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Humanoid-GPT: A Foundation Model for Zero-Shot Humanoid Control
GPT-style Transformer pretrained on 2 billion motion frames that achieves agile, generalist zero-shot control on a real Unitree G1 humanoid for tasks like soccer, dancing, and digging. Requires no…
CHORUS: Decentralized Multi-Robot Collaboration with a Single Shared VLA Model
Finetunes a single Vision-Language-Action (VLA) foundation model so that any robot in a team can control any other. Outperforms both per-robot specialists and a monolithic centralized policy while…
RISE: Self-Improving Robot Policy with Compositional World Model
Trains a compositional world model on real robot data to enable closed-loop policy improvement via future prediction and progress evaluation, bypassing both risky real-world RL and traditional…
EmbodiedOneVision: Interleaved Vision-Text-Action Pretraining for General Robot Control
Open-source 3B unified embodied foundation model trained on 1.5M interleaved vision-text-action samples for perception, planning, and acting.
Robix: A Unified Model for Robot Interaction, Reasoning and Planning
A single vision-language model that unifies reasoning, task planning, and human-robot interaction for complex instructions and long-horizon tasks.
Robotic World Model: Learning to Simulate for Robust Robot Control
Presents a neural network-based world model for model-based reinforcement learning in robotics, focusing on sim-to-real transfer for quadrupedal and humanoid robots. Enables robust policy…
AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization
Embodied egocentric simulation framework that controls first-person worlds with 3D human motion and customizes evolving scenes via pose-anchored views.
ArtiFixer: Few-Step Diffusion for 3D Scene Reconstruction
Few-step auto-regressive diffusion model that converts broken 3D reconstructions into fully realized scenes, outperforming prior methods by 1-3 dB PSNR.
Deployment-Time Memorization in Foundation-Model Agents
Examines memorization phenomena that occur during deployment of foundation model agents in practical applications.
Adversarial Machine Learning: Taxonomy, Threat Models, and Mitigation Strategies in Deep Neural Networks
Focuses on security aspects of deep neural networks, providing taxonomy and mitigation strategies for adversarial attacks.
SoCRATES: Evaluating LLM Mediators in Conflict Scenarios
First comprehensive framework for evaluating LLM mediators in real-time, emotional, socio-cognitive scenarios.
Unembedding Matrix as a Feature Lens: Unlocking Better Text Embeddings
Improves embedding quality without extra training by using the unembedding matrix as a feature lens for text embeddings.
LeanMarathon: Autonomous Formalization of Math Proofs on Erdős Problems
Presents an autonomous system for formalizing mathematical proofs, specifically targeting Erdős problems. Demonstrates automated proof formalization capabilities in the Lean theorem prover.
Deep Research Agents: Survey and Roadmap for Autonomous AI Research
Provides a comprehensive taxonomy, benchmarks, and future directions for autonomous AI research agents. Examines systematic approaches to developing agents capable of conducting independent research.
Cosmos 3: Omnimodal World Models for Physical AI
Omnimodal world models explicitly designed for Physical AI and robotics applications. Enables improved simulation and control for robotic systems through multimodal understanding.
Humanoid-GPT: GPT-Style Transformer for Zero-Shot Dynamic Humanoid Control
GPT-style Transformer trained on 2 billion motion frames enabling zero-shot dynamic humanoid control for tasks like soccer, dancing, and digging on real Unitree G1 robots without fine-tuning. Breaks…
Bending Paper, Shaping Dexterity: The Robotic Origami Challenge
New IROS benchmark providing 500+ teleoperation episodes and physically accurate simulation assets for training policies that outperform human origami experts.
GraspGen-X: A Foundation Model for Zero-Shot 6-DoF Grasping
First foundation model for zero-shot grasping trained on billions of simulated grasps, enabling generalized manipulation without task-specific training.
When Does Deep RL Beat Calibrated Baselines?
Benchmark study examining when deep reinforcement learning outperforms calibrated baseline methods in adaptive resource control tasks.
Training Deep Networks as Random Effects: An Optimization–Inference Duality
Explores training dynamics of deep neural networks through a statistical lens, examining the duality between optimization and inference perspectives.
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Embodied AI 101 has published 105 episodes since March 2026, covering topics in Science, Technology.
Embodied AI 101 is currently highly active with new episodes hourly. Average episode length is 29m.
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