Christy Anzelmo: USD, Machine Learning, surprising uses for Nuke and Foundry software and a career VFX software | TVAP EP16

Wednesday 24th November 2021

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Show Notes

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This week we talk with Christy Anzelmo, Chief Product Officer at Foundry and before that, Director of Product for the Nuke family of projects.

We take a tour of her career, beginning in the fashion industry before moving in to VFX, her role in leading development on one of the most widely used compositing softwares in the industry, and on the uses of Foundry products outside of VFX in product design, architecture and even car configuration. We talk about the rising importance of machine learning and USD in VFX, interoperability and finally we talk about working in software as a career path for VFX Artists.

Apologies for the occasional echoes in this episode - I had my headphones a little too loud.

Time codes

00:00:00 - What to expect in this episode
00:01:36 - Introduction to Christy Anzelmo
00:04:10 - Career beginning and work in the Fashion industry
00:09:30 - Foundry Products in product design
00:12:00 - Use of digital in the fashion industry
00:13:30 - Starting working on Nuke
00:15:30 - How Daniel and Christy met at her first client facing meeting
00:17:30 - The diversity of the Nuke userbase
00:18:30 - Can Christy use Nuke?
00:20:09 - The Nuke team
00:21:02 - Product Management and working in the industry
00:24:30 - What Foundry does with that long survey they send you
00:26:00 - A feature added to Nuke as a result of the survey
00:26:40 - Cara VR and 360 video
00:28:00 - Unusual uses of Nuke
00:30:00 - Car configuration with Nuke
00:32:46 - Different priorities for different companies
00:33:20 - Shake to disconnect and Apple Shake
00:34:00 - Improving usability in professional software
00:36:50 - Looking at rival software and consistency
00:39:00 - Interoperability and less linear pipelines
00:41:30 - USD and “The Dream”
00:43:12 - Copy Cat and machine learning in Nuke 13
00:48:15 - Pre-trained tools in Nuke 13
00:48:50 - IP and copyright obstacles to machine learning

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