“You won’t believe what’s coming,” warned the title of a January 2023 video from the Inside China Auto YouTube channel. “Europe’s premium car makers aren’t ready for this,” warned another video from the same channel, uploaded in July.
Produced by Shanghai-based automotive journalist Mark Rainford, a former communications executive for Mercedes-Benz, the channel is one of several by China-based Western commentators agog at what they are seeing—and driving.
The channels tell salivating viewers that the tech-heavy yet keenly priced Chinese electric vehicles that have appeared on China’s domestic market since the end of the global pandemic will soon wipe the floor with their Western counterparts.
Auto executives in Europe, America, and Japan “didn’t believe China’s car companies could grow so fast,” Rainford told me. “That’s an easy mistake to make from outside the country. You see a lot of stories about China—they don’t hit home until you live here and experience it.”
Rainford worked at Mercedes-Benz for eight years—in the UK, Germany, and latterly China—and has lived in China, in two stints, for five years. He started his YouTube channel to cater to the growing interest in Chinese cars from overseas. His most popular video—“Think You Know Chinese Cars? Think Again. You Won’t Believe What’s Coming”—has had more than 800,000 views. It’s an 84-minute wander through the 11 immense halls of the Guangzhou Auto Show, previewing the automotive near future.
He highlighted cars from 42 brands, almost all of which are largely unknown outside China. Some of the eye-popping EVs he featured would be considered concept cars at a Western auto show, but many are already on the road in China.
These “digital bling” cars, as Oxford-based Ade Thomas, founder of the five-year-old World EV Day, calls them—some with navigation on autopilot (NOA) systems, a precursor to full-on autonomous driving; others with face-recognition cameras that monitor driver fatigue; more equipped with multiple high-res dashboard screens pimped with generative AI and streaming video—are not inferior, unsafe copycats, as mainstream Asian and Western automakers have often urged us to believe, they are standards-compliant, road-going smartphones.
This “iPhone on wheels” epithet has been used by Tesla for many years, with traditional auto brands—led, so the caricature goes, by sensible German men in suits on eye-watering remuneration packages—reportedly flailing in Elon Musk’s wake.
In 2016, Oskarina Fuentes got a tip from a friend that seemed too good to be true. Her life in Venezuela had become a struggle: Inflation had hit 800 percent under President Nicolás Maduro, and the 26-year-old Fuentes had no stable job and was balancing multiple side hustles to survive.
Her friend told her about Appen, an Australian data services company that was looking for crowdsourced workers to tag training data for artificial intelligence algorithms. Most internet users will have done some form of data labeling: identifying images of traffic lights and buses for online captchas. But the algorithms powering new bots that can pass legal exams, create fantastical imagery in seconds, or remove harmful content on social media are trained on datasets—images, video, and text—labeled by gig economy workers in some of the world’s cheapest labor markets.
Appen’s clients have included Amazon, Facebook, Google, and Microsoft, and the company’s 1 million contributors are just a part of a vast, hidden industry. The global data collection and labeling market was valued at $2.22 billion in 2022 and is expected to grow to $17.1 billion by 2030, according to consulting firm Grand View Research. As Venezuela slid into an economic catastrophe, many college-educated Venezuelans like Fuentes and her friends joined crowdsourcing platforms like Appen.
For a while, it was a lifeline: Appen meant Fuentes could work from home at any hour of the day. But then the blackouts started—power cutting out for days on end. Left in the dark, Fuentes was unable to pick up tasks. “I couldn’t take it anymore,” she says, speaking in Spanish. “In Venezuela, you don’t live, you survive.” Fuentes and her family migrated to Colombia. Today she shares an apartment with her mother, her grandmother, her uncles, and her dog in the Antioquia region.
Appen is still her sole source of income. Pay ranges from 2.2 cents to 50 cents per task, Fuentes says. Typically, an hour and a half of work will bring in $1. When there are enough tasks to work a full week, she earns approximately $280 per month, almost meeting Colombia’s minimum wage of $285. But filling out a week with tasks is rare, she says. Down days, which have become increasingly common, will bring in no more than $1 to $2. Fuentes works on a laptop from her bed, glued to her computer for over 18 hours a day to get the first pick of tasks that could arrive at any time. Given Appen’s international clients, days begin when the tasks come out, which can mean 2 am starts.
It’s a pattern that’s being repeated across the developing world. Labeling hot spots in east Africa, Venezuela, India, the Philippines, and even refugee camps in Kenya and Lebanon’s Shatila camps offer cheap labor. Workers pick up microtasks for a few cents each on platforms like Appen, Clickworker, and Scale AI, or sign onto short-term contracts in physical data centers like Sama’s 3,000-person office in Nairobi, Kenya, which was the subject of a Time investigation into the exploitation of content moderators. The AI boom in these places is no coincidence, says Florian Schmidt, author of Digital Labour Markets in the Platform Economy. “The industry can flexibly move to wherever the wages are lowest,” he says, and can do it far quicker than, for example, textile manufacturers.
Meta’s flirtation with innovation has been, at best, poorly panning out and, at worst, delightfully creepy. The latter best describes the case of the tech company’s new foray into AI with machine-generated personas.
News broke late last month that Meta would begin adding some new AI-generated personas to platforms like Instagram and Facebook in the coming weeks, and those personas are now live. Take, for example, Billie who is based on the likeness of model and socialite Kendall Jenner. According to her Instagram bio, Billie is “your local ride or die” based in New York City. A gray disclaimer tag indicated that the account is not, in fact, a human clone of Jenner but is “AI managed by Meta.” Billie’s feed is chock full of AI-generated imagery of photoshoot sets, brick oven pizza, a cheugy fall spread, and even an introductory Reel with a caption touting that “chatting with me is like having an older sister you can talk to, but who can’t steal your clothes.”
“Our journey with AIs is just beginning, and it isn’t purely about building AIs that only answer questions. We’ve been creating AIs that have more personality, opinions, and interests, and are a bit more fun to interact with,” Meta wrote in a release. “And because interacting with them should feel like talking to familiar people, we did something to build on this even further. We partnered with cultural icons and influencers to play and embody some of these AIs.”
Billie is one of 28 AI influencers that Meta has added to Facebook, Instagram, Messenger, and WhatsApp, all with a unique personality and a likeness based on some celebrity or public figure. The AI influencers began posting towards the end of September, and users can direct message these influencers and have a conversation with a chatbot, or browse their feeds for AI-generated content. These profiles may also feature an occasional video or selfie from the celebrities playing these AI characters, who shot content in a studio. Along the way, the faceless corporation tries its best to be hip and relatable with half-hearted attempts at sparking memes and generating social media challenges.
Meta is not breaking any new ground with these AI personas as virtual influencers were popularized by the likes of Lil Miquela, an artificial teenager who has a music career and has modeled for Calvin Klein. What Meta is doing is begging you to spend time on Instagram and use its in-house AI chatbot to spill your guts and ask for recipes. Whether or not people want to meme on the AI or genuinely interact with it, people will be using it, at least for a while. And numbers are numbers.
You can add supernova spotting to the laundry list of accolades attributed to artificial intelligence. This week, a collaboration of astronomers led by Northwestern University said they have developed the world’s first AI-assisted, fully automatic supernova detection, identification, and classification system. The powerful new tool, which the scientists say could “significantly streamline” large studies of exploding stars in the future, has already detected its first supernova.
Prior to this tool, astronomers involved in its creation say, supernova detection relied on a combination of automated systems and human verification methods. Ordinarily, robotic telescopes gaze out into sections of the sky in search of new potential supernova sources that weren’t there before. Once a candidate is spotted, the process is then usually handed over to humans operating telescopes with spectrographs to collect the source’s spectrum, or dispersed light. The automated tool, dubbed the “Bright Transient Survey Bot” (BTSbot),” aims to remove that human middle-man from the process.
Researchers fed the BTSbot machine learning algorithm 1.4 million images from 16,000 astronomical sources. Those images included past evidence of supernovae, glaring galaxies, and temporarily flaring stars. Equipped with that training set, the AI model was able to identify a new supernova candidate and automatically request its spectrum reading from a robotic telescope at the Palomar Observatory in California. The system eventually identified the supernova candidate as a “stellar explosion” in which a white dwarf star fully exploded, and it automatically shared its findings with the astronomical community. In other words, the AI system identified and shared the new discovery all on its own—great news to the humans involved.
“The simulated performance was excellent, but you never really know how that translates to the real-world until you actually try it,” Northwestern graduate student Nabeel Rehemtulla said in a statement. “We felt a huge wave of relief.”
Astronomers responsible for building BTSbot believe all that extra time saved trying to manually detect and identify supernovas will give human scientists more time to analyze their observations and consider new ideas.
“Ultimately, removing humans from the loop provides more time for the research team to analyze their observations and develop new hypotheses to explain the origin of the cosmic explosions that we observe,” Northwestern Assistant Professor of Physics and Astronomy Adam Miller said.
Of course, astronomers don’t necessarily need fully automated AI systems to snap snazzy supernova images. Keep reading for a series of some of the most interesting supernova discoveries in recent memory. If you’re feeling particularly sentimental, you can pour one out for human supernova detectors while you’re at it.
The best seat in the house.Image: Space Perspective
In space, no one can hear you tinkle. But just to be sure, Space Perspective has designed a luxuriously private bathroom experience on board its balloon-propelled capsules.
The space tourism company has already sold more than 1,600 tickets for its luxurious trips to the edge of space, which it says will commence in 2024. On Monday, Space Perspective unveiled a rendering of its “space spa” design, equipped with a toilet, sink, and what’s guaranteed to be a breathtaking view that can be enjoyed in sweet, sweet solitude.
“We’re thinking of the lavatory as the one place that you can actually go where you can essentially be alone,” Dan Window, head of experience design at Space Perspective, told Gizmodo in an interview. “It’s the opportune time for the ultimate kind of selfie experience.”
Unlike other space tourism experiences, the ride on board Space Perspective’s Spaceship Neptune is six hours long, so this bathroom design is a first-of-its-kind necessity.
It used to be that if you dreamed of reaching 6GHz speeds with your hot rod desktop CPU, you’d have to try your luck with overclocking and all of the potential instability and cooling demands that required. Earlier this year, Intel released the Core i9-13900KS, which hit 6GHz right out of the box. Now, the company is doing it again with its fastest 14th-gen desktop CPU, the i9-14900K. That frequency is just a short-lived "Thermal Velocity Boost" speed, which isn’t sustained for very long, but it’s still something Intel can lord over AMD.
These 14th-gen chips, to be clear, are different from Intel’s recently announced 14th-gen Core Ultra processors for notebooks. Understandably, Intel is focusing on efficiency for its mobile lineup, whereas its desktop chips are all about raw power (and 6GHz bragging rights). You can look at the 14th-gen desktop hardware as a last gasp for Intel’s existing architecture, where the company doesn’t mind pushing power demands to out-bench AMD. (The i9-14900K consumes as much as 253 watts, just like its predecessor.)
Intel’s highest-end 14th-gen chip may get most of the attention, but discerning gamers may be more interested in the i7-14700K, which now features 20 cores (8 performance and 12 efficiency) and reaches up to 5.6GHz "Turbo Boost Max 3.0" speeds. Perhaps most importantly, its $409 price tag is well below the 14900K’s $589.
When it comes to benchmarks, Intel claims the 14900K is up to 23 percent faster than AMD’s Ryzen 9 7950X3D while playing Starfield in 1080p. The company also says that chip is up to 54 percent faster than the same AMD hardware while multi-tasking between After Effects and Premiere Pro. (That comparison may be a bit unfair, since Intel tested an Auto Reframe task in Premiere Pro that works together with its UHD graphics, something that AMD’s graphics don’t help with.)
Intel
Perhaps more useful than raw benchmark comparisons, Intel also says the i9-14900K was able to reach over 100fps in Total War: Warhammer III while playing, streaming and recording in 1080p with ultra graphics settings. That game is also optimized specifically for its 14th-gen hardware, so you can’t expect the same results with every title.
If you’re still eager to overclock, Intel is also making that easier with its new XTU AI Assist feature, which will only be available on the i9-4900K. In a demo for media, an Intel representative showed off how the XTU app can quickly determine the ideal processor core voltages, motherboard power settings and "other tuning knobs" to determine safe performance speeds. They noted that Intel had trained its AI overclocking model on hundreds of CPUs, as well as a variety of motherboard and cooler options (including a bit of liquid cooling). Once the AI tuning process is complete, you can roll with its suggested settings or use them as a baseline for further overclocking.
One feature you won’t see in these new 14th-gen chips? An NPU (neural processing unit) for AI acceleration. Oddly enough, the company’s upcoming Core Ultra mobile chips will feature an NPU, which enables things like Windows Studios Effects for AI-powered background blurs in video chats. It makes sense for Intel’s first NPU to appear in its new architecture, whereas the 14th-gen desktop chips are beefed-up versions of last year’s hardware. Still, it’s a bit odd for its priciest desktop hardware to miss out on something mere laptops will see next year.
Intel’s 14th-gen desktop chips will be available from retailers and system manufacturers on October 17th.
This article originally appeared on Engadget at https://ift.tt/N42aBoH
Missy Cummings flew fighter jets for the Navy. Now, as a leading expert on automation and AI, she’s taking aim at self-driving cars. Chelsea Jia Feng/Insider
In 2021, an engineer named Missy Cummings drew the ire of Elon Musk on the social network then called Twitter. A professor at Duke University, Cummings had conducted research on the safety of self-driving cars, and the findings led her to issue some stark warnings about Tesla’s driver-assistance tech. The cars, she wrote, had “variable and often unsafe behaviors” that required more testing “before such technology is allowed to operate without humans in direct control.” On the strength of her research, Cummings was appointed to the National Highway Traffic Safety Administration — to help with regulation of robot cars.
Tesla fans reacted with their usual equanimity and sense of perspective, by which I mean they absolutely lost it. Their insistence that Cummings would attempt to unfairly regulate their boy Elon soon prompted Musk himself to join the thread. “Objectively,” he tweeted, “her track record is extremely biased against Tesla.” In response, Musk’s stans unleashed their full fury on Cummings — her work, her appearance, her motives. They accused her of conflicts of interest, signed petitions demanding her removal, and emailed death threats.
But the thing is, Musk’s bros of war were messing with the wrong engineer. As one of the Navy’s first female fighter pilots, Cummings used to fly F/A-18s. (Call sign: Shrew.) She wasn’t intimidated by the dick-wagging behavior of a few people on Twitter with anime profile pics. She posted the worst threats on LinkedIn, hired some personal security, and kept right on fighting. “I’m like, are you really going to do this?” she recalls thinking. “I double down. The fighter pilot in me comes out. I love a good fight.”
She didn’t exactly win that particular engagement. A lot of whinging from Tesla pushed NHTSA to force Cummings to recuse herself from anything involving the company. But you know what they say about any landing you can walk away from. Cummings took a new gig at George Mason University and broadened her research from Tesla to the wider world of all self-driving vehicles. With companies like Cruise and Waymo unleashing fully roboticized taxis on the streets of San Francisco and other cities, the rise of the machines has begun — and Cummings is on the front lines of the resistance. In a controversial new paper, she concludes that the new robot taxis are four to eight times as likely as a human-driven car to get into a crash. And that doesn’t count the way self-driving vehicles are causing weird traffic jams, blocking emergency vehicles, and even stopping on top of a person who had already been hit by a human-driven car.
“In the paper that really pissed all the Tesla trolls off, I actually say that this is not just a Tesla problem — that Tesla is the first one to experience the problems,” Cummings tells me. “For years I have been telling people this was going to happen, that these problems would show up in self-driving. And indeed they are. If anyone in the self-driving car community is surprised, that’s on them.”
It turns out that serving in the Navy is a very good way to train for inbound ire from Muskovites. In her 1999 memoir, “Hornet’s Nest,” Cummings recalls how she loved flying jets, and says the excitement of getting catapulted off an aircraft carrier — or landing on one — never got old. But the environment was far from welcoming. Sexual harassment in the Navy was routine, and male colleagues repeatedly told Cummings she wasn’t qualified to fly fighters simply because she was a woman. When she and another female officer showed up at a golf tournament on base, they were told to put on Hooters uniforms and drive the beer carts. Cummings declined.
Flying tactical engines of destruction also provided Cummings with a firsthand lesson in the hidden dangers of machines, automation, and user interfaces. On her first day of training, two pilots were killed. On her last day, the Navy experienced the worst training disaster that had ever taken place aboard a carrier. In all, during the three years that Cummings flew, 36 people died in accidents.
In 2011, while conducting research on robot helicopters for the Navy, Cummings had an epiphany. Even surrounded by nothing but air, those helos were far from perfect — and they relied on the same sensors that self-driving cars do while operating right next to cars and people. “When I got in deep on the capabilities of those sensors,” Cummings says, “that’s when I woke up and said, whoa, we have a serious problem in cars.”
Some of the dangers are technical. People get distracted, self-driving systems get confused in complicated environments, and so on. But other dangers, Cummings says, are more subtle — “sociotechnical,” as she puts it. What she calls the “hypermasculine culture in Silicon Valley” intertwines with Big Tech’s mission statement to “move fast and break things.” Both bro culture and a disruptive mindset, as she sees it, incentivize companies to gloss over safety risks.
All of which makes it even tougher for women when they level the kind of critiques that Cummings has. “When Elon Musk sicced his minions on me, the misogyny about me as a woman, my name — it got very dark very quickly,” she recalls. “I think the military has made a lot of strides, but I do think that’s what’s happening in these Silicon Valley companies is just a reminder that we haven’t come as far in our society as I thought we would have.”
An example: Last month, the head of safety at Waymo touted a new study from his company on LinkedIn. The research was unpublished and had not undergone peer review. But Waymo used the study to argue that its robot cars were actually much less likely to get into crashes than cars driven by biological organisms like you and me.
A self-driving taxi from Waymo blocks traffic in San Francisco. “They got complacent,” says Cummings. “They lost their safety culture.” Terry Chea/AP
Cummings wasn’t having it. She had her new results — also still in preprint — which showed self-driving taxis to be way more crash-prone. So she went on LinkedIn, too, and said so.
The response was familiar to her from her days in the Navy. Kyle Vogt, the CEO of Cruise, slid into the comments. “I’d love to help you with this analysis,” he wrote to Cummings, questioning her number-crunching. “Would be great to connect and discuss this further.”
Cummings responded in kind. “I’d love to help you with your understanding of basic statistics, use of computer vision, and what it means to be a safe and responsible CEO of a company,” she wrote. “Call anytime.”
Women, she figures, caught her vibe. “Every woman who read that was like: Mmm-hmm, you go,” Cummings says. But men — friends in Silicon Valley — did not. They thought she had been too mean to Vogt. “He was just trying to help you,” they told her.
“All the guys read it like: She’s such a shrew!” Cummings says. But, ever the fighter pilot, she was unfazed. “That’s how I got my call sign,” she says. “So I live with it.”
So who’s right: Cummings, or the self-driven men of Waymo and Cruise and Tesla? It’s hard to tell, for a simple reason: The data on the safety of robot cars sucks.
Take Cummings’ approach in her new paper. First she had to wrestle with NHTSA’s nationwide data for nonfatal crashes by human drivers, to get numbers she could compare to California, the only place where the robot cars run free. Then she had to figure out comparable nonfatal crash numbers and miles traveled for Waymo and Cruise, tracked by divergent sources. Her conclusion: Cruise has eight nonfatal crashes for every human one, and Waymo has four — comparable to the crash rates of the fatigued and overworked drivers at ride-hail services like Uber and Lyft.
The purveyors of robot taxis argue that Cummings is wrong for a bunch of reasons. Chiefly, they say, the numbers for human crashes are actually undercounts. (Lots of fender benders, for instance, go unreported.) Plus, crash numbers for the whole country, or even just California, can’t be compared to those for San Francisco, which is way denser and hillier than the state as a whole. Looked at that way, Cruise argued in a recent blog post, its taxis have been involved in 54% fewer crashes than cars driven by humans. The company also maintains that ride-hail drivers get into one nonfatal crash for every 85,027 miles of driving — 74% more collisions than Cruise’s robots.
Cummings ain’t buying it. A blog post isn’t science; it’s a press release. “Every company has a fiscal interest in getting a paper out that makes them look good, and in the case of Cruise it makes rideshare drivers look bad,” she says. “So that’s what they’re doing.” This is exactly the sort of sociotechnical culture that Cummings is criticizing — that she’s uniquely qualified to criticize.
Other experts also discount Cruise’s claims, coming as they do from folks who are incentivized to welcome our new robot overlords. “If we were to believe the numbers Cruise is putting out there for ride-hailing drivers, those drivers would be having on average two crashes per year,” says Steven Shladover, a research engineer at UC Berkeley’s Institute of Transportation Studies. “How many drivers have two crashes every year? That is pretty extreme.”
But Shladover is also skeptical of the numbers crunched by Cummings. “Missy is assuming a human driver crash rate that’s too low for San Francisco, and Cruise is showing a human crash rate that’s too high,” he says. “The reality is probably somewhere in between.”
So maybe Cummings is right, and self-driving cars are a menace. Or maybe it’s not quite as bad as her new paper suggests. Until robot cars have traveled for hundreds of millions of miles, there’s no way to get a statistically significant, unequivocal conclusion. But the bottom line is: It shouldn’t matter. When the data on a product or device’s safety is equivocal, regulatory agencies are supposed to make and enforce rules that protect consumers, just as they do in other industries. If the data on robot cars is equivocal or incomplete, then those rules should keep them off the road. The burden of proof is on Waymo and Cruise and Tesla, not Missy Cummings. And if those companies want to put 2-ton robots on public streets, blogging about data benchmarks isn’t the way to show people they’re ready.
“One of the big things I’m on about now, pulling from my aviation years, is that all these companies need a chief AI pilot,” Cummings says. “They need to have somebody, one person, who stands up and says, ‘I’m responsible.’ We do that right now for aviation. That’s why so many heads rolled with the problems that happened with the Boeing 737 Max. They got complacent. They lost their safety culture.”
Cummings is a careful researcher. She’s also, as one transport-safety researcher put it privately, “provocative.” She is more than happy to strafe companies like Tesla and Waymo and Cruise, and to argue that tech bros need to be brought inside a stricter regulatory framework. In a sense, she’s Elon Musk’s worst nightmare. She has repeatedly and routinely risked her life to test the incredible capabilities — and the lethal limits — of human-machine interfaces. And she did it in an environment where the stakes are far higher than the battlefields of Twitter and LinkedIn. To her, the safety of self-driving cars is not an abstract question. It’s a matter of life and death.
“I’m a tenured professor. My work speaks for itself. I’m trying to save your life, right?” Cummings says. “And there’s the side of me where I’m like Don Quixote on steroids. There’s no windmill I don’t want to tilt at.”
