Building Artist-Centric Tools: Machine learning in production Riley Miladi, Cinesite
Event details
Co-STAR Live Lab presents... Riley Miladi
CoSTAR Live Lab is a brand new R&D facility based at Production Park near Wakefield. Live Lab is part of the £75m government-funded CoSTAR Network, and supports innovation in immersive, multisensory and interactive technologies to transform audience experience, shaping next-generation live experiences for screen, stage and into the metaverse.
We are excited to welcome Riley Miladi (Lead ML Researcher at Cinesite) for an inspiring public talk as part of our CoSTAR Live Lab Presents series on “Building Artist-Centric Tools: Machine Learning in Production”.
Recent advances in generative modelling have enabled the creation of videos, paintings, and songs from simple inputs like text. Models such as Veo 3 have made it possible for anyone to create impressive looking videos. However, these tools often come at the expense of losing artistic control and creativity. In this talk, we will explore the intersection of technology and creativity. how these models can undermine artists' creative processes and why they might not be ideal for production settings. We will discuss strategies for developing Machine Learning tools that truly empower artists and enhance, rather than hinder, artistic expression. We will also examine common challenges in translating cutting-edge research into practical, artist-friendly tools for production.
Riley’s talk will take place on the 20th of August between 1-2pm. The talk is open to in-person attendees at Live Lab’s Production Park home, and will also be available as a live online video stream. After the talk, we invite in-person attendees to join us for networking from 2pm-3pm at Production Park’s CentR Stage Cafe. This will be an excellent opportunity to engage with our speakers, fellow attendees and to meet the CoSTAR Live Lab team.
About the speaker
Riley Miladi is the Lead ML Researcher at Cinesite, researching AI driven solutions for films and feature animations. With a background in Visual Effects, they previously held a research role at Embark Studios, focusing on Deep Reinforcement Learning and physically based animation for games. At DNEG, they explored Generative Models for animation and crowds. They currently focus on leading various machine learning projects as well as leading the development of global machine learning strategy at Cinesite.