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Elon Musk has been promising robotaxis since at least 2016. Back then, the idea sounded like a bit like science fiction, and Musk’s timeline was — as ever — aggressively optimistic. Nearly a decade later, fiction is expected to finally become fact: On June 12, Tesla (TSLA) is expected to show off its first real…
It’s a regrettable reality that there is never time to cover all the interesting scientific stories we come across each month. In the past, we’ve featured year-end roundups of cool science stories we (almost) missed. This year, we’re experimenting with a monthly collection. May’s list includes a nifty experiment to make a predicted effect of special relativity visible; a ping-pong playing robot that can return hits with 88 percent accuracy; and the discovery of the rare genetic mutation that makes orange cats orange, among other highlights.
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TU Wien
Perhaps the most well-known feature of Albert Einstein’s special theory of relativity is time dilation and length contraction. In 1959, two physicists predicted another feature of relativistic motion: an object moving near the speed of light should also appear to be rotated. It’s not been possible to demonstrate this experimentally, however—until now. Physicists at the Vienna University of Technology figured out how to reproduce this rotational effect in the lab using laser pulses and precision cameras, according to a paper published in the journal Communications Physics.
Hugging Face is best known as a platform for machine learning and AI development, but it has also been dabbling in the world of robotics. This week, the company revealed two new robots it plans to bring to market—including a humanoid one that it would sell for around $3,000, far less than many of the other options that have been floated, like Unitree’s $16,000 G1.
Dubbed the HopeJR, Hugging Face’s robot has up to 66 actuated degrees of freedom. According to Hugging Face Principal Research Scientist Remi Cadene, it can walk and manipulate objects. As shown in a short X video, it has an accessible look that reminds us a bit of Bender from Futurama. (It’s the eyes.)
Co-designed with French robotics company The Robot Studio, HopeJR will be open source. “The important aspect is that these robots are open source, so anyone can assemble, rebuild, [and] understand how they work, and [they’re] affordable, so that robotics doesn’t get dominated by just a few big players with dangerous black-box systems,” Hugging Face CEO Clem Delangue told TechCrunch.
A week ago we saw Tesla’s Optimus robot showing off some nifty dance moves. This week, you can watch it performing a bunch of mundane tasks, though admittedly with a great deal of skill — for a humanoid robot.
Instructed via natural language prompts, the so-called “Tesla bot” is shown in a new video dumping trash in a bin, cleaning food off a table with a dustpan and brush, tearing off a sheet of paper towel, stirring a pot of food, and vacuuming the floor, among other tasks.
The performance may not shake the world of humanoid robotics to its core, but it nevertheless shows the kind of steady progress that Tesla engineers are making, with the bot’s actions and movements becoming evermore complex.
Commenting on the latest clip, Optimus team boss Milan Kovac said in a post on X: “One of our goals is to have Optimus learn straight from internet videos of humans doing tasks.” Just to be clear, that doesn’t mean the robot will literally watch videos like a human. Instead, it suggests that the robot will learn from the vast amount of data available in those videos, such as demonstrations of tasks, movements, or behaviors.
Kovac said that his team recently had a “significant breakthrough” that means it can now transfer “a big chunk of the learning directly from human videos to the bots (1st- person views for now),” explaining that this allows his team to bootstrap new tasks much more quickly compared to using teleoperated bot data alone.
Next, the plan is to make Optimus more reliable by getting it to practice tasks on its own — either in the real world or in simulations — using reinforcement learning, a method that improves actions through trial and error.
Tesla boss Elon Musk, who has spoken enthusiastically of Optimus ever since the company first announced it in 2021, has claimed that “thousands” of the robots may one day be deployed alongside human staff at Tesla factories, taking care of “dangerous, repetitive, [and] boring tasks.”
The company, better known for making electric cars than humanoid robots, is racing against a growing number of tech firms globally that are intent on commercializing their humanoid robots, whether for the workplace, home, or perhaps some entirely new human-robot ecosystems yet to be imagined.
Tesla has shared a new video showing its Optimus humanoid robot pulling some rather impressive dance moves.
While the nifty footwork might not be much use for the industrial settings that the robot is destined for, the 60-second clip effectively showcases its increasing agility and lifelike range of motion.
The clip comes a day after Optimus boss Milan Kovac said in an online post that his robotics team “has been working very hard in the background.”
Kovac added that for the dancing, Optimus, also known as the Tesla Bot, was trained entirely in simulation, with reinforcement learning. He also noted that the cable in the second clip was in place “in case of a fall” and was not actually holding the robot.
The third generation of the Tesla Bot was unveiled in March 2025. It features significant design and functional upgrades that include a 22-degree-of-freedom hand (up from 11 in previous versions), self-recharging capability, and advanced AI that allows the robot to learn tasks like a human rather than relying on traditional programming.
Tesla chief Elon Musk has previously said that “thousands” of the robots could one day work alongside human staff at Tesla factories in the next year or two, taking care of “dangerous, repetitive, [and] boring tasks.”
There are also plans for a commercial launch, with Musk claiming that Optimus could one day potter around the home as a household helper, or even “babysit your kid, walk your dog, mow your lawn, get the groceries, just be your friend, serve drinks.”
At $20,000 a pop, it won’t come cheap, though there’s also been talk of offering a more affordable rental service.
For decades we’ve been promised advanced, intelligent, and truly useful humanoid robots, and now the technology appears to be finally delivering. Tesla is now in a rapidly developing global race to build a practical humanoid robot, with major players such as Tesla, Figure AI, Apptronik, and Boston Dynamics competing alongside a string of impressive Chinese rivals.
Companies in the sector are keen to move toward mass production in a bid to address labor shortages and automate repetitive or dangerous tasks. While challenges like cost, safety, and real-world complexity remain, there’s a growing possibility that in the next few years, humanoid robots could enter the workplace — and even everyday life — at an unprecedented scale.
One of the most important branding decisions a company can make about its product is the name. It needs to be catchy and descriptive. But when trademarking, it also can’t be “generic,” according to the U.S. Patent and Trademark Office, which rebuffed Tesla’s (TSLA) application to trademark the term “robotaxi” for its…
You may have seen robots dancing like the music icon Mick Jagger, doing parkour, or even painting on a canvas. Tesla’s Optimus humanoid robot is eagerly anticipated, while Google and Meta are also planning to enter the field. The competition in the East, however, is on a different level altogether.
China just put humanoid robots to the test in the world’s first race of its kind, where they ran alongside humans in a half-marathon. A total of 21 robots lined up for the event in the Yizhuang half-marathon, following a long spell of supervised learning on roads.
The event saw a whole bunch of robotics companies showcase their ware. Some of the robots were as short as 3.9 feet, while others reach a typical human height of 5.9 feet. Some stumbled, a few tried to get back up on their own, while a small number needed human assistance.
During the race, the humanoid robots navigated around steep slopes, potholes, puddles, and smooth asphalt. Battery swaps were allowed, but replacement would incur a steep penalty. Not all robots made it to the finish line, however, despite intervention by robotics and software experts.
Not really, and the gap was huge, as well. The human victor finished the half-marathon in just over an hour, while the winning humanoid robot took 2 hours and 40 minutes to reach the finish line.
That comes down to an average speed of 4.89 miles per hour. For comparison, Olympic champion Usain Bolt reached a top speed of 27.33 miles per hour at a track event in 2011. Beating a human runner, however, was never the point, even though the winner outperformed the engineering team’s expectations by roughly half an hour.
The half-marathon in China was more like a showcase of progress made by local robotics companies. The winner among the humanoid robots, named Tiangong Ultra, is developed by the Beijing Innovation Center of Human Robotics.
“I don’t want to boast but I think no other robotics firms in the West have matched Tiangong’s sporting achievements,” Tang Jian, head of the company behind the winning robot, was quoted as saying by Reuters.
It’s a state-backed company in which Chinese electronics giant Xiaomi is also a key stakeholder. According to SCMP, the company aims to become “the Android in the field of humanoid robots.” For the half-marathon, some modification work was also done to get the best performance.
“We lightened the robot without compromising its strength, refined its leg design, and improved its thermal conductivity and air-cooling systems to boost stability and endurance,” Guo Yijie, a technician for the Tien Kung Ultra robot, told Xinhua.
Participating companies and the organizers behind the unique half marathon note that the ultimate goal is to showcase humanoid robots in human environments. They will soon graduate from design labs to industrial settings, but the ultimate goal is to put them into an average person’s home as a helpful assistant.
Several years ago, Harvard University roboticist Robert Wood made headlines when his lab constructed RoboBee, a tiny robot capable of partially untethered flight. Over the years, RoboBee has learned to fly, dive, and hover. The latest improvement: RoboBee has learned how to stick the landing, thanks to biomechanical improvements to its landing gear modeled on the crane fly, which has a similar wingspan and body size to the RoboBee platform. The details of this achievement appear in a new paper published in the journal Science Robotics.
As previously reported, the ultimate goal of the RoboBee initiative is to build a swarm of tiny interconnected robots capable of sustained untethered flight—a significant technological challenge, given the insect-sized scale, which changes the various forces at play. In 2019, Wood’s group announced its achievement of the lightest insect-scale robot so far to have achieved sustained, untethered flight—an improved version called the RoboBee X-Wing. In 2021, Wood’s group turned its attention to the biomechanics of the mantis shrimp’s knock-out punch and built a tiny robot to mimic that movement
But RoboBee was not forgotten, with the team focusing this time around on achieving more robust landings. “Previously, if we were to go in for a landing, we’d turn off the vehicle a little bit above the ground and just drop it, and pray that it will land upright and safely,” said co-author Christian Chan, one of Wood’s graduate students. The trick is to minimize velocity when approaching a surface and then quickly dissipating impact energy. Even something as small and light as RoboBee can generate significant impact energy. The crane fly has long, jointed appendages that enable them to dampen their landings, so the insect served as a useful model for RoboBee’s new landing gear.
Even the tiniest of living things are capable of some amazing forms of locomotion, and some come with highly sophisticated sensor suites and manage to source their energy from the environment. Attempts to approach this sort of flexibility with robotics have taken two forms. One involves making tiny robots modeled on animal behavior. The other involves converting a living creature into a robot. So far, either approach has involved giving up a lot. You’re either only implementing a few of life’s features in the robot or shutting off most of life’s features when taking over an insect.
But a team of researchers at Harvard has recognized that there are some behaviors that are so instinctual that it’s possible to induce animals to act as if they were robotic. Or mostly robotic, at least—the fruit flies the researchers used would occasionally go their own way, despite strong inducements to stay with the program.
The first bit of behavior involved Drosophila‘s response to moving visual stimuli. If placed in an area where the fly would see a visual pattern that rotates from left to right, the fly will turn to the right in an attempt to keep the pattern stable. This allowed a projector system to “steer” the flies as they walked across an enclosure (despite their names, fruit flies tend to spend a lot of their time walking). By rotating the pattern back and forth, the researchers could steer the flies between two locations in the enclosure with about 94 percent accuracy.
