Aug 08, 2026

Why Robotics Still Isn't Solved - But Could Be Soon | YC Paper Club

This Paper Club delves into the current state of robotics, addressing roadblocks like the sim-to-real gap and embodiment drift. Speakers present advancements in multi-scale memory for long-horizon tasks, self-supervised embodied reasoning, zero-shot dexterous manipulation via massive simulation, and the economic imperative of teleoperation-first robotics companies, concluding with optimizations for efficient, real-time World Action Models.

Jul 25, 2026

What Big Tech Missed And How Startups Can Still Win

Alexandre LeBrun, CEO of AMI Labs, discusses his career building and selling AI companies, emphasizing his strategy of tackling problems "20 years too early." He delves into AMI Labs' contrarian bet on "world models" over traditional LLMs, highlighting their ability to learn directly from real-world sensory data, unlike LLMs which learn from human-written text. LeBrun explains how this approach is critical for developing intelligent robots and avoiding the pitfalls of Vision-Language Assistants (VLAs). He also touches upon the challenges of securing talent, data, and compute for such an ambitious project, the strategic choice of location, and the importance of holding an extremely large vision while solving a narrow problem for early founders.

Jul 26, 2025

Robotics: why now? - Quan Vuong and Jost Tobias Springberg, Physical Intelligence

Quan Vuong and Jost Tobias Springenberg from Physical Intelligence (PI) discuss their mission to create a universal model for controlling any robot. They detail their approach, which centers on Vision-Language-Action (VLA) models, a purpose-built data engine for scaled data collection, and the evolution of their models toward open-world generalization.