Beyond Feature Importance: Explaining Uncertainty Estimates (w/ Javier Antorán)
In this talk, Rsqrd AI welcomes Javier Antorán, PhD student at the University of Cambridge! Javier talks about the existing approaches to interpretability
Read MoreJoin this live conversation with Jay Silvas about real world applications of generative deep learning and neural radiance fields (NeRFs) for 3D object creation.
We’ll discuss interesting use cases of generative deep learning, an exciting AI field that allows computers to make original designs, pictures, poems, music, and more!
We’ll also dive into applications of neural radiance fields (NeRFs), a specific type of generative deep learning that create complex 3D models based on a relatively small dataset of images.
View past event on EventbriteAs data volume and complexity grow in an organization, sound decision making and high-quality AI products depend on having a robust approach to maintaining data health. In this talk, Anna Swigart will outline a framework for how to invest in preventative health for data, including choosing the right “data vitals” to measure, how to keep bad data from propagating through systems, early detection of anomalies using ML-driven tools like Luminaire, and being systematic about cleaning up data clutter.
View past event on EventbriteAI and ML have at least one thing in common with traditional software systems: they all fail. AI failures might consist of discriminatory behavior, of privacy violations, or even security breaches that can lead to lawsuits, regulatory fines and more. What can organizations do to avoid these pitfalls? In this talk Patrick Hall will outline a new approach to “incident response” specifically tailored to AI and it will present a free and open sample AI incident response plan. Participants will leave understanding when and why AI creates liability for the organizations that employ it, and how organizations should react when their AI causes major problems.
View past event on EventbriteCan you do UX Research on machine learning systems? Can you get feedback from real users before the AI has been built? Can you even test an ML system before you have a production-ready model? Yes, yes, and yes! In this talk, Michelle Carney will share about how she combines her background in machine learning with her expertise in UX - including the MLUX meetup she organizes, her favorite resource the People + AI Research Guidebook, and a case study on her process of doing UXR for ML.
View past event on EventbriteLet's face it - deploying trained ML models into production is a lot harder than it should be. Join us with Jason Knight and Chris Hoge from OctoML for a conversation on how Apache TVM, an open-source compiler stack, addresses the challenge of deploying models to all kinds of hardware.
View past event on EventbriteIn this talk, Rsqrd AI welcomes Javier Antorán, PhD student at the University of Cambridge! Javier talks about the existing approaches to interpretability
Read MoreIt's extremely difficult to anticipate all the ways a user might want to interact with an open-ended conversational interface. The good news is that you don't have to. Conversational driven development is a framework that can be used to both improve the developer experience and create more inclusive, robust conversational interfaces. Join us with Rachael Tatman, Senior Developer Advocate @ Rasa, where we'll walk through the conversational driven development process and its benefits and drawbacks!
View past event on Eventbrite