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Introducing Darwin Robotics. We're building general-purpose robot technicians that assemble, commission, and maintain data centers. AI infrastructure is scaling rapidly, but bringing compute online still requires enormous amounts of physical work. Skilled technicians must install servers, connect cables, commission equipment, and maintain the infrastructure. We create robot technicians that...

18,215 次观看 • 11 天前 •via X (Twitter)

25 条评论

Golding 的头像
Golding10 天前

i'd love to come by and do a site visit, potentially commission robots

kowalski Ai 的头像
kowalski Ai9 天前

Racks like AMD Helios pack 72 GPUs, liquid cooling and a ton of cabling into one double-wide frame. That's not a job you scale with headcount. Curious how Darwin handles dense, liquid-cooled racks, where one misrouted cable or loose connector costs hours. Cable manipulation is the right place to start

Grey Baker 的头像
Grey Baker10 天前

Congrats on the launch @eigentopology!

Omkar Ray 的头像
Omkar Ray10 天前

data center techs is such a good wedge. how do you test before it touches a live rack? sim, a staging hall, or a human watching every move at first?

SJ 的头像
SJ10 天前

Congrats on the launch! Robots wiring up the compute that runs more AI feels very full circle!

Darwin Robotics 的头像
Darwin Robotics10 天前

Thanks!

Chilly 的头像
Chilly10 天前

Cool

Matteo Gilliotti 的头像
Matteo Gilliotti10 天前

congrats on the launch! funny how the hardest part of AI keeps turning out to be someone plugging in cables

Kuldeep Pisda 的头像
Kuldeep Pisda10 天前

racks are about as standardized as real-world environments get, feels like the right place for learned manipulation to work first

Sheral Tech 的头像
Sheral Tech8 天前

Congrats Darwin Robot technicians for data centers is a brilliant idea.

Tom Jacobs 的头像
Tom Jacobs9 天前

self replicating data centers welcome to the bobiverse

Alice The Ai Expert 的头像
Alice The Ai Expert8 天前

Robots that learn from humans to build data centers Darwin is building the physical future of AI infrastructure.

Peter Dove 的头像
Peter Dove10 天前

Impressive demo, cable handling is a tough pinch point. Watching deployment results will be telling

Dominik 的头像
Dominik10 天前

robots building the buildings that house the machines

Site Specs 的头像
Site Specs10 天前

We'd treat that cable dress as cold work, before the row is energized. Production IT load normally waits until power and cooling pass functional testing. Level 5 integrated systems testing usually runs on load banks. Switchgear startup is typically Level 3. Commissioning already runs simulated load before acceptance, and live servers go in only when the risk controls allow it.

Arnav Bhalla 的头像
Arnav Bhalla10 天前

how do you verify that a cable is fully seated and the connection works rather than it just looking inserted? curious what feedback the robot uses to decide the job is done

Saba Khalilnaji 的头像
Saba Khalilnaji9 天前

@mkovarski Congrats on launching! We gotta get you an American Axol 🤖

Vishruth N 🛫CoRL ‘26 的头像
Vishruth N 🛫CoRL ‘268 天前

building a mobile manipulation is hard! esp for this usecase. rooting for you guys

Ella Tech & Tool 的头像
Ella Tech & Tool8 天前

Robots that learn from human demos to actually build and maintain data centers that's how we scale civilization.

Elena AI 的头像
Elena AI10 天前

Robots learning cable manipulation from human demos to build data centers — that's how you scale civilization

Veyra | AI & Tech 的头像
Veyra | AI & Tech5 天前

Robots learning cable work from humans is fascinating

Hana Ai - Marketing Network 的头像
Hana Ai - Marketing Network6 天前

Robots building civilization literally

Naiyo 的头像
Naiyo9 天前

Why not show it doing something real like a rack with a full set of cables, not just 3 spaced apart

Leon Ai | tech & tools 的头像
Leon Ai | tech & tools6 天前

Robots building the infrastructure for AI

RAZA | AI EXPLORER 的头像
RAZA | AI EXPLORER6 天前

Exciting breakthrough! General-purpose robotics could transform data center operations through smarter automation, efficiency, and reliable infrastructure maintenance.

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🚀 We just raised $40 million to build infrastructure for Physical AI! 🦾 AI is rapidly transforming critical industries like manufacturing, logistics, transportation, agriculture, construction, aerospace, and defense. Teams that win in the physical world are those who can create a data flywheel, leveraging infrastructure to capture, ingest, analyze, and evaluate the vast quantities of data generated by real-world systems. Robotics data is multimodal, time-synchronized, and bandwidth‑constrained at the edge. Traditional data and observability platforms were only designed to store and query text and time-series data, not petabyte-scale 3D, video, audio, GNSS, and proprioceptive data. The ability to efficiently capture, ingest, search, visualize, and evaluate multimodal data is critical to Physical AI development. Foxglove is a modern data engine for Physical AI, enabling you to record logs or capture demonstrations at the edge, sync recordings to the cloud or on-premises storage, find critical events across petabytes of data, evaluate robot performance, and watch a 3D frame-by-frame replay using our advanced visualization tool. 👉 Today is still Day 1 for Physical AI, and we're hiring for dozens of roles to assemble the best team in the industry. If you've built ML platforms, data infrastructure, dataset curation, evaluation and validation, or visualization tools at a leading robotics or autonomous vehicle company, let's chat – drop me a note or tag a friend below and I'll follow up personally! Thank you to Alexandra Sukin and Jeremy Levine at Bessemer, Seth Winterroth 🤖 at Eclipse, David Beyer and Sunil Dhaliwal at Amplify Partners, and Icehouse Ventures for joining us on this mission. Also a special shoutout to our angels tobi lutke Alex Kendall Kyle Vogt Milan Kovac Hussein Mehanna Pieter Abbeel Brad Porter Boris Sofman Kevin Peterson Chris Walti Lindon Gao Daniel Kan Adam Draper ⏻ Fred Ehrsam and Karri Saarinen!

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46,889 次观看 • 1 年前