Design startup InVision, once valued at $2 billion, is shutting down at the end of this year, according to a company blog post Thursday. The business had raised more than $350 million from investors including Goldman Sachs and Spark Capital. From a report: Once a market leader in collaborative design software, InVision's business spiraled after rival firm Figma's product surged in popularity, snatching away its customers, The Information previously reported. InVision's revenue fell by half to $50 million in 2022, pushing it to sell its core business line to Miro, a competitor building digital whiteboards last fall.

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A cartel in the embattled central Mexico state of Michoacan set up its own makeshift internet antennas and told locals they had to pay to use its wifi service or they would be killed, according to prosecutors. New submitter awwshit shares a story: Dubbed "narco-antennas" by local media, the cartel's system involved internet antennas set up in various towns built with stolen equipment. The group charged approximately 5,000 people elevated prices between 400 and 500 pesos ($25 and $30) a month, the Michoacan state prosecutor's office told the Associated Press. That meant the group could rake in about $150,000 a month. People were terrorized "to contract the internet services at excessive costs, under the claim that they would be killed if they did not," prosecutors said, though they did not report any such deaths. Local media identified the criminal group as a faction known as Los Viagras. Prosecutors declined to say which cartel was involved because the case was still under investigation, but they confirmed Los Viagras dominates the towns forced to make the wifi payments.

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An anonymous reader quotes a report from The Verge: Using satellite imagery and AI, researchers have mapped human activity at sea with more precision than ever before. The effort exposed a huge amount of industrial activity that previously flew under the radar, from suspicious fishing operations to an explosion of offshore energy development. The maps were published today in the journal Nature. The research led by Google-backed nonprofit Global Fishing Watch revealed that a whopping three-quarters of the world's industrial fishing vessels are not publicly tracked. Up to 30 percent of transport and energy vessels also escape public tracking. Those blind spots could hamper global conservation efforts, the researchers say. To better protect the world's oceans and fisheries, policymakers need a more accurate picture of where people are exploiting resources at sea. Until now, Global Fishing Watch and other organizations relied primarily on the maritime Automatic Identification System (AIS) to see what was happening at sea. The system tracks vessels that carry a box that sends out radio signals, and the data has been used in the past to document overfishing and forced labor on vessels. Even so, there are major limitations with the system. Requirements to carry AIS vary by country and vessel type. And it's pretty easy for someone to turn the box off when they want to avoid detection, or cruise through locations where signal strength is spotty. To fill in the blanks, Kroodsma and his colleagues analyzed 2,000 terabytes of imagery from the European Space Agency's Sentinel-1 satellite constellation. Instead of taking traditional optical imagery, which is like snapping photos with a camera, Sentinel-1 uses advanced radar instruments to observe the surface of the Earth. Radar can penetrate clouds and "see" in the dark -- and it was able to spot offshore activity that AIS missed. Since 2,000 terabytes is an enormous amount of data to crunch, the researchers developed three deep-learning models to classify each detected vessel, estimate their size, and sort out different kinds of offshore infrastructure. They monitored some 15 percent of the world's oceans where 75 percent of industrial activity takes place, paying attention to both vessel movements and the development of stationary offshore structures like oil rigs and wind turbines between 2017 and 2021. While fishing activity dipped at the onset of the covid-19 pandemic in 2020, they found dense vessel traffic in areas that "previously showed little to no vessel activity" in public tracking systems -- particularly around South and Southeast Asia, and the northern and western coasts of Africa. A boom in offshore energy development was also visible in the data. Wind turbines outnumbered oil structures by the end of 2020. Turbines made up 48 percent of all ocean infrastructure by the following year, while oil structures accounted for 38 percent. Nearly all of the offshore wind development took place off the coasts of northern Europe and China. In the Northeast US, clean energy opponents have tried to falsely link whale deaths to upcoming offshore wind development even though evidence points to vessel strikes being the problem. Oil structures have a lot more vessels swarming around them than wind turbines. Tank vessels are used at times to transport oil to shore as an alternative to pipelines. The number of oil structures grew 16 percent over the five years studied. And offshore oil development was linked to five times as much vessel traffic globally as wind turbines in 2021. "The actual amount of vessel traffic globally from wind turbines is tiny, compared to the rest of traffic," Kroodsma says.

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NASA's Juno spacecraft made its closest flyby yet of Io, one of Jupiter's largest moons, sending back images of "sharp cliffs, edgy mountain peaks, lakes of pooled lava and even a volcanic plume," reports the New York Times. From the report: The Juno spacecraft, designed to study the origin and evolution of Jupiter, arrived at the planet in 2016. NASA extended the mission in 2021, and the orbiter has since captured photos of the Jovian moons Ganymede, Europa and most recently Io. [...] Juno conducted a number of more distant observations of Io in recent years. Its latest flyby occurred on Dec. 30, when the spacecraft came within 932 miles of the moon. The images captured during this visit were made with an instrument called JunoCam and are in visible wavelengths. They are some of the highest resolution views of Io's global structure. The mission's managers shared six images of Io on the mission's website, and members of the public have since uploaded digitally enhanced versions that highlight features on Io's surface. Mission scientists are already at work analyzing these images, searching for differences across Io's surface to learn how often its volcanoes erupt, how bright and hot those eruptions are and how the resulting lava flows. According to Dr. Bolton, the team will also compare Juno's images to older views of the Jovian moon to determine what has changed on Io over a variety of encounters. And they'll get a second set of data to work with in a month, when Juno completes another close flyby of the explosive world on Feb. 3.

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Programmer James Lambert has been working on a demake of Valve's Portal puzzle game for the Nintendo N64. After several years of development, Portal 64: The First Slice is now out of beta with two-thirds of the game's test chambers available to play. PC Gamer reports: In the announcement video Lambert goes through some of the new features in the latest build, including a seriously impressive visual rework on the portal gun itself. The video also showcases just how much of Portal's feel this manages to successfully capture, in particular the mind-bending effects of observing rooms and Chell through the portals themselves. I once called this the most impressive homebrew game I've ever seen and, while admittedly the N64 nostalgia helps, I'd stick by that. While this is obviously the first slice (geddit) and there's more to come, it's an incredible achievement in its own right: The first 13 test chambers of the game all present-and-correct. Portal has 19 test chambers, and Portal: Still Alive (which unbelievably has never seen an official PC release) added a further 14, so Lambert's well on his way to completing a vanilla version of Portal 64. You can follow the Portal 64 project on YouTube and download the game here.

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An anonymous reader quotes a report from Interesting Engineering: Marking a significant advancement in medical science, the world's first partial heart transplant has achieved the expected outcome after over a year of research efforts. Carried out by Duke Health, the patient, a young individual, now exhibits functioning valves and arteries that are growing in tandem with the transplant, as initially expected by the medical team. In spring 2022, doctors carried out the procedure on a baby who needed a new heart valve. Before, they used non-living valves, which didn't grow with the child. This meant the child needed frequent replacements, and the surgeries had a 50 percent chance of being deadly. The new procedure avoids these problems, according to the team. Babies with serious heart valve problems face a tough challenge because there aren't any implants that can grow with them. So, these babies end up needing new implants over and over until they're big enough for an adult-sized valve. It's a problem that doesn't have a solution yet. Duke Health doctors, leading a study published in the Journal of the American Medical Association, discovered that the innovative valve collection method used in the partial heart transplant resulted in two properly functioning valves and arteries that are growing along with the child, resembling natural blood vessels. "This publication is proof that this technology works, this idea works, and can be used to help other children," said Joseph W. Turek, first author of the study and Duke's chief of pediatric cardiac surgery, in a statement. The research also notes that the new procedure requires less immunosuppressant medication, reducing potential long-term side effects. It also facilitates a "domino transplant" method, where one donor heart benefits multiple patients, potentially doubling the number of hearts available for children with heart disease by utilizing previously unused hearts and valves.

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Generative AI models like Google Bard and GitHub Copilot are increasingly being used in various industries, but users often overlook their limitations, leading to serious errors and inefficiencies. Daniel Stenberg of curl and libcurl highlights a specific problem of AI-generated security reports: when reports are made to look better and to appear to have a point, it takes a longer time to research and eventually discard it. "Every security report has to have a human spend time to look at it and assess what it means," adds Stenberg. "The better the crap, the longer time and the more energy we have to spend on the report until we close it." The Register reports: The curl project offers a bug bounty to security researchers who find and report legitimate vulnerabilities. According to Stenberg, the program has paid out over $70,000 in rewards to date. Of 415 vulnerability reports received, 64 have been confirmed as security flaws and 77 have been deemed informative -- bugs without obvious security implications. So about 66 percent of the reports have been invalid. The issue for Stenberg is that these reports still need to be investigated and that takes developer time. And while those submitting bug reports have begun using AI tools to accelerate the process of finding supposed bugs and writing up reports, those reviewing bug reports still rely on human review. The result of this asymmetry is more plausible-sounding reports, because chatbot models can produce detailed, readable text without regard to accuracy. As Stenberg puts it, AI produces better crap. "A crap report does not help the project at all. It instead takes away developer time and energy from something productive. Partly because security work is considered one of the most important areas so it tends to trump almost everything else." As examples, he cites two reports submitted to HackerOne, a vulnerability reporting community. One claimed to describe Curl CVE-2023-38545 prior to actual disclosure. But Stenberg had to post to the forum to make clear that the bug report was bogus. He said that the report, produced with the help of Google Bard, "reeks of typical AI style hallucinations: it mixes and matches facts and details from old security issues, creating and making up something new that has no connection with reality." [...] Stenberg readily acknowledges that AI assistance can be genuinely helpful. But he argues that having a human in the loop makes the use and outcome of AI tools much better. Even so, he expects the ease and utility of these tools, coupled with the financial incentive of bug bounties, will lead to more shoddy LLM-generated security reports, to the detriment of those on the receiving end.

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Qualcomm today unveiled a new Snapdragon XR2+ Gen 2 chipset, a single-chip architecture that will likely power Apple Vision Pro competitors from Meta, Samsung, Google and HTC, among others. ZDNet reports: Succeeding last year's XR2 Gen 2, the plus variant brings improved GPU and CPU frequency -- up 15% and 20% respectively, support for 4.3K per eye resolution at 90fps, and the ability for headsets to field 12 or more cameras with on-device AI capabilities. The latter allows equipped models to better track user movements and surrounding objects for more immersive (and harmonious) VR and MR experiences. As for efficiency gains, you'll still be getting the 50% improvement as the previous XR2 Gen 2 when stacked against the XR2 Gen 1 platform. Basically, there's no change on that front. "(Snapdragon XR2+ Gen 2) will take XR productivity and entertainment to the next level by bringing spectacularly clear visuals to use cases such as room-scale screens, life-size overlays and virtual desktops," said Hugo Swart, vice president and general manager of XR, Qualcomm Technologies, Inc, in a Thursday press release. Clearly, the new silicon is aimed at headsets that can do it all -- with feature parity to the $3,500 gorilla in the room, Apple's upcoming Vision Pro headset -- though Qualcomm says it'll be priced accessibly for manufacturers to build hardware around. How affordable will these competing wearables be? Your guess is as good as mine. But considering we've already gotten products like the $500 Meta Quest 3 fielding the slightly less capable XR2 Gen 2 chip, the future of XR may not be as expensive as it seems. The new Snapdragon XR2+ Gen 2 chipset is made in collaboration with Google and Samsung, both of which bring expertise in the Android ecosystem and developing mobile VR devices. The trio had announced plans to develop an XR platform back in February of 2023, likely in reaction to the then-rumored headset by Apple.

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According to MoffettNathanson, the U.S. pay-TV industry had its worst-ever third quarter after losing about 900,000 subscribers. "That poor result, the research firm added, left the total pay-TV industry shrinking at a record pace of -7.3%, widened from a year-ago decline of -5.9%," reports Light Reading. "It also left pay-TV penetration of occupied households (including vMVPDs) at just 54.8% -- a level last seen in 1989, five years before the debut of DirecTV." From the report: Drilling down on Q3 results, traditional pay-TV providers (cable, telco and satellite) shed 1.97 million subscribers, widened from a loss of 1.94 million in the year-ago quarter. Within that category, US cable lost 1.10 million video subs in Q3, versus a loss of -1.09 million in the year-ago period. Satellite operators (Dish Network and DirecTV) lost 667,000 subs in Q3, versus -567,000 in the year-ago quarter. Telco TV providers lost 198,000 video subs in the period, an improvement when compared to a year-ago loss of -250,000 subs. vMVPDs, meanwhile, added 1.08 million in Q3, down from a year-ago gain of about 1.34 million. Despite those gains, vMVPDs recaptured only 21.7% of traditional pay-TV's subscriber losses in the period, according to MoffettNathanson. Meanwhile, YouTube TV continues to dominate the vMVPD category. MoffettNathanson estimates that YouTube TV added about 350,000 subs in Q3, extending its total to 7 million -- representing 40% of the vMVPD sector's 18 million subscriber total. "Based on our Q3 estimate, YouTube TV has now surpassed Dish Network [6.72 million satellite TV subs at the end of Q3] to become the country's fourth largest MVPD of any kind," Moffett noted. "At the current trajectory, YouTube TV should pass DirecTV for third place in less than a year."

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An anonymous reader quotes a report from Ars Technica: ChatGPT is still no House, MD. While the chatty AI bot has previously underwhelmed with its attempts to diagnose challenging medical cases -- with an accuracy rate of 39 percent in an analysis last year -- a study out this week in JAMA Pediatrics suggests the fourth version of the large language model is especially bad with kids. It had an accuracy rate of just 17 percent when diagnosing pediatric medical cases. The low success rate suggests human pediatricians won't be out of jobs any time soon, in case that was a concern. As the authors put it: "[T]his study underscores the invaluable role that clinical experience holds." But it also identifies the critical weaknesses that led to ChatGPT's high error rate and ways to transform it into a useful tool in clinical care. With so much interest and experimentation with AI chatbots, many pediatricians and other doctors see their integration into clinical care as inevitable. [...] For ChatGPT's test, the researchers pasted the relevant text of the medical cases into the prompt, and then two qualified physician-researchers scored the AI-generated answers as correct, incorrect, or "did not fully capture the diagnosis." In the latter case, ChatGPT came up with a clinically related condition that was too broad or unspecific to be considered the correct diagnosis. For instance, ChatGPT diagnosed one child's case as caused by a branchial cleft cyst -- a lump in the neck or below the collarbone -- when the correct diagnosis was Branchio-oto-renal syndrome, a genetic condition that causes the abnormal development of tissue in the neck, and malformations in the ears and kidneys. One of the signs of the condition is the formation of branchial cleft cysts. Overall, ChatGPT got the right answer in just 17 of the 100 cases. It was plainly wrong in 72 cases, and did not fully capture the diagnosis of the remaining 11 cases. Among the 83 wrong diagnoses, 47 (57 percent) were in the same organ system. Among the failures, researchers noted that ChatGPT appeared to struggle with spotting known relationships between conditions that an experienced physician would hopefully pick up on. For example, it didn't make the connection between autism and scurvy (Vitamin C deficiency) in one medical case. Neuropsychiatric conditions, such as autism, can lead to restricted diets, and that in turn can lead to vitamin deficiencies. As such, neuropsychiatric conditions are notable risk factors for the development of vitamin deficiencies in kids living in high-income countries, and clinicians should be on the lookout for them. ChatGPT, meanwhile, came up with the diagnosis of a rare autoimmune condition. Though the chatbot struggled in this test, the researchers suggest it could improve by being specifically and selectively trained on accurate and trustworthy medical literature -- not stuff on the Internet, which can include inaccurate information and misinformation. They also suggest chatbots could improve with more real-time access to medical data, allowing the models to refine their accuracy, described as "tuning."

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As spotted by X user bedros_p, Google appears to be preparing to introduce a paid upgrade for Bard Advanced, a "new, cutting-edge AI experience" announced in December that gives users access to Google's best models and capabilities. Android Police reports: According to the strings, you will be able to "Try Bard Advanced for 3 months, on us." After that test period, you will likely have to pay up for the service. A defunct link within the code suggests that it may be part of Google One, but it's not clear if Bard Advanced will be added to all tiers or only more expensive ones with more Google Drive storage. It's also possible that it will be an extra new tier in Google One. As a refresher, Google launched its most capable AI model yet in December 2023, called Gemini. The LLM is available in three tiers, including a Nano version capable of running on devices like phones and a Pro version currently powering Bard in the US. There is also a Gemini Ultra which isn't public just yet, but supposedly outperforms other LLMs in almost all metrics. Google says that this is the one that will power Bard Advanced.

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