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Massive walls of dust and debris called haboobs that roll through the U.S. Southwest can be awe-inspiring and terrifying, especially for motorists caught in their path.Thunderstorms spawn the phenomenon and can create a wall of dust thousands of feet tall and several miles wide, reaching speeds of 60 mph (97 kph) or more.Here’s what to know. How do haboobs form? Thunderstorms can produce strong downdrafts that hit the ground at 50 to 80 mph (80 to 129 kph) and then spread in all directions, said Sean Benedict, a meteorologist at the National Weather Service’s Phoenix office.The winds stir up loose dust and dirt, including from arid areas and farm fields, that get blown along in front of the approaching storm cell.If thunderstorms don’t keep developing, the dust dissipates. But rain-cooled air in front of a storm can keep pushing warm air upward, generating new storms and more downdrafts, Benedict said.When that happens, the haboob can keep growing, and some travel as far as 100 miles (161 kilometers), he said.“It’s all dependent on whether they’re moving through an area that’s prone to [generating] dust,” said Benedict, noting that there’s a prominent dust corridor between Phoenix and Tucson.Haboobs also can form in arid areas of Nevada, New Mexico, and Texas. It’s unclear whether haboobs will become more frequent Scientists say localized bursts of rain in the U.S. Southwest during the monsoon season in summer have become more intense since the 1970s as the atmosphere heats up due to human-caused climate change.At the same time, it’s raining less often as droughts last longer and some arid areas expand. Climate change increases the odds of both severe drought and heavier storms that could set the stage for more intense dust storms in the future.Benedict said it’s difficult to say whether haboobs will become more frequent. The storms require a specific set of circumstances, and land use, such as farming, can affect how much dust gets picked up, he said.Not all dust storms are haboobs, which are specifically associated with downdrafts from thunderstorms.The National Oceanic and Atmospheric Administration says the Phoenix area experiences one to three large dust storms a year. How to stay safe The National Weather Service issues dust warnings if it anticipates that thunderstorms and high winds moving through dust-prone areas could reduce visibility to a quarter mile or less. That’s especially important when conditions are favorable for clusters of storms, Benedict said.Haboobs can form quickly, catching drivers by surprise, blotting out the sun, and reducing visibility to zero. Experts recommend that motorists pull off the roadways as far as possible, stop their vehicles, and turn off their lights.“People on the roads, when they can’t see anything, they’re just gonna try to follow those taillights in front of them,” and run into parked cars, Benedict said. “If there is an accident, you might not know, and you just get these big pileups. So it’s definitely very dangerous when the visibility drops down that low.” The Associated Press’s climate and environmental coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP’s standards for working with philanthropies, a list of supporters, and funded coverage areas at AP.org. By Tammy Webber, Associated Press
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E-Commerce
How many apps do you use to chat with other people? I dont mean tweeting out into the ether. I mean actually interacting with a fellow human in a one-to-one way. For most people, the number is one or two. And it’s probably fewer than five. In the U.S., you likely keep in touch with friends and family through Apple or Google Messages, and touch base with colleagues on Slack or Teams. (For Europeans, that’s texting via WhatsApp.) If youre a particularly rabid Swiftie, you might also have a raucous group chat through X or Instagram DMs; if youre a gamer, you keep up with people on Discord. But for all the time we hopscotch across apps like TikTok, YouTube, Snapchat, and Instagram to consume content, the number of platforms we actually use to interact with others remains minimal. So whats the point of Spotifys new direct messaging feature, unveiled this week and rolling out to select markets? The feature allows users to click a “Share” button while listening to a song, podcast, or audiobook and instantly start a conversation with a friend, seeded with a link to whatever theyre listening to. Why nobody wants a do-it-all app In the press release announcing the feature, the music streaming giant promises that “Messages are for the conversations youre already having about music, podcasts and audiobooks with your friends and family.” But the flaw is right there in the pitch: if youre already having those conversations on WhatsApp or iMessage, why would you uproot them into a side-channel inside Spotify? At best it duplicates whats happening elsewhere, and at worst it fractures the conversation into yet another notification stream. (Fortunately, users can turn off the function, too.) Besides the fact that friends who insist on foisting their musical tastes on you are often the most infuriating, the feature looks destined to join the long list of rarely used, half-baked add-ons app makers tack onto their products. (Fast Company has reached out to Spotify for comment.) Spotifys move highlights how wayward app makers decision-making has become, and how easily feature bloat clutters our smartphones. On paper, adding DMs to Spotify makes sense, just as adding AI autosuggestions does for LinkedIn, or layering shortform video onto YouTube does for Googles video platform. The goal is to become an everything appthink of a more modest version of Chinas WeChatthat secures a permanent slot on your home screen. The problem: That never actually happens. Attempts to provide everything to everybody end up providing nothing to anyone, and the app inevitably flops. And flop, this one will. With the exception of YouTube Shortswhich simply extended YouTubes core video offering with another formatmost attempts to ride the zeitgeist are shallow grabs at relevance. The best features, in the best apps, are developed with deep thought about how to benefit users. About that Q2 earnings report Spotify is just the latest entrant in the copycat race, a space where Big Tech borrows whats proven popular in smaller apps. Meta has been one of the most aggressive, and its results hardly inspire confidence. Crowbarring one apps feature into another rarely works. Take Spotify: Its user-loop involves search, pressing play, listening, maybe saving, maybe sharing. Messaging apps, meanwhile, follow a loop of open thread, type, send, await reply. Those loops are fundamentally different. Smush them together and you create friction in both. Do I really want to share that Im listening to the same song for the billionth time? Theres also the matter of network effects. Messaging is winner-take-most because your friends, not you, determine the platform. Thats why people tolerate green bubbles versus blue, or hop between WhatsApp and iMessage depending on the conversation. A new chat feature inside a vertical app fragments your attentionand worse, your conversation. The song you send in Spotify DMs is now marooned from the rest of your life in WhatsApp or iMessage. It creates context silos for no good reason. If an app genuinely wants to be an everything app, it needs a foundation deeper than FOMOwhich seems to be Spotifys rationale here. WeChats everything-ness is anchored in identity, payments, and ubiquity, all under unique market conditions. Silicon Valleys obsession with replicating it is misguided. Every app except WeChat that tries to become an everything app ends up as an anything appa junk drawer of half-ideas. Spotifys new feature feels like more clutter, more cruft, dumped onto an already junk-filled smartphone notification screen. A cynic might say the new messaging feature amounts to a ploy to distract from Spotifys latest earnings miss: a swing to a second quarter $100 million loss despite topping forecasts on subscribers and revenue. The mismatchusers growing, but profits shrinkingunderscores why the company keeps reaching for engagement gimmicks. If it cant squeeze more money out of music, maybe, the thinking goes, it can invent new ways to keep you glued to the app. But yet another inbox on our phones wont make Spotify more essential. It’s just more noise.
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E-Commerce
Have you ever read an article or social post and thought, This is terrible! I bet it was written by AI!? Most people know bad AI writing when they see it. But unless youre a closeted copy editor, its surprisingly hard to put your finger on exactly why AI writing sucks. Now, Wikipedias editor team has just released what amounts to a master class in the clichés, strange tropes, obsequious tones of voice, and other assorted oddities of AI-generated prose. Its a list called Signs of AI Writing, and its a fantastic resource for people who want to get better at spotting AI writingor who want to disguise their own. Add your own slop As one of the internets most trusted sources of information, Wikipedia is uniquely exposed to the risks of LLM-generated content. Large language models love to pontificate on random topics, even when they have very little actual knowledge. Wikipedia covers many of these random topics, from the ash content of Morbier cheese to the gorey details of Justin Biebers love life. Wikipedia famously crowdsources its information through a network of volunteer contributors and editors. This combination of crowdsourced data and highly specific, niche topics is a recipe for the misuse of AI. Theres also an increasingly potent financial incentive for people to pollute Wikipedia with AI slop. As search engines like Google laser in on EEATa tortured acronym that describes the authoritativeness of a brandhaving a Wikipedia page is becoming more valuable to brands as a metric for their legitimacy. Youre not supposed to create or edit your own Wikipedia page, but many brands do. And one of the easiest ways to hide this off-label tinkering is to drown ones nefarious edits in a sea of seemingly unrelated updates and contributions to esoteric Wikipedia pages. AI can spin these up at scale. Everything is fascinating Because of the risks that AI-generated content poses to the site, Wikipedias editors have gotten incredibly good at recognizing AI writing. Their Signs of AI Writing document distills this knowledge into an easy-to-follow guide. Wikipedias list is useful and unique largely because its so specific. Many other rubrics for recognizing AI writing offer broad, generic advice or focus on detection hacks that are easy to bypass. Researchers recently realized, for example, that LLMs tend to overuse the em dasha wonderful and remarkably versatile punctuation mark that I happen to absolutely love. As I recently discussed with Slate, for a brief moment, the presence of an em dash in an article was a good way to detect AI writing. Quickly, though, AI content generators caught on and started to avoid the punctuation mark. Simple hacks for detecting AI writing have a limited shelf life. The arms race of AI content creation and AI content detection means these methods are quickly rendered useless as soon as theyre made public. Wikipedias guidelines go much deeper. Rather than focusing on quick detection hacks, they dig into the more fundamental patterns present in bad AI contentthe writing conventions and literary tropes that LLMs consistently overuse. Wikipedias editors point out, for example, that LLMs place undue emphasis on symbolism and importance. Everything LLMs write stands as a symbol of something, or carries enhanced significance. Natural locations are always captivating, all animals are majestic and everything is diverse and fascinating. Wikipedias editors also note that LLMs tend to overuse transition words and phrases like in summary or overall. Often these show up as negative parallelisms. For example, LLMs love to summarize things theyre already written with tropes like: Its not only but also A restaurant might be described as not only a great place for Italian food, but also a shining example of local entrepreneurship. Every concluding paragraph starts with In conclusion or In summary. The editors also point out that AI writing often overuses the Rule of Three–a handy literary trick that capitalizes on the fact that humans brains love groups of three things. A person might be creative, smart and funny according to ChatGPT, or a company could be innovative, rule-breaking and impactful. Good writing gone bad Interestingly, Wikipedias editors acknowledge that many of these conventions would be considered good writing if they came from a human. Its not that LLMs are inherently bad at writingits just that they write in predictable ways that make their output feel formulaic and robotic. The editors also note that LLMs polished writing style and tendency to follow conventions often serves to obscure their lack of actual knowledge about a topic. By following conventions like the Rule of Three, LLMs make their superficial explanations appear more comprehensive. As readers, we often mistake good form for good contentif an LLM writes with perfect grammar and its content flows beautifully, we might not realize that its not actually saying anything useful or substantive. Beyond these stylistic issues, Wikipedias list goes into extreme detail about technical specifics of AI writingthe ways LLMs consistently format text, use headings, handle punctuation (like curly quotation marks), and sprinkle their content with bolded words and emojs. Spot it (or make it) The guidelines are useful for anyone who edits Wikipedia. But theyre also relevant for anyone who wants to get better at recognizing AI writingor who wants to create their own AI content that doesnt sound machine-generated. If youre reading an article or social media post that feels a bit off and youre curious whether it might be AI-written, Wikipedias guidelines provide a fantastic checklist for validating your suspicions. Compare the suspect writing with Wikipedias list. Do you see the Rule of Three appear a bit too consistently? Are there too many transition words? Does it sound too effusive? Although the editors stress that humans are perfectly capable of generating bland and formulaic writing without an AIs help, spotting these patterns in a piece of writing can lend credence to the idea that it was written by a machine. And if you use LLMs to create content for your businessor even for personal emails or social postsWikipedias list can help you tweak it so its genuinely readable and doesnt sound quite so robotic. As a human editor, you can manually scan the output of ChatGPT, Claude or Gemini for the patterns Wikipedia identifies, and inject your own human touch when the chatbots start sounding a bit too AI. Theres an easier approach, too. Ive found that pasting Wikipedias entire Signs of Writing list into a chatbot as part of your prompt yields noticeably better writing than LLMs produce alone. Spinning up a social post for your bands first mall gig, or generating the landing page copy for your crochet business Square page? Prompt ChatGPT or Claude as you normally would, but tell the chatbot to avoid the items on this list. Then, paste in the full contents of Wikipedias Signs page. Your LLM-generated writing will feel markedly better, with very little effort. Make sure to use your powers for good! With their specificity, focus on stylistic rather than technical patterns, and attention to subtle details of AI writing (see, Rule of Three!), Wikipedias list is a fantastic tool for anyone who wants to spot lazy AI writingor make their own AI content feel a bit less lazy and generic.
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E-Commerce
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