World Models Are Becoming Infrastructure
World models — interactive environments systems can perceive, predict, and act inside — are becoming infrastructure, not features or products.
Podcast profile
Innovating in XR & AI with Varun Siddaraju
By Varun Siddaraju — XR & AI Researcher, Founder of VeeRuby
Exploring the future of AI, AR/VR, and human-centered innovation—building bridges between technology, research, and real-world impact.
Latest episode
World Models Are Becoming Infrastructure
6 min
- Cadence
- Biweekly
- Typical length
- 6 min
- Latest release
- Sep 15
- Language
- EN
- Activity
- Current — released within 30 days
Podcast Classification
Topics
AR & VR
Augmented reality, virtual reality, devices, applications, and immersive experiences.
Spatial Computing
Computing that understands and interacts with three-dimensional physical and digital spaces.
Formats
Interview
Host-led conversation where a guest supplies most of the subject matter.
Audience level
Intermediate
Assumes basic technology literacy and familiarity with common products, roles, and terminology.
Stay connected
From the feed
Latest episodes
Episodes shown — 6 of 6
Explainability — If It Can’t Explain Itself, You Can’t Trust It
It is disclosed explicitly because this work is about trust, explainability, and human-centered systems. Explainability is the fourth and keystone problem: the property that makes a fallible adaptive system trustworthy. Adaptation must be visible, reversible, and tunable.
Adaptive Behavior — When Should AI Step In?
Adaptive behavior is the third problem: not whether a system can act, but when it should. Why timing is the hard part, why restraint reduces cognitive load, the challenge of shared state, and the trust condition — adaptation must be visible, reversible, and tunable.
Spatial Memory — Why XR Keeps Forgetting You
It is disclosed explicitly because this work is about trust, explainability, and human-centered systems. Spatial memory is the second of the four problems: holding a working memory of places, objects, tasks, and relationships across time — so you can leave and return without penalty.
Perception — Reading Human State, Not Head Position
It is disclosed explicitly because this work is about trust, explainability, and human-centered systems. Perception is the first of the four problems behind context-aware XR: reading continuous human state — attention, task, context — not just head pose.
Context Is the Real Interface
It is disclosed explicitly because this work is about trust, explainability, and human-centered systems. Context-aware spatial systems — what they are, and why XR keeps failing the real world. Episode 1 lays out the thesis: persistence, context, and world-state matter more than interfaces.