#VLA
π0 Explained — How Flow Matching Changed VLA Action Generation
A source-based technical guide to Physical Intelligence's π0: the PaliGemma VLM and dedicated Action Expert, continuous action generation with conditional flow matching, cross-embodiment training across seven robot types, and the difference from autoregressive VLA models such as RT-2 and OpenVLA.
Fundamentals · 11 minTechnology Trends in Humanoid Robots
Tesla Optimus and Figure 03 have moved onto factory floors, and Boston Dynamics' Atlas has switched from hydraulic to fully electric. Unitree is driving a price war, while 1X's NEO is starting to teach itself in the home using a video world model. A look at the competitive landscape and the open problems that remain.
Trends · 9 minReinforcement Learning Primer: Imitation Learning and Inverse Reinforcement Learning
Behavior Cloning, DAgger, and inverse reinforcement learning use demonstrations when rewards are hard to write. This primer covers covariate shift, reward inference, VLA connections, evaluation, safety, and data provenance.
Fundamentals · 5 minTechnology Trends in VLA (Vision-Language-Action)
Vision-Language-Action folds camera input and natural-language instructions into a single model that outputs robot actions directly. From RT-2 to OpenVLA to Physical Intelligence's π0 lineage, surveying the spread of a design philosophy that refuses to separate perception from control.
Trends · 9 min