What can unsupervised representation learning learn from deep RL? As it turned out, we can learn representations (unsupervised) by making plans!
Check out our new work at https://t.co/3QbKataX3b
Introducing LPM 1.0 — a video-based character performance model that speaks, sings, listens, reacts, and emotes in real time.
- Generating full-duplex conversation, identity-consistent infinite-length generation, and nuanced human-like performance.
- Building across a co-designed data pipeline, Base model, Online model, and streaming inference optimization.
- Key advantages over other video generation models: performance quality, emotional conversation, precise lip-sync, identity preservation, and lifelike naturalness.
Turning an image into a performance video, LPM 1.0 serves as a visual engine for conversational agents, live streaming characters, and game NPCs.
Page: https://t.co/Ve2c2YNuqj
Arxiv: https://t.co/cM54T3KSPs
Today, we present a step-change in robotic AI @sundayrobotics.
Introducing ACT-1: A frontier robot foundation model trained on zero robot data.
- Ultra long-horizon tasks
- Zero-shot generalization
- Advanced dexterity
🧵->
Today, we present a step-change in robotic AI @sundayrobotics.
Introducing ACT-1: A frontier robot foundation model trained on zero robot data.
- Ultra long-horizon tasks
- Zero-shot generalization
- Advanced dexterity
🧵->