MongoDB’s Post

💰 On My Radar 👉 What I'm watching: Applied Intuition raises at a $15 billion valuation. 18 of the top 20 non-Chinese automakers as customers. Nearly $1 billion of primary capital preserved. Why it matters to me: While everyone funded full-stack robotaxi programs some of which have since collapsed, Applied Intuition quietly built the simulation and validation infrastructure the whole industry needed. They didn't try to win the race. They built the track. The lesson isn't specific to autonomous vehicles — it's a pattern. In every technology transition, the unfashionable infrastructure layer quietly becomes the most defensible business. The same race is happening right now in enterprise agentic AI. And the equivalent of Applied Intuition's layer - the trust, governance, and memory infrastructure that has to exist before any agent can be deployed at scale - is already being built. Salesforce is doing it at the orchestration layer with Agentforce and the Einstein Trust Layer, sitting on top of third-party models rather than competing with them. Snowflake and Databricks are doing it at the data layer, because agents are only as good as the data beneath them. None of these are the names getting the headlines. OpenAI, Anthropic, and Google are. But Applied Intuition wasn't the headline either...

Couldn’t agree more with this… ‘The tech people are worried. Not about capex overbuild. They’re worried about the coming demand. Most people who are reading all the articles… about capex bubbles are thinking in terms of the technology we have today. Coding assistants and chatbots and user-generated artwork. But they’re not thinking about what it’s going to take to facilitate the existence of a hundred million autonomous cars and trucks, humanoid robots, automated manufacturing operations and other such things that are a little further out on the horizon. However, the people making these investments with trillions of dollars and multi-decade time horizons are thinking precisely this way.’ https://lnkd.in/e8J9cFVK

Amazon tested Agility Robotics's humanoid, agreed it hit every engineering goal the company had set, and then refused to put it on the floor. Not because it couldn't do the work. Because it didn't satisfy their safety requirements. I spent yesterday in the transcripts of four robotics interviews from Machina in Paris. ANYbotics, Agility Robotics, 1X, Boston Dynamics. The pattern took a while to see because everybody kept asking about hardware. None of them are selling hardware. Fankhauser at ANYbotics said it out loud: 🗨️"They don't even want the robot.They want the data." An automotive plant loses $2.3 million an hour when it stops. A quadruped at a few hundred thousand pays for itself by preventing one hour of it. That's not a robotics business. That's insurance with legs. Agility Robotics spent three years redesigning the entire machine bottom-to-top so a balancing humanoid could stand beside a person without a cage. They're going public at $2.5 billion. The product is a permission slip. Then the part nobody in the room connected. Børnich at 1X says the unlock is general internet video — make the robot human enough and the corpus already exists. Hurst at Agility Robotics, same stage, one hour apart, says that data does not exist for robot control. No training set. You generate every episode yourself. Two founders. Mutually exclusive foundations for the entire field. Neither was asked about the other. Four names in the source transcript were wrong. I fixed them, checked 41 sources, and quarantined three claims that didn't survive. The robot was never the product. #robotics #physicalai #ai

Breaking: Cognition — the startup behind Devin, the autonomous software engineer — is reportedly in talks to raise at a $40B valuation. In May it was $26B. That's +54% in under 12 weeks. What's driving it? Revenue. ARR is racing from ~$492M toward a $1B annualized run rate, with enterprise usage compounding 50% month over month. Goldman Sachs, Mercedes-Benz, and NASA are already on board. The B2B signal: value is shifting from AI tools you supervise to AI agents that ship the work. CEO Scott Wu insists Devin isn't a human replacement — but boards aren't pricing $40B on copilots. They're pricing autonomous output. When agents do the building, does your org still buy seats — or outcomes? Share your take in the comments 👇 #AgenticAI #AIAgents #EnterpriseAI #AICoding #B2BTech #AIInfrastructure

Physical AI only scales when models can handle real-world complexity. Fantastic work by our Uber AI Solutions team on securing CDAO Tradewinds Awardable status! This award underlines just how essential high-precision data labeling and trusted testing workflows are for AI in the U.S. Government.

Honored to share that Uber AI Solutions has been granted Awardable status with the DoW Chief Digital and Artificial Intelligence Office (CDAO) Tradewinds Solutions Marketplace for Advanced Data Labeling.  🤖 Advanced Data Labeling enables next-generation autonomy & reliable AI solutions in dynamic, complex environments. Our multi-sensor labeling platform helps computer vision teams fuse, track, & annotate perception and robotics tasks in a single interface. 🌍 And since we’re part of Uber, we have access to a real-world physical AI feedback loop at a massive, global scale. Uber’s work on this front is inspiring. Physical AI scales when models understand messy, dynamic, human environments - and when teams have trusted workflows to test, improve, and de-risk those models before deployment. 🤝 If you're working in this area and want to see our Tradewinds video or connect more deeply, please feel free to reach out directly. #ArtificialIntelligence #Robotics #SpatialComputing #AutonomousSystems

Proud to have helped drive this effort and bring Uber AI Solutions onto the Department of War Chief Digital and Artificial Intelligence Office’s Tradewinds Solutions Marketplace. Our Awardable status on the CDAO Tradewinds Solutions Marketplace opens the door to supporting more public-sector and defense organizations with advanced data labeling for physical AI, autonomy, and other complex environments. This is one of several initiatives I’ve been advancing as we expand Uber AI Solutions’ work across government. More to come.

Ever wondered what actually happens on the floor the day a new robot generation goes live? Last week, headlines were full of Amazon's next-gen robots that respond to natural language and can now handle loads up to 400 kg. It reads like science fiction — a robot that understands a spoken instruction and lifts almost half a ton without breaking a sweat. But here's what the press release never tells you. The morning a new robot generation lands on your floor isn't about the robot at all. Here's what actually mattered in that moment, and what I'd tell any operations leader facing the same thing: - Re-mapping the human workflow around the machine, because the bottleneck almost never sits inside the robot itself — it sits in the handoffs around it - Retraining associates on new interaction patterns, not just new buttons, because confidence takes longer to build than competence - Rebuilding safety zones and material flow before you even start measuring throughput, because a fast process that isn't safe isn't a process worth keeping The tech gets the headline. The people who quietly redesign the process around it get the results — and they rarely get the credit. What's the biggest "invisible" step you've had to solve the last time new automation hit your floor? #AmazonVestLife

Travis Kalanick's direct quote on what he's building: "CPU manipulates bits to compute information. Robots and AI manipulate atoms to compute the physical world." That's not a metaphor. It's a thesis. Uber was the proof of concept — touch glass, car arrives. Atoms as a programmable layer. Kalanick calls it "sci-fi at the time." It shipped in 2010. His new company, Atoms, is the follow-through: take that same logic from ride-sharing into every factory, warehouse, and supply chain that still runs on unoptimized physical processes. The framing matters because it changes the competitive landscape entirely. If the physical world is just an atoms-based computer, then robotics isn't automation — it's infrastructure. The same reclassification that made servers into cloud computing and phones into platforms. Kalanick's been thinking about this since Uber. That's a long time to sharpen a thesis before building the company around it.

For those that decry an AI bubble/overbuild, we are just getting started with the capacity needed for a huge increase agentic AI demand for robotics, autonomous systems, transportation, manufacturing, communications, utility operation, safety, and financial systems.