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"A Taiwanese American model says a well-known fashion designer uploaded a digitally altered runway photo that made her appear white. In a TikTok about the incident that has been viewed 1.8m times in the last week, Shereen Wu says Michael Costello, a designer who has worked with Beyoncé, Jennifer Lopez, and Celine Dion, posted a photo to his Instagram from a recent Los Angeles fashion show. The photo depicts Wu in the slinky black ballgown that she walked the runway in - but her face has been changed, made to appear as if she is a white woman."

"But in internet time 2009 was aeons ago. Now, intensive surveillance is available to anyone. And you don't have to be a tech wizard to do it. In mid-January this year, Kashmir Hill, a talented American tech reporter, used three bits of everyday consumer electronics - Apple AirTags, Tiles and a GPS tracker - to track her husband's every move. He agreed to this in principle, but didn't realise just how many devices she had planted on him. He found only two of the trackers: a Tile he felt in the breast pocket of his coat and an AirTag in his backpack when he was looking for something else. "It is impossible to find a device that makes no noise and gives no warning," he said when she showed him the ones he missed."

"Kellin Pelrine, an American player who is one level below the top amateur ranking, beat the machine by taking advantage of a previously unknown flaw that had been identified by another computer. But the head-to-head confrontation in which he won 14 of 15 games was undertaken without direct computer support. The triumph, which has not previously been reported, highlighted a weakness in the best Go computer programs that is shared by most of today's widely used AI systems, including the ChatGPT chatbot created by San Francisco-based OpenAI. The tactics that put a human back on top on the Go board were suggested by a computer program that had probed the AI systems looking for weaknesses. The suggested plan was then ruthlessly delivered by Pelrine."

"First, the authors expect that 80% of the US workforce could see at least 10% of their tasks affected by GPT. In other words, most Americans could benefit at least a bit from these LLMs."

SAN FRANCISCO - New York State's top prosecutor is investigating why American cellphone carriers have yet to embrace antitheft software on Samsung smartphones, raising questions about possible coordination among the biggest carriers.

"Researchers are becoming so adept at mining information from genealogical, medical and police genetic databases that it is becoming difficult to protect anyone's privacy-even those who have never submitted their DNA for analysis."

Sounds a bit extreme just to make sure no one can log on to your laptop or smartphone, but a team of researchers from Stanford and Northwestern universities as well as SRI International is nonetheless experimenting at the computer-, cognitive- and neuroscience intersection to combat identity theft and shore up cyber security-by taking advantage of the human brain's innate abilities to learn and recognize patterns.

"What the apps have done, instead of competing to serve customers and restaurants, is use Wall Street money to accumulate market power, raise barriers to entry, and then merge with each other and set up regional monopolies.The people who have invested tens of billions of dollars in the four dominant delivery apps tolerate huge short-term losses purely because they see the likelihood of monopoly power"

"It may be coincidence that Trump's threat in August to shut down TikTok in the U.S. unless a sale was tendered with an American company drove the app into the arms of one of his allies."

"Creating an algorithm that discriminates or shows bias isn't as hard as it might seem, however. As a first-year graduate student, my advisor asked me to create a machine-learning algorithm to analyze a survey sent to United States physics instructors about teaching computer programming in their courses."

"Our Economy Was Just Blasted Years Into the Future The crisis is compressing and accelerating trends that would have taken decades to play out"

"New research by scientists at Michigan State University suggests that laptops do not enhance classroom learning, and in fact students would be better off leaving their laptops in the dorm during class. Although computer use during class may create the illusion of enhanced engagement with course content, it more often reflects engagement with social media, YouTube videos, instant messaging, and other nonacademic content. This self-inflicted distraction comes at a cost, as students are spending up to one-third of valuable (and costly) class time zoned out, and the longer they are online the more their grades tend to suffer."

"Most AI programs function like a "black box." "We know exactly what a model does but not why it has now specifically recognized that a picture shows a cat," said computer scientist Kristian Kersting of the Technical University of Darmstadt in Germany to the German-language newspaper Handelsblatt. That dilemma prompted Kersting-along with computer scientists Patrick Schramowski of the Technical University of Darmstadt and Björn Deiseroth, Mayukh Deb and Samuel Weinbach, all at the Heidelberg, Germany-based AI company Aleph Alpha-to introduce an algorithm called AtMan earlier this year. AtMan allows large AI systems such as ChatGPT, Dall-E and Midjourney to finally explain their outputs."

"Now researchers have taken a step forward by combining fMRI's ability to monitor neural activity with the predictive power of artificial intelligence language models. The hybrid technology has resulted in a decoder that can reproduce, with a surprising level of accuracy, the stories that a person listened to or imagined telling in the scanner. The decoder could even guess the story behind a short film that someone watched in the scanner, though with less accuracy."

"But it also raises uncomfortable questions: is AI technology helping marginalized people overcome bias, or just perpetuating the biases that make their lives hard in the first place?"

This discrepancy has made it relatively easy to connect an anonymous line of data to a specific person: if a private detective is searching for someone in New York City and knows the subject is male, is 30 to 35 years old and has diabetes, the sleuth would not be able to deduce the man's name-but could likely do so quite easily if he or she also knows the target's birthday, number of children, zip code, employer and car model.