Redwood City, California – on a new morning, knocked on the front door to an elegant two -storey house in Redwood City, California. In a few seconds, the door was opened by a faceless robot, dressed in a beige jumpsuit that perfectly adapted to his narrow waist and long legs.
This narrow humanoid greeted me with what seemed to be a Scandinavian accent, and I offered a handle. When our palms met, he said, “I have a firm clip.” When the owner of the house, a Norwegian engineer named Bernt Børnich, ordered a bottle of water, turned the robot, went to the kitchen and opened the fridge with one hand.
Artificial intelligence already drives cars, writes tests and develops data codes. Now humanoids – machines are built to look like human and driven by AI – about to enter our homes to help with daily tasks. Børnich is the CEO and founder of a start called 1X. Before the end of the year, your company expects to put its robot, Neo, in more than 100 homes in Silicon Valley and elsewhere. Your start is among the dozens of companies that plan to sell humanoids to homes and companies.
Since 2015, investors have injected $ 7.2 billion into more than 50 start -up companies, according to Pitchbook, a research company that monitors the technology sector. Humanoid Fever hit a new peak last year, when investments exceeded $ 1.6 billion. This value does not include the billions that Elon Musk and Tesla, his electric car company, invest in Optimus, a humanoid that started building in 2021.
Entrepreneurs like Børnich and Musk believe that humanoids, one day, will do much of the physical work that is currently done by people, including housework such as cleaning benches and emptying of washes, work in layers such as separating packages and working in factories such as mounting cars in production lines. Simpler robots – such as small robotic arms and autonomous carts – have long shared the workload in warehouses and factories. Companies are now investing that machines can take on a broader range of tasks by imitating human movements, such as walking, trapping, cheering, reaching, holding and generally performing activities.
Videos on the Internet have been circulating for several years that show the remarkable skill of these machines, but they are often guided by people. And simple tasks, such as carrying the dishwasher, are far from simple for them. “There are many videos out there that give a false impression on these robots,” said Ken Goldberg, professor of robotics at the University of California in Berkeley. “Although they seem human, they don’t always behave as human beings.”
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Neo said “Hello” with a Scandinavian accent because he is run by a Norwegian coach in the basement of Bøornich’s house. (In the future, the company plans to create a call center where maybe dozens of techniques can support robots.) The robot went alone through the dining room and the kitchen. However, the coach spoke to Neo and led remotely with a virtual reality headset and two wireless joysticks.
Robots are still learning to navigate the world autonomously. And at least at the moment they need a lot of help to do it.
“I saw a hardware level that I didn’t think was possible”
I visited 1X office in Silicon Valley for the first time almost a year ago. When a robot named Eve entered the living room, opened and closed the door, I could not avoid the feeling that this wide robot was actually a costume person. Eve moved on wheels, not legs. Yet it seemed human. I thought of “The Sleep” (“Sleeper”), Science Fiction comedy from Woody Allen, 1973, full of robotic controls. The company’s engineers had already built Neo, but he had not yet learned to go. A first version was hung on the wall of the company’s laboratory.
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In 2022, Børnich entered a zoom call with an AI researcher named Eric Jang. They had never met. Jang, now 30, worked in a robotic laboratory at the Google head office in Silicon Valley, while Børnich, now 42, ran a start in Norway by the name Halodi Robotics. A potential investor had asked Jang to gather information about Halodi to assess whether it was worth investing. Børnich introduced Eve, something he dreamed of building from a teenager, inspired – like many robotists – by science fiction (his personal favorite: 1982 movie Blade Runner).
Jang was fascinated by how Eva moved. He compared the conversation on a science fiction drama scene “Westworld”, where a man participates in a party and is shocked to discover that everyone in the room is robots. “I saw a hardware level that I didn’t think was possible,” Jang said.
The potential investor did not invest in halodi. But Jang soon convinced Børnich to unite forces. Jang was part of a Google team that taught new skills with the help of mathematical systems called neural networks, which allows robots to learn from data representing real world tasks. After seeing Eva, Jang told Børnich that they should apply the same technology to humanoids.
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The result was a transatlantic company that they renamed 1X. The start, which has grown to about 200 employees, now has more than $ 125 million in investors’ financing, including Tiger Global and Openai.
“All this behavior is learned.”
When I returned to the company’s laboratory about six months after I met Eva, I was received by a neo who already knew how to go. They taught him to go completely into the digital world. By simulating real -world physics in a video game – -like environment, they managed to train a digital version of the robot to stand up, balance and eventually take steps. After months to train this digital robot, they transferred everything he had learned to a physical humanoid.
If I got in the way of Neo, he would stop and divert me. If I pressed his chest, he remained standing. Sometimes he stumbled or did not know exactly what to do. But he could walk a room similar to people. “All this behavior is taught,” Jang said while Neo clicked against the floor with each step. “If we put it in any environment, he should know how to do this.”
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However, training a robot to perform housework is a completely different perspective. Since the physics involved in wearing a dishwasher or folding clothing is extremely complex, 1X cannot teach these tasks in the virtual world. She must collect data in royal houses.
When I visited Børnich’s house a month later, Neo began to have difficulties with the refrigerator’s stainless door. The robot’s Wi-Fi connection had fallen. But as soon as the hidden technician restarted Wi-Fi, he led the robot smoothly in his little task. Neo gave me a bottle of water. I also saw Neo wear a washing machine and gently hook to get clothes from a laundry basket. And while Børnich and I talked outside the kitchen, the robot began to clean the counters. All this was done through remote control.
“What we sell is more a journey than a destination”
When leading Neo on household chores, Børnich and his team can collect data – with cameras and other sensors installed on the robot itself – which shows how these tasks are performed. Then 1X engineers can use this data to expand and improve NEO’s skills.
Just as chatgpt can learn to write academic works by analyzing texts taken from the internet, a robot can learn to clean windows by identifying patterns in digital video hours.
Building a humanoid like Neo costs about the same as making a small car – tens of thousands of dollars.
To achieve its potential, Neo must catch videos of what is happening in the houses. In some cases, technologies will be able to observe what is happening in real time. In essence, this is a robot you learn as you work.
“What we sell is more a trip than a destination,” Bøornich said. “It will be a way really full of obstacles, but Neo will do things that are really useful.”