INFORMAZIONI SU QUESTO EPISODIO
Robotics never got the internet's gift of free training data, so someone has to manufacture it. Josh Gao, founder and CEO of Mecka AI, runs one of the largest robot data factories, and he explains what that actually involves: custom baseball caps and tactile gloves because nothing off the shelf captures force, 100-gigabit upload lines to move hundreds of petabytes, and custom quality gates. Josh lays out the training recipe the industry is converging on (roughly a million hours of egocentric human data, tens of thousands of hours of robot data, and a few hours of in-domain teleop ) and why tactile and simulation data still have to enter the "data pot of soup." He argues the field is still orders of magnitude behind Tesla's FSD, which spent a decade on two degrees of freedom while a robot hand has dozens. His take: there won't be a single GPT-3 moment for robotics, but a steady unlock of commercial tasks, starting with constrained industrial work and ending, he hopes, with robots mining asteroids.
Hosted by Sonya Huang, Sequoia Capital
0:00 – Introduction
1:46 – What Mecka is: pixels, actions and logic
2:45 – Is robot data economically feasible without the internet?
4:15 – Teaching robots about carbon life
5:27 – Cloud kitchens, stablecoins and the path to robotics
7:03 – Entering robotics with a fresh lens
8:45 – What egocentric data is and why Mecka bet on it
10:09 – The first pilot: aunties and uncles with a mobile app
10:42 – Force data and tactile gloves
11:55 – Inside the operations of a data factory
14:41 – Heat-mapping the taxonomy of human work
15:42 – Quality gates, fraud and the McDonald’s POV videos
17:44 – Earning a margin as a data intermediary
19:33 – Millions of hours vs. Tesla’s decade
20:55 – Why it isn’t binary: unlocking commercial tasks along the way
22:02 – Home data is plentiful; home robots are the hardest
23:24 – Useful robots can be deployed today
24:35 – When robotics gets an FSD-style flywheel
26:42 – Deployment diffusion and the modern systems integrator
28:21 – Favorite vertical robot categories; mining an asteroid
30:08 – The hardware slate: Waymo-fying people
30:55 – EgoVerse
32:04 – The data pot of soup: the converged training mix
33:54 – Move 37 for robotics: AlphaGo and Federer
36:02 – World models and the training mix
36:58 – Will scaling the current mix get us to the promised land?
39:05 – Will the AGI labs steamroll robotics?
40:50 – Sci-fi roots and the Kawasaki Corleo
42:44 – How many robots in a decade?
