The Optimus factory construction at Giga Texas is progressing rapidly. It'll be a massive 7 million sq ft facility with a targeted capacity of 10 million Optimus per year. Initial production is planned to begin in 2027. The Fremont facility, planned for 1 million per year, is expected to begin production this year.

Giga Texas Optimus factory construction update with 2 short video clips, one 360 at medium-altitude & a closer, lower flight showing tight views of the main steel structure! Ground work started in late March, with 1st steel on May 27. By 1 October, the frame was nearly at the north grade beam, large sections of upper floors were poured, & roofing insulation is arriving. The E side & the entire S half of the foundation have footings & grade beams, but no steel yet. The basic steel structure is ~ 40% assembled so far. This is the dedicated high-volume 7+ million sq ft (~ 650,000 sq m) Gen 4 Optimus plant. @Tesla has not given a standalone cost, but 2026 company capex was guided at ~ $20–25 billion for AI, robotics, & factory expansion; outside estimates put the broader N Campus at ~ $5–10 billion. This is in addition to the Fremont California Optimus plant (which is the Gen 3 pilot line) is sized at ~ 1 million units a year, expected to begin production in late 2026. The Giga Texas plant is 10X larger & has a planned capacity of ~10 million robots a year at full scale (a long-term ceiling, not the startup rate). The current target for limited initial production is late 2027. What is still ahead for construction over the next 6 to 8 months? Electrical conduit, water & sewage pipes, fire-water loop, storm water management drainage & underground pipes, exterior walls, roofing, ground slab & upper floor concrete & mechanical rough-in then equipment deliveries & installation. As you can see, lots of progress already, but there is a lot left to do before production line setup can happen.

I was there Friday night in San Francisco for the @REK event, and this is something you had be in the room to get it, but I’ll try to describe it. It hit completely differently from robot-versus-robot fights. Those are entertaining, sure, but after a while they start to feel strange. You’re empathizing with machines that aren’t conscious, don’t feel pain, and don’t feel anything. Robot versus human hits different and raw, it was an emotional rollercoaster. I felt real fear for the human fighter, and real excitement, mostly fear, and when it ended there was a huge wave of relief. The robots were remote-controlled, of course, but the kicks were genuinely powerful. We know how power-dense those actuators are, and the human fighter took real hits to his body. The kicks from the six-foot-tall EngineAI T800 seemed nearly impossible to dodge when they were hurled in the right direction. The Unitree H1 was even harder to deal with because its dynamic balance is so good that it just refused to go down. This could be the start of a genuinely new entertainment genre. But I can tell you this: if someone wants to fight a robot with a real AI brain and real perception, you’d need robots that are far less powerful, throttled down, and compliant. Otherwise it ends in serious injury or worse. This is the beginning of something different in robotics and entertainment, and we need to think seriously about it before regulators use moments like this as fearmongering fodder to throttle the entire humanoid frontier.

Introducing Gemini 4 Argon – our new frontier model. It’s built for complex workflows across coding, enterprise knowledge work, and cybersecurity defense – rolling out today to a set of trusted testers through our Fairwind Program.

After 9 years. 16K+ family homes. 500M sqft inside real homes covered, we know home robots are being built in wrong order. So we built Matic the way nature grows a child. Finally, sharing our vision: 1.⁠ ⁠Why robots get stuck at the demo 2.⁠ ⁠Why labs can't ship robots 3.⁠ ⁠Why we started with eyes, not hands 4.⁠ ⁠The 99.999% rule in robotics 5.⁠ ⁠Where Matic is going next 1. Why most robots get stuck at demos Robot demos look brilliant in a room arranged around its limitations: familiar lighting, predictable furniture, nothing troublesome on the floor. A family’s home makes no such accommodations. There are cables, toys, shifting rugs and, occasionally, dog poop. Yes, humanoids will need to avoid that too. Repeating a task under familiar conditions of uncluttered floors is not the same as handling an unfamiliar home with all its chaos. 2. Why labs can't ship robots SLAM (Simultaneous Localization and Mapping) is how a robot maps its surroundings and locates itself within them. Ask most academics and they'll tell you it's a solved problem. But real homes are the most chaotic spaces that exist. There are glass doors that look like open doorways, mirrors, stairs, rugs, charging cables, and Legos placed all around. So ask yourself: if indoor mapping and navigation is "solved," where are the robots? Why aren't airports, hotels and grocery stores full of them? Calling it “solved” misses the question families actually care about: can I leave this thing alone and trust it? 3. Why we started with eyes, not hands Nature doesn't give birth to a fully working human. We took our cue from how nature develops humans: capabilities built on one another. Children learn to see before they learn to grab, and to grab before they learn to plan and handle the unexpected. Perception comes first. Manipulation follows. More complex responsibilities come after that. At every stage, the robot must earn the next job by doing its current one well enough. Before asking a robot to pick up a sock, we wanted it to understand where it was, where the sock was, and how to reach it. Most of the industry started at the top, with humanoids. We started at the bottom, with a robot whose job is to see and move through a home precisely with 1cm accuracy in any lighting condition. Floor cleaning gave that foundation an immediately useful job. It forced us to confront navigation, clutter, privacy and everyday reliability before reaching for more complex chores. The floor cleaner isn’t a detour from our larger ambition. It is how we’re building toward it. 4. The 99.999% rule in robotics At 90%, one in ten decisions is wrong, and a robot makes thousands in a single clean. That's the robot that bumps, gets lost, and falls down the stairs. Every extra nine is a new mountain. The failures get rarer, harder to find, and exponentially harder to fix. They barely even happen until they happen in your home. Matic's visual SLAM runs at 99.999% in 16K+ homes. We’re the ONLY unsupervised home robot at scale with pure vision-only full autonomy. If you ask us, the gap between 80% and 99.999% is where our 9 years of engineering went. We close that gap inside real homes. When Matic handles something imperfectly, it saves a short clip and keeps it on the device. It only leaves if the family chooses to share it. If they do, it gets labeled, fed back into the model, and every Matic gets smarter, including theirs. Families control what leaves their homes. We do the work of making the product better. Better robots earn trust > trust brings more homes > and more homes teach the robot more. 5. Where Matic is going next Phase one was perception and it's nearly done. Matic has covered 500 million square feet, 400K miles in thousands of real lived-in homes. Now phase two is going to be about manipulation. And our idea is to build a robot that doesn't just move through your home, but acts in it to eliminate even more chores. Each step must be useful today, not justified by something we promise tomorrow. The evolution of Matic is the revolution. The goal isn’t to put the most impressive humanoid in your living room. It’s giving your family time and energy back through robots that earn your trust, protect your privacy, and help without becoming another responsibility. More time for each other. Less work getting in the way. That’s Matic. Get yours today at maticrobots.com

Humanoid robots are starting to show up in places you might not expect, including livestreams. AGIBOT X2 humanoid robots jooined ASD’s livestream, interacting with the host, introducing products and taking part in cooking demonstrations. It’s another example of robots moving into everyday, customer-facing environments, not just performing a preset demo, but interacting and working alongside people. #AGIBOT #HumanoidRobots