MEXICO CITY — Mexico’s state-owned oil company said Friday it suffered a rupture in an undersea gas pipeline in the Gulf of Mexico, sending flames boiling to the surface in the Gulf waters.
Petroleos Mexicanos said it had dispatched fire control boats to pump more water over the flames.
Pemex, as the company is known, said nobody was injured in the incident in the offshore Ku-Maloob-Zaap field.
The leak near dawn Friday occurred about 150 yards (meters) from a drilling platform. The company said it had brought the gas leak under control about five hours later.
But the accident gave rise to the strange sight of roiling balls of flame boiling up from below the surface of the Gulf of Mexico.
It was unclear how much environmental damage the gas leak and oceanic fireball had caused.
Miyoko Sakashita, oceans program director for the Center for Biological Diversity, wrote that “the frightening footage of the Gulf of Mexico is showing the world that offshore drilling is dirty and dangerous.”
Sakashita added, “These horrific accidents will continue to harm the Gulf if we don’t end offshore drilling once and for all.”
Four years ago, organizers created the international AI City Challenge to spur the development of artificial intelligence for real-world scenarios like counting cars traveling through intersections or spotting accidents on freeways.
In the first years, teams representing American companies or universities took top spots in the competition. Last year, Chinese companies won three out of four competitions.
Last week, Chinese tech giants Alibaba and Baidu swept the AI City Challenge, beating competitors from nearly 40 nations. Chinese companies or universities took first and second place in all five categories. TikTok creator ByteDance took second place in a competition to identify car accidents or stalled vehicles from freeway videofeeds.
The results reflect years of investment by the Chinese government in smart cities. Hundreds of Chinese cities have pilot programs, and by some estimates, China has half of the world’s smart cities. The spread of edge computing, cameras, and sensors using 5G wireless connections is expected to accelerate use of smart-city and surveillance technology.
The tech displayed in these competitions can be useful to city planners, but it also can facilitate invasive surveillance. Counting the number of cars on the road helps civic engineers understand the resources required to support roads and bridges, but tracking a vehicle across multiple live camera feeds is a powerful form of surveillance. One of the competitions in the AI City Challenge asked participants to identify cars in videofeeds; for the first time this year, the descriptions were in ordinary language, such as “a blue Jeep goes straight down a winding road behind a red pickup truck.”
The competition comes at a time of increased tech nationalism and tension between the US and China, and growing concern over the powers of AI. The Carnegie Endowment for International Peace in 2019 called China “a major driver of AI surveillance worldwide.” The group said China and the US were the two leading exporters of the technology. Last month, the Biden administration expanded a blacklist started by the Trump administration to nearly 60 Chinese companies barred from receiving investment from US financiers. Also in recent weeks, the US Senate passed the Competition and Innovation Act, providing billions in investment for chips, AI, and supply chain reliability. It also calls for investment in smart cities, including expanding a smart-city partnership with southeast Asian nations (excluding China).
China’s domination of the smart-city challenge may come with an asterisk. John Garofolo, a US government official involved in the competition, says he noticed fewer US teams this year. Organizers say they don’t track participants by country.
Stan Caldwell is executive director of Mobility21, a project at Carnegie Mellon University assisting smart-city development in Pittsburgh. Caldwell laments that China invests twice as much as the US in research and development as a share of GDP, which he calls key to staying competitive in areas of emerging technology.
He says AI researchers in the US can also compete for government grants like the National Science Foundation’s Civic Innovation Challenge or the Department of Transportation’s Smart City Challenge. A report released last month found that a $50 million DOT grant to the city of Columbus, Ohio, never quite delivered on the promise of building the smart city of the future.
“We want the technologies to develop, because we want to improve safety and efficiency and sustainability. But selfishly, we also want this technology to develop here and improve our economy,” Caldwell says.
Spokespeople for Alibaba and Baidu declined to comment, but advances from smart-city challenges can help fuel commercial offerings for both companies. Alibaba’s City Brain tracks more than 1,000 traffic lights in the company’s hometown of Hangzhou, a city of 10 million people. A pilot program found that City Brain reduced congestion and helped clear the way for emergency responders.
For the current study, the researchers injected the solution into maize leaves, which they chose, in part, because the crop is critical to worldwide food supply. The nanosensors coated the outside of the leaf’s cells, swelling or shrinking based on how much water was available.
The dye molecules in AquaDust fluoresce at different wavelengths, depending on their proximity to each other, and these wavelengths can be measured with an instrument called a spectrometer. When water is readily available, the nanoparticles swell, pushing the dyes apart and creating a peak in the green wavelength the dyes emit. When there’s not much water, the nanoparticles shrink, and the dyes move closer together, resulting in a peak in the yellow wavelength. Then the researchers can convert the emission spectrum readings into water potential measurements, all without harming the plant.
The technique can be applied to different locations along the leaf to track water flow, says Piyush Jain, a study coauthor and mechanical engineering PhD candidate at Cornell. “What that allows us to do is basically model the water flow through different tissues, starting from the stem to different parts of the leaf,” he says.
The researchers focused their AquaDust measurements on the area just beneath the leaf’s surface, where plants carry out important functions like taking in CO2, releasing water vapor into the atmosphere, and packaging sugars created by photosynthesis. To breed crops that manage water better, having a better grasp of the biology and behavior of water at such critical points will be very helpful, the researchers say.
Ultimately, the technology might be used in real-world situations, like for workers in fields or greenhouses. It might even be possible to someday spray AquaDust over a field and then use a multispectral camera to quickly measure water potential across hundreds of plants.
A researcher using AquaDust in a corn field.Photograph: Siyu Zhu/Cornell University
And while that’s still a far-off development, AquaDust sounds like useful technology, says Irwin Goldman, professor of horticulture at the University of Wisconsin, Madison, who wasn’t involved in the study. “Using any sort of remote sensing technology—in this case they’re using nanosensors—is an enormous leap forward,” he says. “My sense of this technology is that it is the future, really.”
Breeders have focused on developing drought-resistant crops for some time, says Goldman. “For at least the last 15 years, there’s been a sense in the plant-breeding community that we need to be incorporating selection for greater resilience in our crops as part of our breeding programs, that it’s not enough to just breed higher-yielding or better quality, or for disease resistance,” he says. But, he points out, it will be a long process to identify which plants best defy water loss and which genes are linked to that resiliency, before then pairing them with other desirable traits like good nutrition and flavor. “Once we identify the genes, that’s very helpful, but it doesn’t necessarily get us all the way to the end of the project,” he says. “We still have to find useful combinations.”
For now, AquaDust is primarily a research tool, not something that’s ready to be rolled out at scale that farmers or breeders could use to, say, assess 1,000 plants in an hour. For one thing, the injected solution itself contains water, which must evaporate before anyone can take a measurement. “We wait for about a day to get the leaf to come back into its natural state,” says Jain.
AquaDust’s application and readout methods would need to be refined before it could be ready for such high-throughput measurements or commercial products. But in the meantime, being able to precisely target the flow of water within plants might help researchers solve some mysteries. One of them, says Stroock, is whether plants ever allow the innermost layers of their leaves, called mesophyll, to dry out. For years, the conventional wisdom was that they avoid it, but indirect measurements by other labs now suggest that it’s a possibility. Being able to test this directly with AquaDust could fundamentally alter our understanding of how plants manage their water and how they handle the stress caused by dry inner tissue, he says.
“We believe there are very exciting questions to answer in the lab that take precedence over commercialization,” Stroock says. “Right now, Iowa farmers are not calling us to say, ‘Can we cover our field with AquaDust?’”
Those farmers are probably just hoping for rain. But, someday, technology like nanosensors might help them out when those hopes run dry.
Apple and Intel are reportedly testing chip designs with TSMC’s 3-nanometer process and could be first to market with the technology, according to Nikkei. Intel may be planning to use the chips in next-gen notebooks and data centers, while Apple could be first to market with a 3-nanometer processor in future iPad models. Taiwan-based TSMC will reportedly start manufacturing processors for both companies as early as next year.
TSMC is currently manufacturing 5-nanometer chips for Apple’s iPhone 12, and in 2022 will build next-gen AMD Zen 4 chips. It has targeted 3-nanometer volume production for the second half of 2022 with products likely coming along in 2023.
TSMC expects the new tech to deliver 10-15 percent greater performance at the same power levels, or reduce power 25 to 30 percent at the same transistor speeds over 5-nanometer tech. The company also has a 4-nanometer N4 process set to arrive in 2022, offering an evolution over 5-nanometer with minimal changes required by chip designers.
Apple’s iPad will reportedly be the first devices powered by 3-nanometer chips, according to Nikkei‘s sources. The next generation of iPhones rolling out next year will supposedly use 4-nanometer tech for scheduling reasons.
Currently the chip volume planned for Intel is more than that for Apple’s iPad using the 3-nanometer process.
The situation with Intel is perhaps more interesting. Intel confirmed to Nikkei that it would work with TSMC for its 2023 product lineup and has previously said that it would subcontract some chip manufacturing out to the Taiwan-based company, though it didn’t say which technology it would use.
As it stands now, Intel has only just started rolling out its 10-nanometer chips (which are broadly equivalent to chips made with TSMC’s 7-nanometer process), and has delayed 7-nanometer production until 2023.
According to Nikkei, TSMC will produce more chips for Intel than Apple. "Currently the chip volume planned for Intel is more than that for Apple’s iPad using the 3-nanometer process," a source said. Intel plans to use TSMC to build processors for notebook and data servers "in an attempt to regain market share it has lost to Advanced Micro Devices and NVIDIA over the past few years," the story reads.
If the rumors prove accurate, Intel could possibly beat AMD to 3-nanometer tech, as AMD plans to use 5-nanometer chips for its next-gen Zen 4 processors. AMD now relies on TSMC for its processor and GPU chips, as its previous supplier GlobalFoundries decided not to manufacture 7-nanometer or smaller chips back in 2018.
TSMC is building a $12 billion chip fab plant in Arizona and plans to use its current 5-nanometer manufacturing technology. Intel, meanwhile, plans to invest $20 billion in two Arizona factories.
The derby by a dozen or more companies — Hyundai and GM, and Stellantis, Mercedes, Audi, you name it — to launch a “flying car” has not really involved anything you’d call a “car” that could fly. Instead, they are pursuing electric vertical takeoff and landing aircraft (eVTOL) that could taxi paying passengers from point A to point B, after which those folks would need to catch an Uber or something. But recently, a machine called AirCar actually performed both tasks implied by that name — flying between two airports in Slovakia, then transmogrifying into a road car and driving off.
It’s best just to show you, in this video above that was posted yesterday.
The AirCar prototype is built by a Slovakian company, Klein Vision, which launched the vehicle from Nitra and landed 35 minutes later in Bratislava. Then, the eponymous inventor and pilot Stefan Klein folded the aircraft’s wings and tucked its tail, a transition that takes about three minutes. And poof, it’s a car. Which actually drove off, to the applause of a throng of well-wishers.
Klein is said to have been working on a series of prototypes for 30 years, and has racked up 40 air hours. This was the craft’s 142nd landing, but its first inter-city flight. During its time in the air, the craft cruised at around 90 knots (105 mph). Klein said it has flown to 8,200 feet and has made 45-degree banking turns during testing, though it did nothing flashy on this outing. It’s powered by a 160-horsepower BMW engine and a simple fixed-pitch propeller. Like many small aircraft these days, it also has a ballistic parachute, just in case.
Klein says next up is a 300-horsepower model with a variable-pitch propeller. He says it will be capable of cruising at 160 knots to a range of over 600 miles, will achieve full commuter certification from European aviation regulators and will also be street-legal.
The challenge there, as always in achieving the “flying car” dream, is to balance the needs of an aircraft, not the least of which is lightness, with what it takes to be certified as roadworthy, particularly safety equipment and crashworthiness that can add a weight penalty. In the video, the AirCar prototype certainly looks like a car — a heavy car even — when it’s airborne. Compare it to the chase planes alongside it. Although it is kind of cute how the rear wheels keep spinning when it’s up there.
Also, like any small plane, the AirCar needs a runway to take off and land. The eVTOL approach being taken by the major players eliminates the challenges of being an automobile, or of being limited to runways. At least one startup, Terrafugia in Boston, however, has also spent years pursing the air-car twofer. Its vehicle, the Terrafugia Transition, earned an FAA light-sport airworthiness certification earlier this year.
