Lex Fridman PodcastGavin Miller: Adobe Research | Lex Fridman Podcast #23
CHAPTERS
- 0:00 – 3:22
Poetry as a window into Gavin Miller’s creative mind
Lex opens with a humorous poem excerpt to introduce Gavin’s artistic side alongside his role leading Adobe Research. Gavin explains how poetry and technology have run as parallel threads throughout his life, occasionally cross-pollinating in surprising ways.
- 3:22 – 5:44
From voice synthesis to smart homes: early experiments in “magical realism”
Gavin connects writing to early AI/agent ideas, including composing a poem for a 1990s voice synthesizer. He describes building a proto–smart home and interactive photo albums that combine sensors, audio, and context-aware behavior.
- 5:44 – 7:43
Uncanny valley in conversation: what it means for AI to “understand”
The conversation shifts to dialogue systems and the uncanny valley—when AI sounds convincing but lacks grounded understanding. Gavin argues that flexible, multi-perspective explanations and varied phrasing can make systems feel less canned and more competent.
- 7:43 – 10:00
Creativity from pixels to ideas: Adobe’s spectrum from low-level craft to automation
Lex and Gavin discuss how AI can shift creative work from tedious pixel labor toward higher-level ideation—without abandoning hands-on artistry. Gavin describes Adobe’s goal of supporting both highly controllable “analog-like” simulation tools and AI-driven acceleration for production workflows.
- 10:00 – 14:56
AI inside Photoshop/Premiere: smart defaults, faster selection, and background removal
Lex asks how AI can improve day-to-day creative workflows, especially for users who work manually. Gavin highlights practical entry points: smart “auto” settings, dramatically improved selection tools, and reliable background removal—often as a strong starting point with human refinement.
- 14:56 – 16:32
From research demo to shipped feature: robustness, intervention, and product reality
Gavin contrasts academic novelty with the demands of shipping tools used by professionals. He describes how product success depends on high success rates plus UI mechanisms for recovery when models fail, enabling creators to move from 99% to 100% quickly.
- 16:32 – 21:12
Teaching users in the moment: AI-guided learning from tutorials and context
Lex raises a key adoption issue: powerful tools are hard to learn. Gavin describes research that mines thousands of tutorial hours and uses recent user actions to recommend next steps, relevant learning content, and context-aware guidance—moving toward an “assistant + teacher” experience inside the app.
- 21:12 – 25:33
Compound AI workflows: Sky Replace and spatial search that feels like design
Gavin highlights AI projects that compress multi-step workflows into a single action. He explains Sky Replace as a compound operation (selection, stock search, compositing, relighting) and introduces Concept Canvas for spatially constrained image search where layout intent becomes part of retrieval.
- 25:33 – 28:42
Deep Fill and generative models: structure inference, resolution limits, and ensembles
The discussion turns to removing objects and filling missing regions, contrasting classic patch-based methods with neural generative approaches. Gavin explains why global structure understanding is hard, why high-resolution generation remains challenging, and how future systems may route tasks to specialized “experts” with confidence estimation.
- 28:42 – 34:28
Data, trust, and privacy: learning from users without crossing the line
Lex asks about leveraging Adobe’s massive user base to learn real workflows. Gavin emphasizes explicit permission, clear user benefit, and privacy-preserving approaches, describing a spectrum from high-level aggregate signals to opt-in detailed studies and careful governance.
- 34:28 – 43:37
AR/VR and 3D creation: immersive design, spontaneity, and UI challenges
Gavin explains how VR and AR differ: VR transports you to new worlds; AR brings digital assets into real context and demands adaptation to physical environments. They explore the promise of immersive tools for 3D layout, and the open question of whether precise CAD-like tasks can become practical in AR/VR through better interfaces.
- 43:37 – 49:14
Deepfakes, idealized selves, and imagined realities: benefits, harms, and media literacy
Prompted by another poem, Lex asks about living in increasingly artificial digital worlds. Gavin notes the long history of flattering representation (portraits) while acknowledging modern risks: impossible standards, manipulation, and the need for public literacy about what images can and cannot prove.
- 49:14 – 55:26
How Adobe Research stays inventive: interns, freedom, and the funnel from novelty to impact
Gavin lays out his philosophy that interns are essential to a thriving lab: they bring fresh ideas and enable lightweight exploration of risky concepts. He explains Adobe’s culture of researcher autonomy balanced with strategic priorities, and how projects evolve into papers, features, or longer-term bets.
- 55:26 – 58:11
2019 and beyond: assistants, high-res GANs, and the Sensei platform for scaling impact
Looking forward, Gavin highlights creative/analytics assistants that infer intent and offer helpful suggestions as a major direction. He also describes Adobe Sensei as a shared platform to standardize and deploy AI models across products, shortening the path from research idea to real user impact.
- 58:11 – 1:09:11
Snake robots as a lifelong muse: from animation physics to autonomy and personality
The conversation closes on Gavin’s robotics passion—especially snake robots—originating from 1980s animation and soft-body simulation research. He recounts iterative hardware builds, the constraints of early onboard compute, modern autonomy enabled by embedded AI accelerators, and the long-term vision of robots that can explain their reasoning and feel meaningfully alive.
