Between its ongoing supply chain constraints, brutal rounds of layoffs and a plummeting stock price, the past year has been a glass case of emotion for Tesla and its embattled CEO, Elon Musk. Still, the company managed to produce nearly 440,000 vehicles and delivered over 405,000 of them — year over year increases of 47 and 40 percent, respectively — Tesla announced on Wednesday during the Q4 2022 earnings call. Those are both records for Tesla, as was the full-year deliveries of 1.31 million. Profits for the year totaled $12.6 billion.
"Despite the fact that 2022 was an incredibly challenging year due to forced shutdowns, very high interest rates, and many delivery challenges," Tesla CEO, Elon Musk, said during the call. "It's worth noting that all these records were in the face of massive difficulties. a credit to the team for achieving that."
The final quarter of 2022 was especially volatile for the electric automaker following the finalization of Musk's Twitter acquisition in late October. While the billionaire sought to split his attention between his EV company, his spaceship company and his new social media platform, Tesla shareholders revolted, furious that the automaker had lost some $620 billion in market capitalization that year. Musks antics at Twitter combined with his sale of Tesla stock to fund the acquisition sent the EV company's ticker tumbling, resulting in drastic price cuts — by as much as $20,500 in some cases. This, in turn, saw customers in China, angry that they had just purchased their vehicles at a higher price, raid Tesla showrooms to demand answers and restitution.
"The most common question we've been getting on investors is about demand," Musk said. "I want to put that concern to rest. Thus far in January, we've seen the strongest orders here today then ever in our history, we currently are seeing orders at Almost twice the rate of production."
Those price cuts will continue into the new year. "In the near term we are accelerating our cost reduction roadmap and driving towards higher production rates," the company announced Wednesday. "In any scenario, we are prepared for short-term uncertainty, while being focused on the long-term potential of autonomy, electrification and energy solutions."
Despite the turbulence, Tesla continues to expand its regional production capacities. In January, the company announced its $3.6 billion investment in two new factories, one of which will produce the long-awaited, repeatedly-delayed Semi electric 18-wheeler. The company aims to produce 1.8 million vehicles in total this coming year.
Honda has big plans for the new year and electrification will play a huge part of that, the company's recently-promoted SVP of Sales, Mamadou Diallo, told reporters on Tuesday. Expect to see a lot more Honda and Acura hybrids on the road this year, ahead of a major EV push come 2024.
Overall, Honda is officially aiming to move 1.2 million units in 2023, with Acura shooting for 160,000 units, a 20 - 25 percent increase over what they sold in 2022. And although the company managed to maintain a single-digit days' supply of vehicles throughout last year, it enters 2023 with a glut of cars and trucks and a 17-day supply. As such, dealers are going to be looking to move a lot of that inventory before this year's models start arriving so fingers crossed, we could potentially see some Tesla-level price cuts in the near future.
"In 2023, we will see the strategies we've been talking about, including growing sales of light truck models, increasing volume of hybrid-electric models and the start of digital sales at Acura," Diallo said in a Wednesday press release. "All this leads toward our vision of 100-percent electrified sales by 2040 to fulfill our ultimately goal of zero emissions by 2050."
The ZDX and ZDX Type S will be Acura's first full-EV offerings and serve as the harbingers of the company's new, exclusively online EV sales strategy. Diallo didn't have much additional information regarding how the system would work — such as whether haggling was allowed or how individual vehicle prices would be set — but assured the assembled journalists, "as we get closer to [the ZDX debut], we certainly will be discussing this a little bit more with our dealer body and the press in general. For right now we're still finalizing all those details." Acura joins Ford, Volvo, GM and VW in shifting its electrified vehicle sales to the digital marketplace.
For its part, Honda is planning a significant increase in its hybrid vehicle production in 2023, starting with the newly-redesigned Accord and Accord Hybrid (they'll also be Honda's first with Google Built-In). The company "will continue to increase hybrid sales through core models as an important step in bridging customers to full electrified vehicles while reducing GHG emissions," the Wednesday release reads. Honda anticipates a solid half of this year's CR-V and Accord sales to be of the hybrid variety and its efforts bolstered in 2024 with the introduction of a new Civic hybrid. Sales for the all electric Prologue begin this year with deliveries set for 2024.
If you just bought a 2023 Polestar 2, hoooo boy are you about to be mad. The company on Tuesday showed off some of the, ahem, numerous updates that the upcoming 2024 model year PS2 will sport, including next-generation motors, a slew of new standard equipment, a more potent battery pack and the SmartZone sensor suite first teased on the Polestar 3. Also, the previously front-wheel drive single motor Polestar 2 — that's RWD now, so let the drifting begin!
The Polestar 2 is now a fully RWD platform for the single-motor variant that arrived in March. It uses newly devised permanent magnet motor and silicon carbide inverter technologies to increase the horsepower output from 231 to 299 hp. Torque similarly jumps from 243 lb-ft to 361, putting it in line with the Tesla Model 3's output, while the 0-60 figure drops more than a full second compared to the old motor, to 5.9 seconds.
Polestar
The dual-motor AWD version will see equivalent performance gains — 421 hp and 546 lb-ft, up from 408 hp and 467 lb-ft — as well as improved traction and a 0-60 of 4.3 seconds. Opt for the 2024 Performance pack and the horsepower jumps to 455 and the 0-60 drops to 4.1 seconds. The powertrain and torque ratios in the dual-motor version have been given a rear-wheel bias and, when the extra performance of AWD isn't necessary, the second (front) motor can be disengaged to improve efficiency and range (using the larger battery of 82 kWh) up to 300 miles, a 10 percent increase.
The PS2's battery is receiving some slight chemistry tweaks as well. It to now offer a max 205kW charge rate while requiring 1.1 fewer tons of carbon emissions to produce — now just 5.9 tons per battery pack! Note however that this specifically applies to the Long Range single motor variant, the dual-motors both are stuck with the existing 78 kWh packs charging at 155 kW.
Polestar
“Changing from front- to rear-wheel drive in the single-motor variants, and re-calibrating the torque ratio in the dual-motor variant for an increased rear-wheel drive feel, elevates the Polestar 2 driving experience to a whole new level,” Joakim Rydholm, Head of Chassis Development, said in a press release. “The updated Polestar 2 is an even more playful and agile car, retaining its compactness and complete sense of control, while at the same time becoming more mature with added comfort.”
Polestar
Next year's PS2 will be quite a bit smarter than its predecessor thanks to tech first shown off by its successor, the PS3. Polestar's SmartZone, mounted in the vehicle's vestigial front grille, houses an improved mid-range radar array and front-facing camera. A number of ADAS systems will come standard as well. For example, the Pilot Pack (which includes the 360-degree camera, parking assist and adaptive cruise control) will now come standard on the long-range dual motor PS2, while every trim level will get wireless device charging. And for folks that purchase the Performance package (Brembo brakes, 20-inch rims and a performance software upgrade) will receive the Plus package (Harmon Kardon stereo, panoramic glass roof, air quality software that sounds like something everyone should get just like the device charging) for no additional cost. Deliveries are expected to begin later this year and Polestar's online order window has already opened.
San Francisco has long sought to square its deeply-held progressive ideals with the region's need for tangible, technological progress. SFO international airport, which opened for business in 1959 and has undergone significant expansion and modernization in the years since, is a microcosm of that struggle. On one hand, the Bay Area likely wouldn't be the commercial, technical, and cultural hub that it is today if not for connectivity the airport provides. On the other hand, its installation and operation has had very real consequences for the local environment and the region's populace.
Dr. Eric Porter, Professor of History, History of Consciousness, and Critical Race and Ethnic Studies at the University of California, Santa Cruz, examines how San Francisco International came to be and the challenges it will face in a climate changing 21st century in his latest work, A People's History of SFO: The Making of the Bay Area and an Airport. Porter's connection to the topic is a personal one. "My grandfather worked as a skycap there beginning in the 1940s," Porter wrote in a recent UC Press blog. "Carrying white people’s luggage and the racial baggage that came with it was servile but good-paying work."
As Black skycaps protested changes to their working conditions during the spring and summer of 1970, a different group of activists, largely white and operating primarily as homeowners rather than as workers, were engaged in their own SFO-focused struggle. The issue was jet noise, a long-standing nuisance that had become more unbearable as the airport grew and as environmentalists and government agencies deemed it a form of pollution that could have detrimental effects on human well-being. That November, after months of unsuccessfully lobbying airport and government officials for changes to SFO flight operations, thirty-two property owners from South San Francisco, a then largely white working- and middle-class suburb located northwest of the airport, filed claims with the San Francisco Airport Commission seeking compensation for the disruptions caused by jets taking off over their neighborhoods. The commission denied the claims, so the following February the South San Franciscans filed a $320,000 lawsuit ($10,000 per plaintiff) against the City and County of San Francisco on the grounds that jet noise had “diminished and damaged” the “reasonable use and quiet enjoyment of their property.” Subsequently, ten individuals from the tonier suburbs of Woodside and Portola Valley, located southeast of the airport, filed their own lawsuit, requesting the same per-person damages caused by noise from aircraft on approach to SFO.
These lawsuits, ultimately settled by the Airport Commission’s promise to institute a $5 million noise mitigation program, were among the many antinoise actions undertaken by outraged SFO neighbors following the introduction of jet aircraft to the facility in 1959. Their communities had grown in symbiotic relationship with SFO in ways physical, social, political, and economic. Jet sounds helped to compose their soundscapes, or acoustic environments, offering their inhabitants references through which they conceptualized and lived their urban experiences. The sounds oriented local residents toward the sky, providing a generalized sense of being urban, while also defining their relationships to SFO through the horizontal positioning of homes, workplaces, recreation sites, schools, and other places they inhabited in relation to takeoff and landing vectors and the facility itself.
How people experienced this relationship to place via jet sounds — whether positive, negative, or ambivalent—was affected by people’s proximity to such sounds, the frequency and duration of them, their relative audibility in relation to other components of the soundscape, and the social and political meanings they were conditioned over time to hear in them. When Bay Area residents heard jet sounds as “noise,” it was often simply because they were loud and profoundly disruptive. But at other moments jet noise was a more subjective, socially determined “unwanted sound.” Such determination happened, in part, as anthropologist Marina Peterson’s work on LAX and its environs helps us understand, because of what these insistent sounds had come to symbolize as they catalyzed relationships among an expanding ensemble of individuals and community groups; government officials, agencies, and regulations; activists and their organizations; scientists and other researchers; the airport and its operations; and a broad set of social, political, and economic forces.
Some local residents were willing to tolerate the noise. It was an inconvenience to be put up with in exchange for the benefits of living, working, or doing business near the airport. Noise itself, and the impunity to make it, might have signified the financial and political interests of airlines, airport officials, and other powerful interests, but these entities offered something (jobs, construction contracts, airport employee spending, convenient travel, and so on) in return. For others, however, this loud component of the soundscape signified differently on the pros and cons of living near the airport as well as on the relationships in which they were immersed. Jet noise, in other words, could be heard as a manifestation of the forms of power that defined the regional colonial present, and it raised the question of how local residents would live out their attachments to them.
Anti–jet noise activism by individuals, homeowner associations, political figures, environmental groups, and others around SFO usually reflected their relative degrees of privilege and aspiration as mostly white beneficiaries of accumulated colonial power in the region. Yet their activism simultaneously articulated critiques, explicit and implicit, of the ways elements of the power—economic, legal, bureaucratic, and so on—that lay behind the noise had diminished human thriving in the region more generally. Airport and local government officials, labor unions, and others who opposed, deflected, or sought to incorporate strategically the goals of these activists also expressed or otherwise engaged multiple forms of social, economic, and bureaucratic power while seeking to advance or protect their own accumulated interests.
The activists had some successes. SFO and its surrounding communities eventually became less noisy because of changes in aircraft technology (especially engine technology) and also because the FAA, airport operators, civic leaders, and others eventually started to listen to anti-noise activists and made significant efforts to mitigate jet noise. But jets continued to generate noise at and near SFO, and some people are still complaining about the problem today. Still, the history of antinoise activism around SFO—the version in this chapter runs from the late 1950s into the 1980s — is still worth exploring because it makes audible some of the complex ways that challenging and reproducing power in the mid- and late twentieth-century regional colonial present occurred through the synergies, conflicts, and missed opportunities for cooperation among largely white homeowner, environmentalist, and worker movements when they collided with SFO as manifestation of broader economic transformations and modes of governmental infrastructure development and resource stewardship.
• • •
Aircraft noise had been the subject of intermittent complaints in the Bay Area going back to the early days of aviation. Concern that loud air planes might depress real estate prices was among the factors that led to the shuttering of San Francisco’s early civilian airstrip in the Marina District. Noise was initially not a problem around Mills Field. Aircraft of the 1920s and 1930s were not terribly loud, and there was little residential development nearby. That began to change after World War II as commercial air operations at what became SFO increased, aircraft grew in size and sound-generating capability, and residential neighborhoods encroached upon the airport. As was the case elsewhere in the United States, growing local concern about airport noise dovetailed with fears of aircraft crashing into homes or businesses below, as happened near the Newark and Idlewild airports in late 1951 and early 1952. Two pre–jet age incidents of aircraft developing engine trouble after taking off over South San Francisco increased the level of anxiety about that community’s proximity to SFO in particular. Complaints, emanating primarily from five surrounding cities, grew exponentially with the arrival of jet aircraft in April 1959. Residents of San Bruno, Daly City, and, most vocally, South San Francisco were primarily affected by aircraft departing to the northwest from runway 28, oriented to allow aircraft to take off into the wind through the “gap” between San Bruno Mountain and the Santa Cruz Mountains. South San Franciscans formed neighborhood jet noise committees, but their complaints were often channeled through city councilman and later mayor Leo Ryan and City attorney John Noonan. The two officials began a dialogue with airport representatives, pilots, airlines, and federal officials about the coming jet noise problem in 1957, commissioned an engineer’s report on the matter, and stepped up their efforts after the jets arrived.
As complaints from South San Francisco increased, and as technological advancements permitted more takeoffs in crosswinds or slight tail winds, flights were shifted to the intersecting, perpendicular runway 1 in an effort to redistribute aircraft noise. This made things more difficult for residents of Millbrae and northeastern Burlingame and especially for those living in Bayside Manor, a Millbrae neighborhood established in 1943, across the Bayshore Freeway from the end of the runway. Bayside Manor residents were primarily affected by the “jet blast” (i.e., noise, vibration, and fumes) from aircraft as they began their takeoffs just seven hundred feet away from the edge of the development. Residents organized primarily through the Bayside Manor Improvement Association, formed in 1948, which had for several years been fighting the placement of industrial facilities on undeveloped land near their subdivision.
Local residents experienced a variety of dramatic and disruptive effects from jet engine-produced sound waves. According to a Millbrae woman, “We thought the old planes were bad enough. But jets are terrible. The house shakes, light bulbs burn out from the vibration, and we can’t hear TV programs when the planes are taking off.” People also complained about frightened and crying children, sleepless nights, distractions in schools, disrupted church and funeral services, interrupted in-person and telephone conversations, jumping phonograph needles, the inability to entertain outside, and actual physical damage to their property from sonic vibrations: cracked walls, stucco, chimneys, fire places, gas lines, and windows, as well as dishes breaking after falling from shelves. They worried about falling home values and about their physical and mental well-being. Some were exhausted. Others complained of headaches, earaches, temporary hearing loss, and other ailments. According to one petition, some South San Franciscans were “in a constant state of anxiety and have had to undergo medical treatment for nervous conditions said to have been induced by the noises created by the jet aircraft and the anxiety due to the passage of jet aircraft over their homes.”
Elon Musk wasn't lying last October when he told Bloomberg that 75 percent of the employees at his newly acquired toy, Twitter.com, wouldn't lose their jobs under his ownership, as The Washington Post had reported at the time. Turns out, it's closer to 80 percent. Of the roughly 7,500 people working there before Musk's takeover, CNBC reports Friday that barely 1,300 in total, and fewer than 550 full-time engineers, are left at the husk of a company, either through said layoffs or voluntary resignations.
CNBC also notes that 75 employees are currently on leave, 40 of which are engineers, while the Trust and Safety team, which oversees content moderation for the site, has been culled to fewer than 20 full-timers. This news comes at the end of a seemingly ceaseless string of blunders since Musk announced an unsolicited $44 billion bid to buy the social media site last April.
In the video above, Atlas shows a surprising amount of forethought, grabbing and placing a wooden plank across a large gap before heading over to pick up the tool bag itself. From there, it's a simple matter of climbing a set of stairs, balancing across said plank, hopping up a couple ledges, jump spinning in place to turn around and gently hucking the bag over its head to the platform above. That's all before it shoves a box off its platform — carefully avoiding not tilting over the side itself and then, "dismounting with an inverted 540-degree flip that project engineers have dubbed the Sick Trick,'" according to Wednesday's release.
“Parkour forces us to understand the physical limitations of the robot, and dance forces us to think about how precise and dexterous the whole-body motion can be,” Robin Deits, a software engineer on the Atlas controls team, said in that release. “Now, manipulation is forcing us to take that information and interpret it in terms of how we can get the hands to do something specific. What’s important about the Atlas project is that we don’t let go of any of those other things we’ve learned.”
But don't expect an Atlas to replace your local UPS driver anytime soon (for one, their union would never allow it) because for as impressive as this video is, it took a substantial amount of time and effort to develop. As you can see in the behind-the-scenes video above, Atlas suffered dents, scrapes, scratches, and more than a few tumbles in learning this routine.
"This is more a demonstration of some of the robot’s new control capabilities, and a fun connection to our prior work,” Scott Kuindersma, Atlas team lead said. “Our hope is that, if we can build the foundational technology that allows us to easily create and adapt dynamic behaviors like these, we should be able to leverage it down the road to perform real, physically-demanding jobs with hustle. There are many pieces required to deliver a complete solution in a domain like manufacturing or construction—this video highlights a narrow slice of what we’re working on.” So maybe it isn't so much the hyper-agile acrobots we need to worry about as it is the EOD machines armed with high explosives and piloted by the cops.
"It is Getty Images’ position that Stability AI unlawfully copied and processed millions of images protected by copyright and the associated metadata owned or represented by Getty Images absent a license to benefit Stability AI’s commercial interests and to the detriment of the content creators," Getty Images wrote in a press statement released Tuesday. "Getty Images believes artificial intelligence has the potential to stimulate creative endeavors."
"Getty Images provided licenses to leading technology innovators for purposes related to training artificial intelligence systems in a manner that respects personal and intellectual property rights," the company continued. "Stability AI did not seek any such license from Getty Images and instead, we believe, chose to ignore viable licensing options and long‑standing legal protections in pursuit of their stand‑alone commercial interests."
The details of the lawsuit have not been made public, though Getty Images CEO Craig Peters told The Verge, that charges would include copyright and site TOS violations like web scraping. Furthermore, Peters explained that the company is not seeking monetary damages in this case so as much as it is hoping to establish a favorable precedent for future litigation.
Text-to-image generation tools like Stable Diffusion, Dall-E and Midjourney don't create the artwork that they produce in the same way people do — there is no imagination from which these ideas can spring forth. Like other generative AI, these tools are trained to do what they do using massive databases of annotated images — think, hundreds of thousands of frog pictures labelled "frog" used to teach a computer algorithm what a frog looks like.
And why go through the trouble of assembling and annotating a database of your own when there's an entire internet's worth of content there for the taking? AI firms like Clearview and Voyager Labs have already tried and been massively, repeatedly fined for scraping image data from the public web and social media sites. An independent study conducted last August concluded that a notable portion of Stable Diffusion's data was likely pulled directly from the Getty Images site, in part as evidenced by the art tool's habit of recreating the Getty watermark.
“We are now at the dawn of the age of infinitely connected music,” the data alchemist announced from beneath the Space Needle. Glenn McDonald had chosen his title himself, preferring “alchemy,” with its esoteric associations, over the now-ordinary “data science.” His job, as he described it from the stage, was “to use math and typing and computers to help people understand and discover music.”
McDonald practiced his alchemy for the music streaming service Spotify, where he worked to transmute the base stuff of big data — logs of listener interactions, bits of digital audio files, and whatever else he could get his hands on — into valuable gold: products that might attract and retain paying customers. The mysterious power of McDonald’s alchemy lay in the way that ordinary data, if processed correctly, appeared to transform from thin interactional traces into thick cultural significance.
It was 2014, and McDonald was presenting at the Pop Conference, an annual gathering of music critics and academics held in a crumpled, Frank Gehry–designed heap of a building in the center of Seattle. I was on the other side of the country, and I followed along online. That year, the conference’s theme was “Music and Mobility,” and Mc Donald started his talk by narrating his personal musical journey, playing samples as he went. “When I was a kid,” he began, “you discovered music by holding still and waiting.” As a child at home, he listened to the folk music his parents played on the stereo. But as he grew up, his listening expanded: the car radio offered heavy metal and new wave; the internet revealed a world of new and obscure genres to explore. Where once he had been stuck in place, a passive observer of music that happened to go by, he would eventually measure the progress of his life by his ever broadening musical horizons. McDonald had managed to turn this passion into a profession, working to help others explore what he called “the world of music,” which on-demand streaming services had made more accessible than ever before.
Elsewhere, McDonald (2013) would describe the world of music as though it were a landscape: “Follow any path, no matter how unlikely and untrodden it appears, and you’ll find a hidden valley with a hundred bands who’ve lived there for years, reconstructing the music world in methodically- and idiosyncratically-altered miniature, as in Australian hip hop, Hungarian pop, microhouse or Viking metal.”
Travelers through the world of music would find familiarity and surprise — sounds they never would have imagined and songs they adored. McDonald marveled at this new ability to hear music from around the world, from Scotland, Australia, or Malawi. “The perfect music for you may come from the other side of the planet,” he said, but this was not a problem: “in music, we have the teleporter.” On-demand streaming provided a kind of musical mobility, which allowed listeners to travel across the world of music instantaneously.
However, he suggested, repeating the common refrain, the scale of this world could be overwhelming and hard to navigate. “For this new world to actually be appreciable,” McDonald said, “we have to find ways to map this space and then build machines to take you through it along interesting paths.” The recommender systems offered by companies like Spotify were the machines. McDonald’s recent work had focused on the maps, or as he described them in another talk: a “kind of thin layer of vaguely intelligible order over the writhing, surging, insatiably expanding information-space-beast of all the world’s music.”
Although his language may have been unusually poetic, McDonald was expressing an understanding of musical variety that is widely shared among the makers of music recommendation: Music exists in a kind of space. That space is, in one sense, fairly ordinary — like a landscape that you might walk through, encountering new things as you go. But in another sense, this space is deeply weird: behind the valleys and hills, there is a writhing, surging beast, constantly growing and tying points in the space together, infinitely connected. The music space can seem as natural as the mountains visible from the top of the Space Needle; but it can also seem like the man-made topological jumble at its base. It is organic and intuitive; it is technological and chaotic.
Spatial metaphors provide a dominant language for thinking about differences among the makers of music recommendation, as they do in machine learning and among Euro-American cultures more generally. Within these contexts, it is easy to imagine certain, similar things as gathered over here, while other, different things cluster over there. In conversations with engineers, it is very common to find the music space summoned into existence through gestures, which envelop the speakers in an imaginary environment populated by brief pinches in the air and organized by waves of the hand. One genre is on your left, another on your right. On whiteboards and windows scattered around the office, you might find the music space rendered in two dimensions, containing an array of points that cluster and spread across the plane.
In the music space, music that is similar is nearby. If you find yourself within such a space, you should be surrounded by music that you like. To find more of it, you need only to look around you and move. In the music space, genres are like regions, playlists are like pathways, and tastes are like drifting, archipelagic territories. Your new favorite song may lie just over the horizon.
But despite their familiarity, spaces like these are strange: similarities can be found anywhere, and points that seemed far apart might suddenly become adjacent. If you ask, you will learn that all of these spatial representations are mere reductions of something much more complex, of a space comprising not two or three dimensions but potentially thousands of them. This is McDonald’s information-space-beast, a mathematical abstraction that stretches human spatial intuitions past their breaking point.
Spaces like these, generically called “similarity spaces,” are the symbolic terrain on which most machine learning works. To classify data points or recommend items, machine-learning systems typically locate them in spaces, gather them into clusters, measure distances among them, and draw boundaries between them. Machine learning, as the cultural theorist Adrian Mackenzie (2017, 63) has argued, “renders all differences as distances and directions of movement.” So while the music space is in one sense an informal metaphor (the landscape of musical variation) in another sense it is a highly technical formal object (the mathematical substrate of algorithmic recommendation).
Spatial understandings of data travel through technical infrastructures and everyday conversation; they are at once a form of metaphorical expression and a concrete computational practice. In other words, “space” here is both a formalism — a restricted, technical concept that facilitates precision through abstraction — and what the anthropologist Stefan Helmreich (2016, 468) calls an informalism — a less disciplined metaphor that travels alongside formal techniques. In practice, it is often hard or impossible to separate technical specificity from its metaphorical accompaniment. When the makers of music recommendation speak of space, they speak at once figuratively and technically.
For many critics, this “geometric rationality” (Blanke 2018) of machine learning makes it anathema to “culture” per se: it quantifies qualities, rationalizes passions, and plucks cultural objects from their everyday social contexts to relocate them in the sterile isolation of a computational grid. Mainstream cultural anthropology, for instance, has long defined itself in opposition to formalisms like these, which seem to lack the thickness, sensitivity, or adequacy to lived experience that we seek through ethnography. As the political theorists Louise Amoore and Volha Piotukh (2015, 361) suggest, such analytics “reduce heterogeneous forms of life and data to homogeneous spaces of calculation.”
To use the geographer Henri Lefebvre’s (1992) terms, similarity spaces are clear examples of “abstract space” — a kind of representational space in which everything is measurable and quantified, controlled by central authorities in the service of capital. The media theorist Robert Prey (2015, 16), applying Lefebvre’s framework to streaming music, suggests that people like McDonald — “data analysts, programmers and engineers” — are primarily concerned with the abstract, conceived space of calculation and measurement. Conceived space, in Lefebvrian thought, is parasitic on social, lived space, which Prey associates with the listeners who resist and reinterpret the work of technologists. The spread of abstract space under capitalism portends, in this framework, “the devastating conquest of the lived by the conceived” (Wilson 2013).
But for the people who work with it, the music space does not feel like a sterile grid, even at its most mathematical. The makers of music recommendation do not limit themselves to the refined abstractions of conceived space. Over the course of their training, they learn to experience the music space as ordinary and inhabitable, despite its underlying strangeness. The music space is as intuitive as a landscape to be walked across and as alien as a complex, highly dimensional object of engineering. To use an often- problematized distinction from cultural geography, they treat “space” like “place,” as though the abstract, homogeneous grid were a kind of livable local environment.
Similarity spaces are the result of many decisions; they are by no means ``natural,” and people like McDonald are aware that the choices they make can profoundly rearrange them. Yet spatial metaphorizing, moving across speech, gesture, illustration, and computation, helps make the patterns in cultural data feel real. A confusion between maps and territories— between malleable representations and objective terrains— is productive for people who are at once interested in creating objective knowledge and concerned with accounting for their own subjective influence on the process. These spatial understandings alter the meaning of musical concepts like genre or social phenomena like taste, rendering them as forms of clustering.
Everything was going great until it wasn't in the skies over Cornwall, UK on Monday. Virgin Orbit, the space launch division of Sir Richard Branson's sprawling commercial empire, was in the midst of setting a major milestone for the country and the nation: to be the first orbital launch from European soil. The carrier aircraft, Cosmic Girl, had successfully taken off from Spaceport Cornwall, LauncherOne had cleanly separated from the modified 747 and properly ignited its first stage rocket, blasting it and its payload of satellites into space. But before they could be pushed into their proper orbit by the rocket's second stage, something went wrong. On Thursday, Virgin Orbit leaders provided a preliminary explanation as to just what happened.
"At an altitude of approximately 180 km, the upper stage experienced an anomaly. This anomaly prematurely ended the first burn of the upper stage," the company told Engadget via email. "This event ended the mission, with the rocket components and payload falling back to Earth within the approved safety corridor without ever achieving orbit."
Virgin Orbit has also announced a "formal" investigation into the root causes of the anomaly which will be led by Jim Sponnick, who developed the Atlas and Delta launch systems, and Chad Foerster, Virgin Orbit's Chief Engineer. Despite the setback, the company is already in contact with UK officials to reschedule the launch for as soon as late 2023.
With the rapid evolution of AI chatbot systems like Chat-GPT, VALL-E, and BlenderBot 3 and their growing abilities to generate text on par with human writers, robots coming to take your writing job is becoming a viable threat. Over at CNET, it's apparently already happening.
On Wednesday, The Byte reported that the popular tech site appears to have employed "automation technology" to produce a series of financial explainer posts beginning in November 2022 under the byline of CNET Money Staff. It is only after clicking the byline that the site reveals that "This article was generated using automation technology and thoroughly edited and fact-checked by an editor on our editorial staff."
Looks like @CNET (DR 92 tech site) just did their coming out about using AI content for SEO articles. pic.twitter.com/CR0IkgUUnq
Online marketer Gael Breton first flagged the content Wednesday on Twitter. In all, the tech site produced 73 such posts since last November on subjects such as "Should You Break an Early CD for a Better Rate?" or "What is Zelle and How Does It Work?" Since news of its activities broke at the start of the day, CNET has subsequently taken down the CNET Money Staff bio page as well as removed the "Staff" from numerous posts it had written.
Using text generators isn't currently a widespread practice throughout the journalistic sphere but outlets like the Associated Press and Washington Post have used them for various low-level copywriting tasks — the latter employing them to write about high school football and the equally unimportant 2016 Rio Olympics. But normally when an outlet makes a fundamental shift to the operations of its newsroom such as this, they typically send out a press release or make an announcement on social, anything. It does not appear that CNET has made any sort public note that this program exists beyond the dropdown explainer window.
The quality difference between CNET's system and the AP's is a stark one. The AP system is a glorified mail merge, shoving specific pieces of data into preformatted story blanks for daily blotter posts and other highly repetitive journalistic tasks. CNET's system, on the other hand, appears to be far more capable, able to compose feature length explainer posts on complex financial concepts — a far cry from the journalistic Mad Libs the AP engages in. We've reached out to CNET for comment and will update the post when the company responds.
