one question i get a lot is why i started a podcast it's so hard to explain but it really is because i just find people endlessly fascinating i've always been that chatty person who'll ask 10 different questions, fall down random rabbit holes, and want to understand how other people see the world now i just get to record those conversations :)

Biological intelligence to bootstrap robotic intelligence? If robotics is about to enter its golden age, @MeckaAI is one of the companies feeding it, by sensorizing humans to train robots. The biggest challenge robotics faces is the data flywheel cold start problem. LLMs got a free cold start from the internet: trillions of tokens, already written. Robotics gets nothing. Someone has to go create the training data to jumpstart the system. @joshavata is the co-founder and CEO of Mecka, the data and deployment company for physical AI. Josh read every robotics paper he could find in late 2024, visited the labs, and made a bet: humans and humanoids look the same, so humans could act as the training fleet. Egocentric data, first-person video of people doing real work, could become vital fuel. Two years ago, the biggest egocentric dataset was Ego4D at 4,000 hours. The field is now in the millions of hours, thanks in part to Mecka. We’re probably still orders of magnitude of training data away from robotics nirvana. But every rung on the physical intelligence ladder unlocks real commercial tasks. And eventually, Josh imagines a world with an order of magnitude more robots than people, of a plurality of shapes and sizes and use cases, as the Hitchhiker’s Guide to the Galaxy foretold :) A few things we cover in this conversation. - Why robotics has no cold start: pixels, actions and logic, and why pre-training data is a real market in robotics in a way it never was for LLMs - What “teaching robots about carbon life” means: in sci-fi the final frontier is organic. The human brain runs on 20 watts and self-heals - The egocentric bet: teleop couldn’t scale, humans and humanoids share a form, so Waymo-fy the humans. The first pilot was aunties and uncles recording themselves cooking on a mobile app - Force data: video can’t tell a robot how hard to squeeze an egg. Wrist cameras are a hack. Mecka built the gloves instead - Inside the data factory: a consumer app that streams your tasks, a B2B engine recruiting across “the taxonomy of all physical human work,” 100-gigabit upload lines, hundreds of petabytes - Millions of hours vs. Tesla’s decade on two degrees of freedom, and why it’s a slow creep up, not a GPT-3 moment - The home has the most data and is the hardest place to deploy. Laundry folding and assembly-line pick-and-place get solved in the next year or two - Useful robots already exist: hotel delivery and cleaning bots in China and Southeast Asia, industrial cleaning in the US. Humanoids are the terminal state, not the first step - Deployment diffusion: a modern systems integrator whose installed robot does something next week it couldn’t do last week. If Mecka ever helps deploy a robot that mines an asteroid, they’ve done their job - The data pot of soup: a million hours of human data, tens of thousands of UMI, a few hours of in-domain teleop. Tactile and simulation haven’t entered the mix yet - Move 37 for robotics: AlphaGo went behavior cloning, then self-play, then magic. The catch is the rules of the game are the entire physical world, and we don’t have the simulator yet - Will the AGI labs steamroll robotics? “It takes a lot of courage to scale up data with imperfect information.” - The Kawasaki Corleo, the robot panther-dog-horse on Mecka’s conference room wall, and why the future of robotics looks like Hitchhiker’s Guide to the Galaxy Timestamps: 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?

the more time i spend building in physical ai, the funnier i find the idea that we're heading towards a world with millions of autonomous machines while 50% of the population (including my parents) still can't get a printer to work

i think we've overused the phrase "from first principles" to the point where i can no longer take it seriously every time i hear someone use it, it makes me laugh because it's usually followed by a take that sounds like it was pulled straight from a linkedin post

AI is getting a body, and things are about to get very interesting. Had such a fun time speaking at @0G_labs Dev Day on “AI Gets a Body: The Robotics Revolution Is Here,” during Token 2049. We talked about everything from robots moving out of labs and into the real world, to the funniest robot stories we’ve each encountered. Still think we’re incredibly early, and that’s what makes this space so exciting. s/o to @amarbedi (@tashiprotocol), @Weisiyuen (@0G_labs), and @theshikhai (@LongHashVC).

A milestone moment for Axe Compute at NASDAQ! Congratulations to the entire Axe Compute team on ringing the NASDAQ bell today At Aethir, we're proud to help @AxeCompute build the next generation of AI infrastructure together The future of compute is just getting started! $AGPU

i feel like all of singapore has been taken over by crypto was grabbing dinner and overheard so much shit about some project from the table next to me founders, just a psa that your bd is probably 3 drinks deep leaking all your company secrets to the entire restaurant

collabing with The Cercle on a series for my pod on a side of finance we rarely hear about: the next generation who will inherit family offices and eventually shepherd their family capital > earn credibility in the family IC > build your own investment conviction > carve out an identity beyond the generation before you > convince family who built their wealth in traditional businesses that you want to allocate to crypto, AI or venture > at what point do you know you’re rebelling against the generation before you because you genuinely see the world differently, versus rebelling for the sake of it excited to unpack what it means to become the next steward of family capital from the next-gen of allocators, coming soon!

i guess we’re in the “escape the matrix” ads on grab stage of the cycle ty @injective for the reminder, almost forgot i was trapped in the matrix while waiting for my cab