• Elon Musk said a shortage of training data meant teaching Tesla's Optimus robot is like raising a toddler.
• Tesla has built an "Optimus Academy" where robots can learn through "self-play," Musk told investors.
• The EV giant said on Wednesday that it had begun production of Optimus.

Tesla is sending its Optimus humanoid robot back to school.

Speaking on the company's earnings call on Wednesday, CEO Elon Musk compared training the EV maker's humanoid robot to raising a toddler.

Musk said that while Tesla's autonomous driving models can learn from data collected by its massive fleet of vehicles, its Optimus robot has to learn by watching people do tasks and practicing them itself, a process similar to how humans learn.

"You can see this when you have a toddler, and they initially are sort of wobbly, and they don't know how to do things, and eventually, they learn to wipe their own ass, which is a big milestone," Musk told investors.

"They learn to read and do all sorts of things, and they learn this by playing. And we actually need Optimus to play at scale in order to have it be really good at tasks in the real world," Musk said.

The Tesla CEO added that the company was building out an "Optimus Academy" where prototypes can practice a wide range of tasks and generate training data to teach future versions of Optimus.

"For Optimus to get the training data we need, we actually need to make a lot of Optimi. So we need to make, I think, on the order of 10,000 or 20,000 bots and then have them do self-play," said Musk.

Tesla said on Wednesday that it had begun production of Optimus at its Fremont factory, with Musk saying the company expects to begin delivering Optimus to customers by the end of next year.

The near-trillionaire cautioned that production would be "somewhat bumpy" and that development of the humanoid robot still has some way to go.

He listed the challenges of designing durable yet responsive robotic hands, as well as AI capable of handling open-ended tasks, among the main hurdles Tesla faces.

Tesla is not alone in setting up robot academies to provide training data for humanoid robots.

Unlike large language models like ChatGPT, which were trained on the vast corpus of text data available on the internet, robotics faces a shortage of real-world training data to teach humanoids to navigate the physical world.

Other startups, such as Texas-based Apptronik, have also set up "data factories" where robots load conveyor belts and sort objects to generate training data to combat the data shortage.

• Tesla has begun production of its humanoid robot, Optimus, in Fremont, California.
• Musk said he expects to begin delivering Optimus to customers at the end of 2027.
• Musk said it will take at least a year to produce 20,000 Optimus units a week.

Tesla has begun producing its long-awaited humanoid robot, Optimus, at its Fremont factory, the company said in its quarterly earnings report.

"The bots coming off this line are the first production-quality bots that we have manufactured," Tesla said, saying the current manufacturing process is "suitable for a commercial product."

"There's still some things we need to tweak about the design, because you need to deliver a robot that is safe and reliable and has long duration," CEO Elon Musk said on Tesla's Q3 earnings call. "It can't, like, wear out after a month."

Musk said the company will take at least a year to scale up Optimus production to 20,000 units a week in Fremont. He said he expects to begin delivering Optimus to customers at the end of next year.

Musk tempered expectations about how quickly Tesla can scale up Optimus production because it is "such a radically new product." He said the early stages of production will be "somewhat bumpy" because "there's like 10,000 things that have to go right" to build the robot. One of the big challenges Musk outlined is building robot hands.

Musk said Tesla is building an "Optimus Academy," where robots will practice tasks and generate data to improve the AI models that power them. The company also plans to install its next-generation AI5 chip in Optimus in April, which will give the robots more computing power and be a "big step change in intelligence," Musk said.

The latest version of Optimus has not been unveiled. Musk said he expects to release a video of Optimus within one or two months. He previously said Tesla was keeping the robot under wraps to prevent competitors from copying its design.

Tesla stopped producing the Model S and Model X at its Fremont, California, plant earlier this year to make room for an Optimus line designed to eventually produce a million robots a year. A second line under construction in Austin is planned to have an annual capacity of 10 million robots.

Tesla is competing in a crowded humanoid market. Agility Robotics, which plans to go public, has deployed its Digit robot across nine customer facilities, while Figure AI has announced deployments in logistics and distribution centers this year. Sunday Robotics, 1X, and Weave Robotics are preparing to ship robots into homes this fall.

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• You can sign up for Business Insider's daily newsletter here.

Daft Punk only had it half right. Robots don't just rock; they also draw a ton of investment.

The French musicians who famously donned robot helmets retired five years ago, but Silicon Valley's obsession with robotics is reaching a fever pitch.

Robotics and physical AI companies raised $33.4 billion globally in the first half of 2026. It's a stunning rise for a sector that didn't even hit $5 billion in funding in all of 2020.

Rya Jetha, our resident robotics expert, wrote about why Silicon Valley is betting billions on a robot revolution. It's the first installment in Robonomics, our new series examining the rise of robots and their impact on business, jobs, and everyday life.

The size of the market that robotics can address is a big draw. The need for physical labor is so vast — from construction sites to at-home butlers — the possibilities are almost endless.

Nvidia CEO Jensen Huang, a huge proponent of physical AI, valued the industry at … $50 trillion.

Just because the opportunity is there doesn't mean it'll be easy to realize.

Here are some of the biggest pain points standing in the way of the robotics revolution:

Not an easy hand-off: When talking about robots, the discussion typically starts and ends with human hands. It turns out our paws are pretty special, and quite difficult to recreate.

Granted, not every company wants to replicate the human hand. But a lot of tasks require the dexterity we have. Figuring out how to build those capabilities into robots hasn't been easy.

Hardware is hard: Building robots has gotten considerably cheaper than years ago thanks to advancements in computing and hardware. It's still a much more expensive endeavor than most software work, though. It's one thing to rewrite some code. It's another to build an entirely new prototype.

Those problems get magnified as you try to scale up physical production. The smallest mistake becomes a bigger problem if it gets too far down your supply chain. Just ask Elon Musk about it.

Human pushback: Companies often pitch AI tools as a way to enhance, not eliminate, human workers. Whether that's the reality is up for debate. Building robots to perform the same physical labor as humans leaves less room for interpretation.

Some still don't see it as a zero-sum game. Edward Mehr, the CEO of robotics startup Machina Labs, previously told me his new factory had the same number of human workers as one at a robot-free facility.

If robots do start replacing humans, they'll have to navigate another nuance specific to the blue-collar world: unions.

AI has benefited some blue-collar workers, including those involved in building AI data centers. That construction has been a boon for tradespeople, with some national labor unions even siding with developers.

They'll be a lot less friendly if robots mean replacing their members, though.

For decades, hardware was a hard sell in Silicon Valley. Now investors are pouring tens of billions into machines that can do things in the real world.

A Goldilocks set of conditions has made robotics one of tech's hottest bets. As investors look beyond chatbots to the next frontier in AI, cheaper hardware, smarter AI models, labor shortages, and competition with China are fueling interest in machines capable of performing physical work.

Robotics and physical AI companies raised $33.4 billion globally in the first half of this year alone, according to PitchBook data. That's already more than the $28.7 billion the sector raised in all of last year — and an astronomical rise from 2020, when funding came in at just under $5 billion.

Investors are writing billion-dollar checks to fund both the machines and the AI brains behind them. Defense company Anduril raised $5 billion in May, co-led by Thrive Capital and Andreessen Horowitz. Autonomous shipbuilder Saronic raised $1.75 billion in March in a round led by Kleiner Perkins. Skild AI, which builds software to control different kinds of robots, raised $1.4 billion in January in a round led by SoftBank. Physical Intelligence, which is also building an AI model to command robots, raised about $1 billion in May, co-led by Leopold Aschenbrenner's Situational Awareness and Lux Capital.

"This is off the charts," Ken Goldberg, a UC Berkeley robotics professor and cofounder of warehouse robotics startup Ambi Robotics, told Business Insider. "In my 45 years in this field, this is the most funding and energy and interest in robotics that I've ever seen."

This is the first installment of Robonomics, Business Insider's new series on the rise of robots and their impact on business, jobs, and everyday life. We'll go inside factories and warehouses where humans work alongside robots, meet the founders, investors, and workers driving the boom, and examine how the technology is reshaping industries from manufacturing to defense. We'll also ask how close robots are to becoming part of everyday life, and what is still standing in their way.

The prize is enormous. Unlike software, which is largely confined to work done on screens, robotics companies are going after physical labor, from factories and construction sites to robot butlers in every home. Nvidia CEO Jensen Huang, who popularized the term "physical AI," has described robotics as the "technology industry's first opportunity to address a $50 trillion industry that has largely been void of technology until now." Many Nvidia veterans have launched their own robotics startups.

But investors are pricing companies as though the robot revolution has already arrived. Startups still in research and development command multibillion-dollar valuations, often with little revenue and few deployments to show for it. Humanoid maker Figure AI, for example, secured a $39 billion valuation last year, even as its deployments remain limited to small factory pilots.

"Robotics is going to happen, and a lot of money will still be lost," said Sarah Guo, founder of the venture firm Conviction, which is an investor in robotics startups Sunday Robotics and Watney. "Both things are true."

From not to hot

From industrial arms assembling electronics to Roombas cleaning floors, robots have long been part of everyday life.

What venture investors struggled to see was how to make money from them. Building robots required expensive hardware, factories, and supply chains, often to produce machines that could perform just one narrow task. Why fund that when you could back a college dropout building the next viral app?

Guo used to tell fellow investors that robotics was a good way to lose a lot of money over many years. "The models didn't work," she said. "Every robot was a brittle, single-purpose system hand-built for one task."

Ajay Agarwal, a partner at Bain Capital Ventures, was among the few investors willing to bet on robotics during the internet era. In 2004, he backed Kiva Systems, which pioneered warehouse automation with fleets of mobile robots that brought products directly to human workers.

Bain led every successive funding round because Kiva was "not able to raise money on Sand Hill Road," Agarwal told Business Insider. By the time Amazon bought it for $775 million in 2012, Bain was its only institutional investor.

More than two decades later, AI has changed the calculation. Advances in machine learning are helping robots perceive their surroundings, make decisions, and adapt to new tasks, raising hopes that companies can build more versatile machines instead of engineering a different robot for every job. Cheaper computing and hardware are also making the economics more attractive.

Some of Silicon Valley's biggest names are now chasing that vision. Former Uber CEO Travis Kalanick's Atoms raised $1.7 billion in July to pursue automation in food, mining, and transportation. Rivian CEO RJ Scaringe's Mind Robotics has raised $900 million this year, while former Cruise CEO Kyle Vogt's home robotics startup, The Bot Company, has raised at least $300 million.

Big Tech and AI labs, too, are joining the rush. OpenAI has advertised robotics jobs with base salaries reaching $500,000 a year. Meta acquired robotics startup Assured Robot Intelligence in May and is testing robots in its data centers. Google has invested in humanoid maker Apptronik, which is also working with DeepMind to develop AI models for robots. Elon Musk, meanwhile, is staking Tesla's future on the Optimus humanoid.

Some venture firms are setting aside dedicated capital for robotics. In August, Andreessen Horowitz raised $1.1 billion for "Machine Age," its first fund focused on the physical infrastructure behind AI, including robotics.

The gold rush

For longtime robotics investors, alarm bells are ringing. Industry veterans whisper about "hardware tourists" piling into robotics deals — investors drawn by AI hype who underestimate how difficult it is to build machines that work reliably in the real world. There is precedent for caution. Venture firms poured billions into autonomous vehicles in the 2010s, only to see startups fold or consolidate as self-driving technology proved harder and more expensive to commercialize than expected. Years later, only a handful of deep-pocketed players have managed to bring robotaxis to the public.

Robotics faces its own formidable obstacles. Unlike large language models trained on vast amounts of internet text and images, robots lack a comparable trove of data showing them how to act in the physical world. Dozens of startups are now scrambling to collect it, but nobody knows how much will be enough. And even smarter AI won't eliminate the challenges of manufacturing, maintaining, and deploying expensive hardware.

"The most difficult part of physical AI is the physical part," said Charly Mwangi, a partner at VC firm Eclipse who has backed The Bot Company and robotics startup Genesis AI. "The next few years are going to be really, really hard for the robotics industry as companies go from the lab to deployments."

Some of the most speculative robotics bets are attracting the biggest checks. Humanoids and general-purpose robot models were the two fastest-growing areas of robotics investment last year, according to venture firm F-Prime. "You cannot raise money on demos forever," said Sanjay Aggarwal, an F-Prime partner and coauthor of the firm's annual robotics report. "I would personally be surprised if all these companies independently exist two or three years from now."

There are signs that some startups are becoming real businesses. Field AI, which is building an AI "brain" that works across robots, has crossed $100 million in revenue and customer contracts from more than 30 customers, including construction firms, data center operators, and defense companies, Business Insider previously reported. Skild AI said last month that it had reached $100 million in annual recurring revenue from more than 60 customers. Its projects include robots assembling Nvidia's Blackwell chips with Foxconn and kitchen pilots with Mitsui, a Japanese conglomerate.

Believers see robotics on the cusp of a breakthrough that could put machines to work in nearly every corner of the economy. Brad Porter, the former head of Amazon Robotics who now runs workplace robotics startup Cobot, says the field could be nine to 18 months away from major advances in dexterous manipulation — the ability of robots to handle objects with the ease of human hands.

"When I think of a 'ChatGPT moment' for robotics, it is cracking dexterous manipulation," Porter said. "Then there will be a Cambrian explosion of robots."

The question is whether these breakthroughs will arrive quickly enough to justify the money pouring in.

At Business Insider's Growth Mode event this month, Menlo Ventures partner Matt Murphy singled out robotics among the fields attracting enormous amounts of financing "before they're really showing traction." Abundant funding, he warned, can make startups "sloppy."

For investors, he said, that means "a lot more opportunity to have a really big crater."

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Ukraine’s six-wheeled Frodo ground robot fired on targets during a demonstration in Kharkiv Oblast for the Pomsta (Revenge) Border Guard Brigade, a border guard detachment posted on Facebook. Frodo made its public debut only on 30 September.

Ukraine had contracted more than 22,000 ground robots for 2026 by July, mostly logistics carriers, with combat models the smallest group, the Defense Ministry said. Frodo’s first reported mission was an evacuation. The demo shows its armed version to a fighting brigade, the kind of robot Ukraine has ordered least.

What the armed version carries

The platform completed its tasks at a training ground in near-combat conditions, said the 3rd Border Guard Detachment named after Hero of Ukraine Colonel Yevhenii Pikus. The Buria turret mounted on Frodo can fire either a Mk 19 automatic grenade launcher or a Browning M2 heavy machine gun. It engaged targets at up to 1.3 km (0.8 mile), the detachment said.

The 47-kg (104-lb) module has a ballistic calculator, stores up to 256 targets, aims in three seconds, and has a stated autonomous run time of up to 48 hours, the post said. Frodo is rated for up to 150 km (93 miles) on paved roads and 75–80 km (47–50 miles) over rough terrain, the post added. A Frontline Robotics Zoom reconnaissance drone flew reconnaissance during the test.

The developer, Frontline Robotics, describes its core philosophy as arriving fast, doing the job, and leaving very fast—hit and run, the detachment’s post said. Familiarizing the brigade’s soldiers with such systems aims first and foremost to preserve personnel’s lives and health, the detachment said.

A robot first reported as a medevac

Frontline Robotics told Militarnyi at the unveiling that Frodo had passed Defense Ministry codification and was built for logistics, evacuation, and strike missions. The robot reaches 40 km/h (25 mph) and carries up to 200 kg (441 lb) of payload, or 400 kg (882 lb) at most, the company said. A single soldier can swap its batteries.

The 92nd Assault Brigade used an early test unit to evacuate a wounded soldier, Frontline Robotics told Militarnyi. An operator, callsign Tango, named the robot’s speed and its ability to handle complex maneuvers as its main advantages, Militarnyi reported.

National Guard commander Major General Oleksandr Pivnenko signed a follow-on contract with Quantum Frontline Industries managing director Matthias Lehna and Frontline Robotics chief technology officer and co-founder Pavlo Kosolapkin to build two Ukrainian drones in Germany, Quantum Systems said on 5 October. The deal covers the Linza strike drone and the Zoom reconnaissance drone, exceeds the volume of the 2026 agreement, and schedules delivery for 2027.

The order scales up a line that is already running. Quantum Frontline Industries' first production year remains on track for completion in 2026, it has already delivered its first drones to Ukraine's Defense Forces, and it is now preparing to increase production capacity fivefold for next year, Quantum Systems said.

German plants, Ukrainian designs

Quantum Frontline Industries is a German-Ukrainian joint venture of Frontline Robotics and Quantum Systems. Both the Linza and the Zoom come from Frontline Robotics, and the systems are manufactured in Germany for Ukraine.

Explore further

German defense firm has made Ukraine its second-largest international base

Linza 3.0 carries up to 4 kg of payload out to 15 km and stays aloft up to 60 minutes, and it is already in service with more than 60 Ukrainian units, Frontline Robotics has said. Zoom 3.0 detects targets, fixes their coordinates, and corrects fire under active Russian jamming, the company told Militarnyi. It loiters for up to an hour and works at a tactical radius of up to 20 km. AI-driven navigation and autonomous operation over the target keep its data flowing even when standard radio links break down.

From ramp-up to serial production

Quantum Frontline Industries said the contract moves it from initial production ramp-up toward sustained, high-volume manufacturing. Kosolapkin told Militarnyi the firm keeps refining Linza and Zoom on feedback from Ukrainian troops, whose needs drive how the systems evolve, and that producing in Germany gives it extra capacity to scale Ukraine-proven designs and deliver them in larger volumes.

It’s getting better all the time (Better, better, better) It’s getting better all the time I admit it’s getting better –The Beatles In an X post, Marko Jukic, senior analyst at Bismarck Analysis, lamented: “Enshittification” is sort of a “safe horny” term for what is really just outright impoverishment and declining living standards due to […]

The post US enshittification vs Chinese involution appeared first on Asia Times.

What once felt like science fiction, an AI robot Olympics, now looks more possible as robotics improves. Reports mention sprinting, soccer, table tennis, gymnastics, and other tests. The World Humanoid Robot Games in Beijing brings in more than 2,000 robots for 51 events. That scale shows how fast robot sports are growing.

Still, could robots run something like their own Olympics one day? It could happen. But getting a world wide version would mean big upgrades in tech, clearer event rules, stronger safety, and a solid way to organize it across countries.

Robots are already competing in sports

The idea is now more than just theory. The World Humanoid Robot Games has made a global stage where robots take part in sports and show what they can do in motion. In August 2026, a Chinese humanoid robot named Tiangong Ultra is said to have run the 100-meter dash in 8.86 seconds. That time beats Usain Bolt's well known mark of 9.58 seconds.

These events let teams study balance and how a machine moves. For viewers, it is a fun way to watch progress in robotics unfold.

What would an AI robot Olympics look like?

A future AI robot Olympics might look like the human Games, but add contests made for machines.

In the main lineup, there could be robotic sprint races, robot jumping events, robot swimming, robot soccer, robotic weightlifting, and robot gymnastics. Alongside those, there could also be robot-only events that check battery use, fine control, path finding through obstacles, long mechanical runs, gripping and moving objects, and doing tasks with less outside help.

Robots would not be judged in the same way as people. Some scores could come from the kit itself, like the sensors, the motors, and the software setup. Organizers might also ask how well the system handles shifts in its surroundings, or how steadily a robotic hand finishes tricky work.

With this setup, a robot Olympics would feel more like a tech contest than a simple sports meet. It could draw teams from around the world to prove who builds the better machine.

AI would be just as important as hardware

A big contrast between sports played by people and robot contests is how much artificial intelligence is involved. A robot’s body still matters, but it is also tested on how it reads the world, avoids trouble, and chooses what to do next.

The International Olympic Committee has pointed out that AI matters more and more. It did this with the Olympic AI Agenda, and the plan talks about using AI in a way that stays focused on people throughout the Olympic Games.

So a coming robot event could link AI work with real athletic effort. The contest could set up tasks where deciding on the fly is just as critical as raw speed.

There are still major challenges

Robots have made real strides, but they still cannot fully take over normal sports run by people. A few humanoid machines can sprint at high speed. Yet they often trip on simple tasks like slowing down, staying upright, or getting back up after a fall. In recent events, there were crashes that showed gaps in current engineering.

If robots were to compete regularly, clear rules would be needed. People would have to decide what kind of machines are allowed. Would it be remote control only, full autonomy, or some kind of mix with assistance? There would also need to be set limits for the gear and the code. Battery limits and safety rules would matter too. The goal would be to keep the games fair even in PH Bingo on GameZone.

Could it become a major global event?

It feels more likely now than it did a few years back. More countries are joining in already, and many robotics events are getting tougher and more advanced. If the tools keep getting better, an event built around AI robots could bring in makers, schools, major tech firms, and robotics teams from many places.

For people who like tech and digital games, this kind of change also shows how fast interactive stuff is moving. If you have been watching new trends in gaming and online entertainment, you might run into sites such as PH Bingo on GameZone. That is one more sign that digital tools keep reshaping how people relax.

An AI robot Olympics plan would still take time, so it is not ready yet. Still, the base work is happening. Today’s robot contests already show that machines can handle more complex physical tasks. As AI models, sensors, power systems, and robot parts improve, the gap between a science demo and a real sport may shrink in a way that draws more attention.

Right now, the traditional Olympics belongs to people. But the growth of robot contests hints that a separate global event for machine athletes may be closer than many expected.