Author: peterjang73

There are some who use their YouTube success to fund excessive lifestyles of debauchery, coveted cardboard, and opulent mansions. However, there are others who try to do something interesting. That’s undeniably the case for educational YouTube channel Wendover, which last year launched Jet Lag: The Game—a globe-spanning series of challenge-based board games, where the board is the planet, and the pieces are the players. As their sixth season draws to a close, we take a look at why this is something you’ll want to watch.

OK, so, everyone’s heard of The Amazing Race. It’s that long-running CBS show that isn’t Survivor, the one where teams of two “race around the world,” flying from country to country to complete challenges, attempting to be first to arrive on the mat and be greeted by the ever-grimacing Phil Keoghan. Except, if you’ve watched it, you’ll know that if there’s one thing it isn’t, it’s a real, ongoing race. The show is so astonishingly artificially rubber-banded, and the challenges so carefully produced, that the artifice often obscures the view. It’s tremendous fun, of course! But it’s very, very television.

Step in, Jet Lag: The Game. Created by the minds behind Wendover’s Half As Interesting channel—Wendover creator Sam Denby and writers Ben Doyle and Adam Chase—it began with the ambitious goal of playing Connect 4 across the United States of America, claiming states as counters. But perhaps more importantly than the geographic scale of this ambition, they also approached it as a board game design challenge, with all the intricate detail and balance this involves.

Since that initial game of Connect 4, they’ve circumnavigated the globe, played tag across Europe, and are just finishing airing an epic game of capture the flag over the whole of Japan. And with each season, they’ve further refined the many elements that make this show so compulsively watchable. Oh, and Ben getting drunk.

Connect 4 with the United States as the grid

Connect 4 Across America worked right away. The concept was reasonably simple. In a barely post-covid-restrictions America, Sam, Ben, Adam and guest Brian McManus from Real Engineering needed to fly to U.S. states (well, the 22 West of Mississippi) and complete challenges. By completing a challenge, the state became theirs, played like a counter on a Connect 4 board. The goal was to claim four in a row, or of course to block the opponent team’s attempts to do so. And the means was public or commercial transport of any type, including a lot of flying.

This immediate success was definitely helped by what had essentially been a pilot season, called Crime Spree. Not officially a Jet Lag season, this Nebula series had Sam attempting to break as many obscure laws across American states as he could, while pursued by Ben and Adam simply guessing where he might be and trying to fly there to find him. It was fun, but deeply janky, and due to illness, didn’t even properly conclude. But they clearly learned a lot.

With the game designed by its players, and so many lessons learned, Connect 4 was a whole other vibe. While filmed on phones by the players themselves, it immediately looked great, boosted by fantastic post-production efforts, from superb on-screen graphics to excellent editing. It felt like TV, but with the hands-on sensibilities of YouTube.

Each pair of players had a starting budget of $5,000, from which they needed to pay for their transport, food, and hotels. After that, the rules were that they had to inform the other team (by text) as soon as they had successfully claimed a state, and only then would the opponents know where the other team currently was.

The combination of the logistics (the subject that Wendover’s channels have always focused on) and the personalities makes it all immediately enjoyable. Ben and Adam immediately showed an incredible partnership energy, the two of them so outlandishly nerdy, while enormously witty, and in another life they’d clearly have become writers for late-night TV. Ben has the vibe of the lovely best friend in a romantic comedy, while Adam is destined to play a young Richard Kind in the biography of the actor’s life. Meanwhile, Sam and Brian were far more serious, and somewhat antagonistic. Sam is the person who completed a bungee jump for the first time, and responded to it by being glad about how efficient it had been. These two opposite approaches gave the show all the drama and fun it required, allowing viewers to side with the pairing that matched their own personality.

The challenges were fairly simple, but offered entertaining viewing. “Catch three different local bugs,” for instance. Or, “Bowl a strike.” Incredibly tame-seeming, compared to the complexity or silliness of challenges in the show’s more recent runs, but enough to delay them in their attempts to claim a state. Oh, and there was also—in the very first episode (above)—“Get one team member intoxicated.”

Getting drunk on YouTube is hardly an original idea, but the magic here was that Ben, the player who did the challenge, barely drank at the time. His tolerance was low, and his drunkenness was bizarrely endearing. It would become A Thing, a highlight of each following season.

Circumnavigation as a board game

By the second season, their ambitions grew enormously. Perhaps, it could be argued, a little too fast. Race to Circumnavigate the Globe in 100 Hours, while definitely worth a watch, is definitely the weakest of their adventures. As cumbersome as its own title (how was it not called “Around The World In 4.1666667 Days”?), the series failed to properly define its terms, explain its boundaries, and in the end proved to be much more of a straight travelogue than an exciting race.

Yet, it’s still a great watch, purely thanks to the personalities at play. Sam’s rigorous seriousness, and his clear nerdlove of transport, contrasts so splendidly with Adam and Ben’s comedy double-act. This time Sam was joined by RealLifeLore’s Joseph Pisenti, who usefully poked at Sam’s severity. But let’s skip ahead to the real meat…

Because then comes Tag Across Europe, and this is where the show really finds its stride. Simplifying things somewhat by not having a guest, the core three set out for a 72-hour game of tag, where each of them is trying to reach a different distant point around the continent. Whoever is “it” runs on their own, trying to make ground toward their finishing goal, while the other two pair up to chase them. And this time, the players are wearing trackers so the chasers can see exactly where they are.

Beginning in Charleville-Mézières, France, and because of “no tag-backs,” Ben begins as the first runner by charging toward the train station to get to Lille using his 45 minute head start. Ben has figured out that it’s the longest distance he can gain from the soonest train, that the others can’t immediately follow. We then cut back to Sam and Brian perfectly describing which train he’ll choose to catch and at what time, and how they’ll respond to this by heading straight to Brussels to cut him off later.

That’s the key here. They’re so damned smart. This has been shown off in previous seasons, but it really shines here. As much as the board games they’re playing may be of their own creation, they’re never not playing chess.

But as much as the dynamics between the personalities contribute to our viewing enjoyment, there’s another element that elevates Jet Lag: The Game, and it’s here that the series distinguishes itself so distinctly from that most obvious comparison, The Amazing Race. It’s game design.

In Tag Across Europe, there’s a lot of up-front design to see. Players are able to travel based on a complicated system of coins. It costs 25 coins to travel for 1 minute on high-speed rail, but only 10 coins for the same on low-speed rail. A minute on a bike or scooter will only cost a single coin, but the same time on a plane is 100. Coins are gained through completing challenges, which of course delay a runner, but can’t be avoided if they need to travel. And it can all be augmented with Powerups, expensive options that have big effects, like 1,500 coins to turn your tracker off for 10 minutes, or 250 coins to double the value (and veto penalty) of your next challenge.

All of these cards and counters provide the very board-game approach, and each is partly based on the lessons learned from previous seasons, but it’s a lot deeper than that, because the contestants have theory-tested every season multiple times before they even head out.

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Simulation ahead of stimulation

The three behind the show craft each game via meticulous simulation. Based on maps, guesses and instinct, they’ll play through their design over and over, working out timings, refining rules, and balancing, balancing, balancing. It’s here that the team implements their own rubber-banding, that essential part of good TV that prevents teams from running away with an insurmountable lead early in the game.

In The Amazing Race, this is achieved by the most brute-force means imaginable. Challenges teams have to complete will only open up at certain times of day, for instance, meaning a three-hour lead is entirely wiped out by having to wait for a Chinese temple to open at 8am, by which point every other team has rolled up too. Or there are fixed flights they’re allowed to book on, again buffering all the teams back to regimented slots.

However, in Jet Lag, everything is far more subtle, and ultimately, far more fair. While the players have certainly encountered situations where locations for challenges are closed by the time they reach them, they generally plan to prevent this from happening, and have back-up challenges available. As a last resort, they also have veto rules in place, meaning teams can opt out of a challenge for a time penalty, and of course a lack of coins or cash earned.

Instead, the rubber-banding is pre-built into the game design itself. Take, for example, what I’d argue is the best season so far, the horribly named We Turned New Zealand Into A Real-Life Board Game. Here, Ben and Adam raced against Sam and Tibees’ Toby Hendy, to travel from the northern tip of New Zealand down to its southernmost point. Using hired cars instead of public transport (causing some amount of controversy among its more, er, dedicated viewers), each pair could pick different pre-defined routes, based on their length and the nature of the gating challenges along their way.

There were shorter routes, but featuring more complicated or even luck-based challenges, or longer roads that had far more perfunctory goals to achieve. Through simulation, they had worked out many route options that would allow a team to catch up, but with higher risk, and incentives for teams in the lead to take slower roads for an easier life. Then, there were the many extra elements in place to further scupper a team, like the excellent Curses.

Curses were drawn at random from a Curse deck, at a high cost of tokens earned from challenges, with the gamble that some were a lot more effective than others. One team being forced to listen to Tom Lehrer’s “The Element Song” on loop for two hours might have been a form of torture, but it didn’t slow them down. Not being able to say words that use the letter “e” without incurring a five-minute time penalty, however, proved enormously problematic.

The current series—We Played A 96 Hour Game Of Capture The Flag Across Japan—sees Ben and Adam square up against Sam and Scotty Allen from Strange Parts, and as you might have gathered from the grimly YouTube title, they’re…well, you already know. It’s back to public transport, although this time entirely restricted to rail travel, in a game that takes place on an ever-expanding board of larger and larger sections of Japan. And while the addition of Toby Hendy gave the previous season a much-needed different temperament (and, it must be said, the first and only time a woman has been involved), it’s fair to say they’ve never got the game design as perfect as this.

What now appears to be a core element of the games remains in place: travel is paid for by an in-game currency, which is earned by completing challenges. But this is a whole different approach, with the two teams trying to get to specific vending machines in the country to get a specific item, and then return it to their own defined territory without being “tagged” (clearly filmed) by the opposing players. This time, there’s lots of splitting up, as well as the introduction of game pieces called Towers, that impose bizarre and infuriating restrictions over a certain radius around them. You can only walk sideways, for instance, or you have to be holding a slice of pizza. The latter sounds silly, until you realize it means getting off a train at the first opportunity to try to find some, while someone else is pursuing you to reset your flag.

Colonialist routes

I’ve done my best to be pretty vague in much of my description here, because everything’s a spoiler in a show like this. But if you’ve ever been of a mind that YouTube is just filled with yobbish rich kids or trashy low-quality bitching to camera, then Jet Lag is essential. It demonstrates the incredible power of what can be done by a bunch of 20-somethings, without a production company and network behind them. While its five-to-seven episode runs wouldn’t work for network TV, everything else about the show easily would. It just…doesn’t need to.

It’s also worth noting something else the show impressively avoids: cultural insensitivity. The Amazing Race is astoundingly garish in this regard, the way each country it visits is reduced to stereotypes through the challenges arranged and the locations in which they take place. Jet Lag mostly avoids this, by its challenges’ tendency toward the general, rather than specifics of any particular country. When designing challenges that could potentially be completed in any given nation, they’re far more likely to lean on the ubiquity of McDonald’s than patronizing some country’s national dress or local tradition, as The Amazing Race so often relies upon.

Even in its most “touristy” season, the New Zealand race, the spots they choose are as obscure as a clock museum or a refuse site nicknamed Mt. Cleese. Concerned by not wanting to annoy or patronize Maori culture, one stop required the players to simply “admire” the Tāne Mahuta tree for a set amount of time, their motivation always being not wanting to be “annoying YouTubers” at any point. Plus, it’s always a lot more entertaining to watch Adam and Ben failing to remember the words to “The Okaihau Express” while standing in a deserted railway tunnel than it is to watch white Americans trying to learn some local dance between commercials for washing powder.

The latest series in Japan, that draws to an end on YouTube next week (and already finished for Nebula subscribers), has spectacularly avoided all that grim fetishizing of Japanese culture that’s all too often the focal point of any travel show that visits the country. It’s just four guys trying to use a notoriously complex train network to play a game, while getting in no one else’s way or spoiling no one else’s day, on the planet on which they live.

Where they certainly do fall down is in their own diversity. It’s incredibly noticeable that five out of six seasons have featured four young white men, while the other managed to feature one young white woman. They’ve called themselves out on it, but—you know—that doesn’t do much. As much as they do a great job of avoiding behaving awkwardly in Japan, it remains awkward that the show features almost no one who’s Japanese.

It’s this latter aspect that is, perhaps, the game’s defining barrier. When they focus on areas like their home nation, Western Europe, or even New Zealand, they avoid the uncomfortable resonating tones of colonialism that would accompany their shining white faces if they tried to play across countries like India or Nigeria. Clearly this is a barrier that could be lifted by their having the nous to create teams with YouTubers who live in such countries, allowing somewhere like Pakistan, say, to be presented with the same back-alley nonchalance with which they approach the U.S. or France.

What Jet Lag: The Game unambiguously achieves, however, is demonstrating what a small planet we’re on, and how extraordinarily accessible so much of it is. It’s hard not to view this with a soothsayer’s eye, wondering what our grandchildren might think of a time when kids were leaping on airplanes to traverse the globe for pure entertainment. But given the 10x carbon offsetting for all their travel, and the fact they’re actually traveling internationally for just a handful of days a year (perhaps a total of 10 or 15) compared to the average businessperson, it’s disingenuous to condemn this as unacceptably egregious. You can strongly disagree, and absolutely not like it, certainly, but I see it as eminently defensible. (And heck, if we compare it to The Amazing Race’s footprint, it’s a mouse’s paw.)

Instead, I see Jet Lag as a celebration of our planet, combined with a love for board game systems, grabbing what is possibly the only moment in all of human history when such a combination is possible. It’s also some incredibly smart people being entertainingly intelligent on camera. Heck, even when Ben’s drunk, he can complete a math minute without making any mistakes.

 

 

Last week’s government inflation data showed used car prices were falling and likely stabilizing to levels just above pre-pandemic pricing. It seems prices for used electric vehicles, however, are falling even faster.

According to auto research firm iSeeCars.com, used EV prices are collapsing more than those in the overall used car market. In the firm’s June 2023 report, the data shows that used EV prices have fallen by nearly 30% year over year, with price drops actually accelerating from 8.8% in January to 16.8% in March and to 29.5% in June. The firm analyzed transactions from over 1.8 million one- to five-year-old used cars from the June 2022 and 2023 time period to capture the results.

“A year ago, used EV prices were on the upswing, rising faster than the average used car,” said iSeeCars executive analyst Karl Brauer in the report. “Electric vehicle prices are now falling at nearly 10 times the rate of the average used vehicle, reflecting a clear shift in EV supply and demand.”

Meanwhile, the overall used car market is stabilizing according to iSeeCars.com, with overall prices down 3.6% year over year in June, following price drops of 2.9% in May and 3.6 % in April.

Tesla price cuts

The biggest reason behind the fall in used EV prices? Tesla’s (TSLA) massive price cuts earlier this year put extreme downward pressure on the used EV market, which is dominated by Tesla EVs like the Model 3 and Model Y.

“With Tesla cutting prices on new models its used EV values have tumbled. And because Tesla makes up the bulk of the used EV market the dramatic drop in Tesla values has impacted the entire category,” Brauer said.

Other factors pushing prices lower on the second-hand EV market include fuel prices stabilizing this year (hurting demand for EVs), rising interest rates, and price-conscious shoppers looking for better vehicle deals regardless of powertrain, Brauer said.

Looking deeper into the data, the top 10 models with the steepest price drops included six hybrid and electric vehicles, with Tesla occupying three of the top five slots with the Model 3 (30.5% drop), Model X (21.3% drop), and Model S (19.0% drop).

Conversely, used cars with the biggest overall price increases were traditional gas-powered cars led by the Mercedes-Benz SL convertibles, Fiat 500X crossover, Chevrolet Suburban, and two Porsche sportscars — the 911 convertible and 718 Cayman coupe.

Looking across metropolitan markets in the US, the data showed that the Miami market saw the steepest used car price drops at 8.1% year over year in June, followed by New York (6.9%) and Jacksonville, Florida, at 6.8%. Only Dallas, Salt Lake City, and San Antonio saw used car price appreciation across the 50 metro areas covered by iSeeCars.

The bottom line for used EV car buyers could be this: If you want a cheap Tesla EV, now might be your best chance to buy one. And don’t shy away from going across state borders to Florida or New York to buy one.

Pras Subramanian is a reporter for Yahoo Finance. You can follow him on Twitter and on Instagram.

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Developing new antibiotics presents a complicated challenge, but scientists are now using artificial intelligence to design new drugs to address the problem. In May researchers at the Massachusetts Institute of Technology and McMaster University published a study on their use of an AI algorithm to identify an antibiotic that can kill a particularly resistant type of bacterium. The pathogen, called Acinetobacter baumannii, can lead to serious infections, including meningitis and pneumonia, and is often found in hospital settings. It’s also a leading cause of infections in military personnel in the Middle East.

The findings are significant because they show how AI can be used to hasten the development of new antibiotics to fight drug-resistant bacteria. Using AI and machine learning—the subset of AI that involves using algorithms to find patterns in data—dramatically reduces the number of experiments that humans would need to screen a potential drug for efficacy. It also greatly reduces the cost because the computer modeling weeds out compounds that aren’t promising.

Antibiotic resistance, the phenomenon in which bacteria become resistant to the drugs used to treat them, is a growing threat that could cause up to 10 million deaths annually by 2050. The World Health Organization (WHO) estimates that in 2019 alone 1.27 million people died globally from drug-resistant bacterial infections.

“We need new antibiotics because we’re facing a crisis due to the fact that the number of resistant bacterial pathogens is growing while our pipeline of new antibiotics is diminishing,” says James Collins, a professor at M.I.T.’s Institute for Medical Engineering & Science and co-senior author of the new study. “The former is arising due to numerous factors—largely the overuse and misuse of antibiotics, both in health care and in agriculture. And the latter is largely caused by a broken economic market for antibiotics.”

Antibiotic development presents something of a catch-22. The cost of developing a new antibiotic is enormous; it’s on par with the cost of developing a new cancer drug. But unlike cancer drugs, which can be taken for months or even years, antibiotics are usually taken for a relatively short period of time and often just for a single infection. Because of stewardship programs designed to decrease antibiotic resistance, any new antibiotic is likely to be reserved by health care workers until it’s really needed. And long drug approval periods and the widespread availability of generic drugs mean that there is little financial incentive for drug companies to develop new antibiotics.

“There is a real market failure in the antibiotic space, in the antimicrobial space—and I’d include some antifungal medicines in that bucket as well,” says Jocelyn Ulrich, deputy vice president for policy and research at the industry group Pharmaceutical Research and Manufacturers of America (PhRMA). She points out that antibiotic resistance is a naturally occurring phenomenon and that the only ways to control it are to use tools, such as those for infection prevention and control, to slow down the use of new products.

“We have seen the number of companies, especially the larger companies, decline from 20 or so down to just a handful who are still even in the space,” Ulrich says. “And as a result, we have a much smaller pipeline of novel therapeutics coming through.”

Scientists are hoping to change that. In the recent study, Collins and his fellow researchers exposed A. baumannii to thousands of potential drug compounds to see which of them blocked the pathogen’s growth. They used those data to train a computer model to predict a compound’s antibacterial activity based on its structure.

The team used the model to analyze 6,680 compounds in just a few hours—a process that would have taken a few weeks without AI. The analysis narrowed the batch down to a few hundred possibilities—240 of which Collins and his colleagues tested in the lab. Among these, the researchers identified nine antibiotics, including one that was effective at killing A. baumannii. Importantly, the compound is “narrow spectrum,” meaning it doesn’t kill other species of bacteria. This is beneficial because it reduces the chance of other bacteria spreading resistance against the drug and does not compromise the gut’s overall microbiome.

Collins explains that the new drug, named abaucin, works by disrupting the bacterium’s protective outer layer, the cell membrane. In tests on mice, it was effective against wound infections caused by A. baumannii. Abaucin also worked against a number of drug-resistant strains of A. baumannii that had been isolated from human samples and subsequently grown in the lab.

Collins’s team used the computer model to test thousands of compounds. “Now imagine you want to go from [testing] thousands to many billions of molecules,” he says. “It would be effectively impossible [for humans] to curate, purchase and test all of those molecules. And yet for billions of compounds, it still only takes several days to analyze with AI. So we are able to explore much, much larger chemical spaces that really would not be available to us without these computer models.”

“I think these tools have the potential to speed many aspects of the drug development process, but it’s early days,” Ulrich says. “Whenever we have really large data sets and can very efficiently analyze that data, that’s certainly time-saving.” But she notes that the findings are only in animal models. “You still have to do all the work to develop that compound into something that can be metabolized in the human body, and they need to do thorough clinical trials and other things,” she says. “I’d say there’s immense potential and immense excitement around some of these tools.”

Aleksandra Mojsilovi? is an IBM fellow and head of AI Foundations at IBM Research. She has been instrumental in research showing how AI can be used to develop new therapeutics and has co-authored a paper showing how IBM’s AI system could help accelerate the processes of finding new antibiotics.

Mojsilovi? agrees that AI can accelerate research by reducing the time it takes to search thousands or millions of compounds. “But it can go way beyond that,” she says. “You can train the models to actually predict properties of existing molecules quickly, which allows you to screen or predict how good the molecule is, or identify the unknown properties, such as toxicity.” Additionally, with generative AI, computer models can be trained on the existing molecules to learn their “representation,” or characteristics, Mojsilovi? says. Researchers can then design molecules that have never been seen before in nature.

In response to the market challenges in developing new antimicrobial drugs, in 2021 U.S. senators Michael F. Bennet of Colorado and Todd Young of Indiana introduced the  PASTEUR Act in Congress. The bipartisan bill would create an incentive program and government investment of $6 billion for the development of new antivirals and antibiotics—and give the government unlimited access to the drugs once they’re approved by the Food and Drug Administration. The bill was just reintroduced in April 2023, after more than 200 organizations, including PhRMA, signed a letter in support of the act in March.

If the bill passes, researchers will still be in a race against time to develop new antibiotics against the most dangerous drug-resistant pathogens—and that’s where AI could be critical. The FDA recently released a paper to facilitate discussion among developers, manufacturers, regulators, academic groups and other stakeholders on the use of AI and machine learning throughout the drug-development process.

AI has been getting a lot of negative attention lately for the ways it could be misused, but it could also be a very powerful tool in helping us solve some of our most pressing challenges.

“I’m very hopeful,” Collins says. “I think our AI tools, our technology platforms to discover, design and develop new antibiotics, are expanding with each year.”

How do you design a robot that can explore a wide variety of terrain it might encounter on alien planets?

A team from Caltech and NASA’s Jet Propulsion Laboratory (JPL) has designed a robot that goes way beyond your typical rover and may be the next step in planetary exploration. The four-wheeled Multi-Modal Mobility Morphobot (M4) is designed to autonomously asses its surrounding terrain to determine how to best traverse upcoming obstacles. 

The M4’s unique capabilities combine solutions from hurdles experienced in previous robotic missions on Mars and could provide the innovation needed to anticipate future ones. Rough terrain ahead? No problem. The M4’s four wheels are designed to pivot onto their sides and work as propellers, turning the Morphobot into a quadcopter drone. Obstacle in your way? M4 can stand up using its back two wheels like legs, balancing itself with the rotary thrust of its front propellers as it pivot-walks to a clear path. And using artificial intelligence (AI), M4 is designed to make these determinations autonomously. 

Related: Curiosity rover on Mars gets a brain boost to think (and move) faster

Robotic planetary exploration vehicles, like the wheeled rovers on Mars, are limited to the landscapes they are able to navigate. NASA’s Curiosity rover, for example, has been exploring the Martian surface for eleven years. In that time, the robotic explorer has driven less than twenty miles (32 kilometers) and experienced damage to its wheels within the first several months of its mission. 

NASA’s more recent Mars rover, Perseverance, was sent with a small helicopter companion called Ingenuity. The success of Ingenuity’s flights on the Red Planet prompted NASA to keep the drone-like vehicle operational long past its planned mission in order to help scout routes for Perseverance, providing mission operators valuable insight into the rover’s road ahead. 

M4 could handle all of these tasks on its own thanks to a revolutionary set of capabilities.

“Our aim was to push the boundaries of robot locomotion by designing a system that showcases extraordinary mobility capabilities with a wide range of distinct locomotion modes. The M4 project successfully achieved these objectives,” assistant professor of electrical and computer engineering at Northeastern University Alireza Ramezani said in a Caltech statement. 

Ramezani and Caltech director of Bioinspired Engineering and aeronautics professor Mory Gharib came up the idea for M4, which they developed together with a group at Caltech’s Center for Autonomous Systems and Technologies (CAST). Their team consisted of Caltech’s Eric Sihite, an aerospace postdoctoral scholar research associate, CAST design engineer Reza Nemovi and Arash Kalantari, from JPL. 

The group published a paper last month in the journal Nature Communications announcing the robot. The paper cites the locomotive techniques of different animals as the inspiration behind some of M4’s design, such as the Chukar bird, which flap its wings for balance while walking over hilly landscapes. 

“Chukar birds adopt a similar wing repurposing to increase redundancy to support legged locomotion over steep terrain through a phenomenon known as wing-assisted incline running (WAIR),” the paper states. It also draws comparisons to sea lions’ differing appendage usage depending on whether they animal is swimming or walking on land. 

The M4 team at CAST also see uses for the Morphobot’s technology here on Earth, particularly in the field of emergency services. One example in the paper describes the aftermath of a natural disaster, in which M4 is able to fly inside a collapsed building, then drive and “walk” around confining obstacles until it locates survivors and alerts first responders. 

Join our Space Forums to keep talking space on the latest missions, night sky and more! And if you have a news tip, correction or comment, let us know at: community@space.com.

NASA’s supersonic plane has moved closer to the runway in preparation for its debut flight. 

New photos show the X-59 supersonic plane parked on the flight line — the space between the hangar and the runway —  at Lockheed Martin’s Skunk Works facility in Palmdale, California. The plane was moved from its construction site to the flight line on June 19, according to a statement from NASA. 

This milestone kicks off a series of ground tests to ensure the X-59 is safe and ready to fly as part of NASA’s Quesst mission, which aims to demonstrate that the aircraft can fly faster than the speed of sound (or Mach 1) without generating the loud sonic booms generally produced by supersonic planes. 

Related: Watch NASA’s supersonic X-59 jet come together in Lockheed Martin’s new video

“NASA will then fly the X-59 over several communities to gather data on human responses to the sound generated during supersonic flight,” officials said in the statement from the space agency. “NASA will deliver that data set to U.S. and international regulators to possibly enable commercial supersonic flight over land.” 

The X-59 supersonic jet is expected to produce only a gentle thump, or the equivalent of a nearby car door slamming, for people on the ground. In comparison, previous generations of supersonic aircraft are known to rattle windows when flying over the speed of sound. 

Therefore, the X-59 could lead to new sound-based rules regarding supersonic flight over land, opening new doors for faster commercial cargo and passenger air travel. 

The plane will remain parked near the runway during its ground and initial flight tests by Lockheed Martin. The 99.7-foot-long, 29.5-foot-wide aircraft is powered by a single jet engine, which was built by General Electric Aviation, a subsidiary of General Electric. It is designed to reach a speed of Mach 1.4, or 925 mph, flying at an altitude of 55,000 feet (16,764 meters).

If all goes according to plan, the X-59 will fly over select U.S. cities starting in 2024. Residents will be able to share their responses to the sound produced by the X-59 aircraft. Then, data collected from the flights will be shared with American and international regulators in 2027, when the Quesst mission comes to a close. 

Join our Space Forums to keep talking space on the latest missions, night sky and more! And if you have a news tip, correction or comment, let us know at: community@space.com.

Chinese commercial launch firm Landspace is preparing for the second test flight of its Zhuque-2 rocket, setting the stage for a groundbreaking achievement, should the methane-fueled rocket successfully reach orbit.

Zhuque-2, meaning “Vermillion Bird-2,” is scheduled to launch on July 12, 2023, at 2:00 a.m. ET from the Jiuquan Satellite Launch Center in the Gobi Desert, according to NextSpaceflight. The rocket’s success could usher in a new era of methalox-powered rocket engines for orbital and interplanetary transportation. The global spaceflight community will undoubtedly be keeping a close eye on this upcoming launch as Landspace seeks to demonstrate the viability of methalox rocket fuel. As of yet, no information has been disclosed about the rocket’s payloads.

Methalox is fast becoming the preferred rocket fuel for launch providers. The benefits of methalox (a methane-oxygen mixture) are deemed to be more attractive than conventional liquid fuels like kerosene due to its cleaner, safer properties, and is deemed particularly suitable for reusable rockets. And conceivably, it could be manufactured off planet, including on Mars. Several prominent space companies are developing rockets that will use the fuel, including SpaceX’s Starship, Rocket Lab’s Neutron, Blue Origin’s New Glenn, and Relativity Space’s Terran R.

The first launch of the 162-foot-tall (49.5 meters) rocket didn’t go so well. Zhuque-2 failed to reach orbit during its maiden flight on December 14, 2022, resulting in the destruction of all 14 satellites on board. Investigations traced the issue to a faulty second-stage liquid oxygen inlet pipe, as reported by SpaceNews. A successful mission this time would see Landspace becoming the second private Chinese company to conduct a successful launch with a liquid propellant rocket, after Space Pioneer achieved the feat in April with its Tianlong-2 rocket.

Equipped with gas generator engines, the Zhuque-2 is capable of producing 243 metric tons of thrust, and it boasts a payload capacity of 6 metric tons to low Earth orbit—or a reduced payload capacity of 4 metric tons to a Sun-synchronous orbit, the company claims.

The evolution of the Zhuque-2 represents a significant shift in Landspace’s strategy, which earlier focused on solid propellants like the one used in the three-stage Zhuque-1 rocket, which failed to reach orbit during its first and only launch. Landspace and the Zhuque-2 are products of the Chinese government’s commitment to opening up the space sector to private industry, a process that began nearly 10 years ago.

Two other methalox-driven rockets failed to reach orbit during their maiden flights, namely SpaceX’s Starship and Relativity Space’s 3D-printed Terran-1, the latter being retired and replaced with Terran-R. A private launch provider, one would think, will eventually hoist a methane-fueled rocket to orbit. This coming Wednesday, it could very well be Landspace.

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