Author: peterjang73

The Chinese company Landspace just notched a big milestone in its quest to develop a reusable rocket. 

The Beijing-based startup launched and landed a test version of its Zhuque-3 rocket at the Jiuquan Satellite Launch Center in Inner Mongolia on Jan. 19.

The vehicle soared about 1,150 feet (350 meters) into the sky during the roughly 60-second flight, then came back down for a pinpoint landing within 7.9 feet (2.4 meters) of its target, according to Landspace, which declared the test mission "a complete success."

Related: Chinese startup Landspace poised to begin reusable rocket landing tests

Zhuque-3 is a two-stage, stainless-steel rocket whose first stage will be reusable, like that of SpaceX’s workhorse Falcon 9. 

The Zhuque-3, which Landspace hopes to start flying in 2025, will stand about 250 feet (75 meters) tall and be capable of carrying up to 40,350 pounds (18,300 kilograms) to low Earth orbit (LEO) in reusable mode, according to SpaceNews.

The Falcon 9, for comparison, can haul about 50,265 pounds (22,800 kg) to LEO, according to its specifications page.

Landspace — which also flies the expendable, and currently operational, Zhuque-2 rocket — isn’t the only Chinese outfit working to develop a reusable launch vehicle, as SpaceNews notes.

Others include the companies iSpace, Galactic Energy and Orienspace, as well as the state-owned China Aerospace Science and Technology Corp., whose many projects include a fully reusable version of its future Long March 9 heavy lifter.

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BMW has signed a first-of-its-kind deal to put “humanoid” robots to work at one of its factories. The robots, which are designed to be more operationally flexible than traditional industrial robots, will supposedly assist the luxury car manufacturer with various parts of the manufacturing process.

The robots in question were designed by California robotics firm FigureAI and are described as being “general purpose”—meaning they can be used for any number of physical tasks. The bipedal bot, which is simply dubbed the “Figure 01,” stands 5’6" tall, weighs 130 pounds, and has five-fingered hands that the company claims can be used to physically construct objects. On its YouTube channel, Figure has a video of the robot making coffee. Another video shows the bot swiftly walking across a room using its two sturdy legs.

That said, it’s not entirely clear what the bots will actually be doing in this case. The related press release speaks of the “deployment of humanoid robots in an automotive manufacturing environment” and claims the robots will focus on “difficult, unsafe, or tedious tasks,” all of which sounds pretty vague.

The press release further states that, as part of the first phase of the deal, the two companies will work together to “identify initial use cases to apply the Figure robots in automotive production.” Again, the wording here sorta makes it sound like both companies are a bit unclear on what the robots will actually be doing. After the two firms finally agree on what the Figure 01 can do, some of the bots will be deployed to one of BMW’s manufacturing facilities in Spartanburg, South Carolina.

“Single-purpose robotics have saturated the commercial market for decades, but the potential of general-purpose robotics is completely untapped,” said Figure’s CEO Brett Adcock. “Figure’s robots will enable companies to increase productivity, reduce costs, and create a safer and more consistent environment.”

Figure has been steadily unveiling photos and videos of its new worker:

Tech companies throughout the world are currently in a race to churn out the first generation of “humanoid” robots. While robots have helped out in factories and warehouses for years, the human form factor of this newer iteration of robots is thought to have many added benefits for more complicated forms of industrial work. This has, of course, spurred concerns that the robots will (eventually) take a lot of human jobs. Figure’s CEO has claimed that his company has no interest in taking jobs away from people—which is, of course, what he would say.

Gizmodo reached out to Figure for more details about the deal and will update this story if it responds.

Taking a cue from a recent recommendation by the National Transportation Safety Board, a legislative proposal in California would require that new vehicles be equipped with “intelligent” speed restrictive technology to limit speed in specific locations.

If it were to pass, the bill, put forward by San Francisco state Sen. Scott Wiener, would require cars and trucks of the 2027 model year or later that are built or sold in California to include speed governors that would prohibit motorists from driving more than 10 mph over posted speed limits.

The speed “governor” technology relies on GPS data or car cameras to cap vehicle speeds based on where the car is driving. For instance, vehicles wouldn’t be able to drive faster than 80 mph on state highways with a posted 70 mph speed. In residential neighborhoods, for example, motorists would have to keep their speed below 35 mph on streets with 25 mph limits.

Several auto manufacturers, such as Hyundai, already offer speed governor features in their newest models, which some motorists utilize as a form of cruise control, according to the San Francisco Chronicle.

“We have speed limits, and they exist for a reason. And it’s perfectly reasonable to say you can’t travel more than 10 miles over the speed limit,” Wiener said. “That’s what this bill will do. It’s very reasonable, and it’s an idea whose time has come.” The bill exempts emergency vehicles, such as ambulances and fire trucks, and the California Highway Patrol would have the discretion to disable speed governors on their vehicles.

One factor motivating the passage of the bill are reports that speed factors into about a third of traffic deaths across the country, according to the National Safety Council. The National Highway Safety Administration estimated more than 40,000 traffic fatalities in 2022.

Last November, the National Transportation Safety Board, prompted by a multi-vehicle crash in North Las Vegas that resulted in nine fatalities, recommended that the federal government “at a minimum” require speed limiters in cars that warn drivers when they’re speeding.

Meta shook up the race to build more powerful artificial intelligence last July by releasing Llama 2, an AI model similar to the one behind ChatGPT, for anyone to download and use. In November, a little-known startup from Beijing, 01.AI, released its own open source model that outperforms Llama 2 and scores near the top of many leaderboards used to compare the power of AI models.

Within a few days of its release 01.AI’s model, Yi-34B, rocketed to the top spot on a ranking maintained by startup Hugging Face, which compares the abilities of AI language models across various standard benchmarks for automated intelligence. A few months on, modified versions of 01.AI’s model consistently score among the top models available to developers and companies on the Hugging Face list and other leaderboards. On Monday, the startup launched a “multimodal” AI model called Yi-VL-34B that can process images and discuss their contents.

OpenAI, Google, and most other AI companies tightly control their technology, but 01.AI is giving away its AI models in hopes of inspiring a loyal developer base that helps it hatch some killer AI apps. 01.AI, founded in June of last year, has raised $200 million in investment from Chinese ecommerce giant Alibaba and others and is valued at over $1 billion, according to Pitchbook.

The startup’s founder and CEO is Kai-Fu Lee, a prominent investor who did pioneering artificial intelligence research before founding Microsoft’s Beijing lab and then leading Google’s Chinese business until 2009, a year before the company largely pulled out of the country. He says the creation of Yi-34B is the culmination of his life’s work trying to build more intelligent machines.

“This has been the vision of my whole career,” Lee says over Zoom from a handsomely decorated apartment in Beijing. “It’s been too long that we’ve had to learn computers’ language—we really need systems that can understand our language, which is speech and text.” In Chinese 01.AI is known as ????, Ling-Yi Wan-Wu in Chinese, which means “zero-one, everything” and alludes to a passage from the Taoist text Tao Te Ching.

01.AI is one of China’s leading contenders in the AI race that was started by OpenAI and ChatGPT and has so far been dominated by US companies. Lee says his company aims to lead the next phase of this revolution by building some of the first “killer apps” built on the capabilities of language models, which earn 01.AI healthy revenues. “The apps that won the mobile era are ones that are mobile-first, like Uber, WeChat, Instagram, TikTok,” Lee says. “The next-gen productivity tools shouldn’t look like Office anymore—Word, Excel, PowerPoint—that’s the wrong way to go.”

01.AI’s engineers are experimenting with different “AI-first” apps, Lee says, for office productivity, creativity, and social media. He says the plan is for them to become successful around the globe, in a similar way to how Chinese-backed social network TikTok and online retailer Temu are top apps with US consumers.

In 2017, detectives at the East Bay Regional Park District Police Department working a cold case got an idea, one that might help them finally get a lead on the murder of Maria Jane Weidhofer. Officers had found Weidhofer, dead and sexually assaulted, at Berkeley, California’s Tilden Regional Park in 1990. Nearly 30 years later, the department sent genetic information collected at the crime scene to Parabon NanoLabs—a company that says it can turn DNA into a face.

Parabon NanoLabs ran the suspect’s DNA through its proprietary machine learning model. Soon, it provided the police department with something the detectives had never seen before: the face of a potential suspect, generated using only crime scene evidence.

The image Parabon NanoLabs produced, called a Snapshot Phenotype Report, wasn’t a photograph. It was a 3D rendering that bridges the uncanny valley between reality and science fiction; a representation of how the company’s algorithm predicted a person could look given genetic attributes found in the DNA sample.

The face of the murderer, the company predicted, was male. He had fair skin, brown eyes and hair, no freckles, and bushy eyebrows. A forensic artist employed by the company photoshopped a nondescript, close-cropped haircut onto the man and gave him a mustache—an artistic addition informed by a witness description and not the DNA sample.

In a controversial 2017 decision, the department published the predicted face in an attempt to solicit tips from the public. Then, in 2020, one of the detectives did something civil liberties experts say is even more problematic—and a violation of Parabon NanoLabs’ terms of service: He asked to have the rendering run through facial recognition software.

“Using DNA found at the crime scene, Parabon Labs reconstructed a possible suspect’s facial features,” the detective explained in a request for “analytical support” sent to the Northern California Regional Intelligence Center, a so-called fusion center that facilitates collaboration among federal, state, and local police departments. “I have a photo of the possible suspect and would like to use facial recognition technology to identify a suspect/lead.”

The detective’s request to run a DNA-generated estimation of a suspect’s face through facial recognition tech has not previously been reported. Found in a trove of hacked police records published by the transparency collective Distributed Denial of Secrets, it appears to be the first known instance of a police department attempting to use facial recognition on a face algorithmically generated from crime-scene DNA.

It likely won’t be the last.

For facial recognition experts and privacy advocates, the East Bay detective’s request, while dystopian, was also entirely predictable. It emphasizes the ways that, without oversight, law enforcement is able to mix and match technologies in unintended ways, using untested algorithms to single out suspects based on unknowable criteria.

“It’s really just junk science to consider something like this,” Jennifer Lynch, general counsel at civil liberties nonprofit the Electronic Frontier Foundation, tells WIRED. Running facial recognition with unreliable inputs, like an algorithmically generated face, is more likely to misidentify a suspect than provide law enforcement with a useful lead, she argues. “There’s no real evidence that Parabon can accurately produce a face in the first place,” Lynch says. “It’s very dangerous, because it puts people at risk of being a suspect for a crime they didn’t commit.”