRFs, smarter curation, and vector search. It's all powered by NVIDIA Omniverse and FiftyOne, and it's a glimpse at what the future of data looks like.