Month: June 2023

Device makers have struggled to incorporate temperature sensors into smartphones and smartwatches to turn them into medically accurate body thermometers, but researchers at the University of Washington claim they’ve come up with a way to turn an off-the-shelf smartphone into exactly that–with nothing but a new app. They’re calling it FeverPhone.

Although smart wearables like the Apple Watch Series 8 and Apple Watch Ultra can measure a user’s body temperature through newly added sensors, it’s a feature that Apple insists is not yet accurate enough to be used for medical diagnosis or treatment. Instead, both of those devices use temperature measurements to provide users with a better understanding of their sleep patterns throughout the night. Unlike heart rate readings, the Apple Watch still isn’t a digital thermometer that can make accurate temperature readings on demand.

As many of us discovered during the wilder days of the Covid-19 pandemic, non-contact digital thermometers aren’t terribly expensive, but they can quickly sell out when demand for them skyrockets. As a readily available alternative, researchers at the University of Washington turned to smartphones. One key difference: Their solution does not need any added attachments or hardware upgrades. Smartphones already rely on components called thermistors to measure the temperature of the device’s internals, including the battery, in order to activate safety precautions to ensure they don’t overheat. It’s why your iPhone will sometimes show a warning that it needs to cool down before you can safely use it again.

Thermistors, which are also used in medical-grade thermometers, can’t directly measure a user’s body temperature while inside a smartphone, but they can be used to track the amount of heat energy that has been transferred between a user and the mobile device they’re making contact with. To simulate a fevered test subject, the researchers used a sous-vide machine to heat a plastic bag full of water, and pressed the touchscreens of several different smartphones against it, including devices in protective cases, and those using screen protectors. The built-in thermistor was used to measure how quickly the device warmed up during this interaction, and that data was used to train a machine learning model powering the FeverPhone app that can estimate what a user’s body temperature is.

Using the FeverPhone app sounds easy enough, but it requires users to hold their device at its corners and press its touchscreen against their forehead for around 90 seconds. This was deemed the ideal amount of time for enough body heat to be transferred to the device, and since the forehead interaction is detected by the touchscreen, it allows the device and the app to know when a measurement is being deliberately made.

During a clinical trial at the University of Washington’s School of Medicine’s Emergency Department, the app was tested by 37 participants, which included 16 with a mild fever, and the results were compared against readings from an oral thermometer. FeverPhone was able to predict a user’s core body temperature with “an average error of about 0.41 degrees Fahrenheit (0.23 degrees Celsius),“ which is on par with the accuracy of home use thermometers, including non-contact options.

The researchers are currently working to improve the app’s accuracy by expanding the number of smartphone models that were used to train its machine learning model, as initially just three different devices were used. But they’re optimistic that it could be trained to work with smartwatches, too, which would actually work much better as their smaller size would allow them to heat up faster and allow for measurements much shorter than 90 seconds. FeverPhone may never be approved as a medical grade thermometer, but it sounds like it will be accurate enough to give users a better idea when they might actually be sick, and should be taking appropriate measures to protect themselves and others.

We’ve been sucking the earth dry, and it’s starting to change how our planet works. A study published this month in the journal Geophysical Research Letters, explains that we’ve extracted so much damn water out of the ground, it has changed the planet’s tilt and has contributed to sea level rise.

Groundwater is a pretty important source of water throughout the world, especially in the U.S. It’s used to provide drinking water and it’s a backup source of water when there’s drought. But there is such a thing as taking too much out of the ground. “Earth’s pole has drifted toward 64.16°E at a speed of 4.36 cm/yr during 1993–2010 due to groundwater depletion and resulting sea level rise,” researchers wrote in the study. That’s a tilt of about 1.7 inches towards the east per year, or more than 28 inches (70 centimeters) in less than two decades.

But why does this happen? The planet’s rotational pole, which is the point that the Earth rotates around, moves via a process that is called polar motion. This describes the axis the world spins on relative to the Earth’s crust. And the water distributed across the planet affects how the world spins, researchers explained in the study. So if groundwater is taken out of the Earth’s crust and moved elsewhere, it’s adding to the water in the ocean, and it’s shifting how mass is moved around. This makes a difference because there is a lot of water underground around the world. There is actually over a thousand times more water underground than there is in all the world’s rivers and lakes, according to the U.S. Geological Survey.

“Earth’s rotational pole actually changes a lot,” Ki-Weon Seo, a geophysicist at Seoul National University and study coauthor, said in a statement. “Our study shows that among climate-related causes, the redistribution of groundwater actually has the largest impact on the drift of the rotational pole.”

But water extraction hasn’t just changed how the world tilts. Researchers used groundwater data and climate models to conclude that we’ve pumped enough groundwater to contribute to 6.24 millimeters (.24 inches) of sea level rise from 1993 to 2010. These findings are alarming because the sea level has increased at a rate of 3.4 millimeters (.13 inches) a year since 1993, according to NASA. These numbers may seem small, but sea level rise that is already fueled by climate change has major implications for the world. Recent research shows how sea level rise is washing away the breeding ground for endangered species of turtles. Major cities on the coast will be swallowed up by sea level rise, potentially displacing hundreds of millions of people in a few decades.

Communities throughout the U.S., especially in the South, are struggling with sea level rise. Louisiana has a huge erosion problem. Data from the U.S. Geological Survey shows that the state lost an estimated 2,000 square miles of land between 1932 and 2016. That’s larger than the state of Rhode Island. Sea level rise has been a long-time growing concern for Florida’s coast, but flooding and king tides are projected to happen more often in the sunshine state. The increased flooding over time has also messed with the real estate market, and people in flood zones could see their property values plunge.

Some local governments in the U.S. have addressed the over-extraction of groundwater recently. Arizona officials recently paused some housing development expansion over groundwater supply. Construction can only continue for new builds in parts of Phoenix if developers are able to prove that there is a steady source of water for those future households. However, developers cannot rely on groundwater as a water source to obtain a certificate that would allow them to continue building, AZFamily reported. Officials have decided on this because groundwater is a finite resource, and if communities continue to overdraw water, it could take up to thousands of years to replenish that source of water.

Want more climate and environment stories? Check out Earther’s guides to decarbonizing your home, divesting from fossil fuels, packing a disaster go bag, and overcoming climate dread. And don’t miss our coverage of the latest IPCC climate report, the future of carbon dioxide removal, and the un-greenwashed facts on bioplastics and plastic recycling.

There’s a saying that the eyes are the window to a person’s soul, but according to a team of researchers from the University of Maryland, the eyes might instead be a mirror, providing enough data to reconstruct exactly what a person in a short video clip was looking at as an interactive 3D model.

A lot of factors made CSI, and its spin-offs, a popular franchise for CBS, but what drew many viewers back, week after week, was the over-the-top technology the crime scene investigators had at their disposal. A grainy, low-resolution frame of video captured in the middle of the night by a security camera could be repeatedly enhanced until it revealed the individual fibers on a suspect’s shirt. Most of the tools used to solve crimes on the show still only exist in the writers’ imagination, but researchers are making impressive advances when it comes to the amount of data that can be extracted from just a few frames of video footage.

Leveraging previous research on neural radiance field (NeRF) technology, where complex scenes or objects can be fully recreated in 3D using just a partial set of 2D images captured at various angles, and the fact that the shape of the eye’s cornea is more-or-less the same for all healthy adults, the University of Maryland researchers were able to generate 3D recreations of simple scenes based on imagery extracted from eye reflections. Don’t expect the results to be used to solve any crimes, though.

This approach, as detailed in a recently published study, comes with some very unique challenges. For starters, recreating 3D models from 2D images usually starts with high-quality source material, like video captured from a modern smartphone’s digital camera. Here, the reflections are extracted from a tiny, low-res portion of each frame, and they’re layered atop the complex textures of the eye’s iris, which also varies in color from person to person, requiring extensive post-processing to clean up the imagery.

Further complicating this approach is the fact that the series of 2D images being used to create the reconstruction are all originating from the same location, with only slight variations introduced as the subject’s eye looks around. If you’ve ever tried to generate a 3D model of an object or a room using a smartphone’s camera and an app, you know you have to move around and record it from all sides and angles in order to get optimal results. But that’s not an option here.

As a result, the 3D models generated using this new technique are very low resolution and low on details. You can still identify objects like a plush dog, or a bright pink Kirby toy, as the researchers did, but these results were also achieved using optimal conditions: very basic scenes, very deliberate lighting, and high-res source imagery.

When the researchers attempted to apply their approach to footage they weren’t responsible for capturing but was still created using ideal lighting conditions, such as a clip of Miley Cyrus from her Wrecking Ball music video sourced from YouTube, it’s impossible to discern what you’re looking at in the resulting 3D model. The vague blob is probably a hole in a white shroud the camera lens was looking through in order to achieve the specific look of this shot, but not even Grissom’s CSI team could confirm that using this 3D model. As fascinating as this research may be, it’s going to be a while before it becomes a tool that has any practical applications.

AI hype has officially reached “Metaverse” levels of incomprehensibility. Large language models are a wormhole sucking in any and all tech companies looking to promote long-existing products, and now e-bike maker Urtopia is one of the first companies trying to force chatbots on users who are simply trying to travel from A to B.

In a press release, Urtopia shared scant details for its latest smart e-bike features other than that its products were getting access to ChatGPT. This feature would apparently sit alongside existing built-in navigation capabilities and connections to apps like Apple Health and Strava. Gizmodo reached out to the company for clarification, but we did not immediately hear back. Instead, we’re left with many, small questions but only one that actually matters: why?

The company already has released two e-bikes, the Carbon 1 and the more recent Chord. Both bikes also include navigation features and other safety capabilities like GPS tracking. The more expensive Carbon 1 includes “game pad” as well as voice controls, while the Chord only includes the latter.

In a promotional video, Urtopia shows somebody asking what appears to be the Chord bike “who are you?” The bike responds in a grinding, artificial voice “I am an AI language model.” In response to a query about what the point of an e-bike is, the chatbot gives the boilerplate answer for the health benefits of electric bicycles.

Instead of sharing how a chatbot could be useful while ducking and weaving around cars on a crowded street, we’re presented with what is just the start of the new tech hype cycle. At the start of this tech hype cycle, companies have relegated chatbots to boring app applications. Having ChatGPT accessible in an app like Snapchat was derided by the app’s users, but that hasn’t stopped plenty of other applications from trying to integrate AI. Some have done better than others, but nearly all these tech companies try to stave off complaints by calling the chatbot applications a “beta” or “experimental.”

Urtopia isn’t even doing that much. Both bikes already come stock with wifi, Bluetooth, and 4G connectivity, but what remains unclear is if its existing apps are interoperable with the ChatGPT integration. Beyond potentially allowing more natural voice controls for the smart bikes’ screen, the only other use case seems to be asking the chatbot for the kind of boring, noncommittal answers to the same, tired prompts you get from either the browser or app versions.

While this may be one of the first commercial bikes to stuff a modern AI chatbot into its system, it’s not the first vehicle to promise ChatGPT on the go. Earlier this month, Mercedez-Benz announced a new beta program that adds ChatGPT to its cars’ voice assistant. Those cars equipped with the MBUX assistant program can opt to talk to the car and then receive chatbot-based responses channeled through Microsoft Azure OpenAI cloud-based service.

Mercedes-Benz claimed that ChatGPT adds more natural responses to user questions beyond the predefined queries about sports and weather updates. The examples the carmaker gives are asking for details about their destination, or asking the car for a dinner recipe (though knowing what kinds of recipes ChatGPT is likely to generate, we don’t recommend it). So if you get into an argument with other passengers in the car, you could potentially have ChatGPT settle the score, as long as you’re willing to believe it’s not lying to you.

The car company’s chief technology officer Markus Schäfer said the goal is “redefining the relationship with your Mercedes.” Unfortunately, ChatGPT isn’t a great conversationalist. At its best, it’s a capable assistant program. At its worst, it’s an extremely effective liar. As long as the GPS and AI systems are kept functionally separate, then we shouldn’t have to worry about AI sending users careening off a cliff.

Competition for jobs is fierce in China right now. After he graduated from college with a business major earlier this year, David struggled to find work. There were too many applicants for every position, and, he says, “even if you find a job, the pay is not as great as previous years, and you have to work long hours.”

After David—who asked for anonymity to talk freely about his business—saw some videos on Weibo and WeChat about ChatGPT, the generative artificial intelligence chatbot released to great fanfare late last year by the US tech company OpenAI, he was struck with an idea. There’s a thriving essay-writing business in China, with students asking tutors and experts to help them with their homework. Brokers operating on the ecommerce platform Taobao hire writers, whose services they sell to students. What if, David thought, he could use ChatGPT to write essays? He approached one of the sellers on Taobao. He quickly got his first job, writing a paper for a student majoring in education. He didn’t tell anyone he was using a chatbot.

“You first ask ChatGPT to generate an outline with a few bullet points, and then you ask ChatGPT to come up with content for each bullet point,” David says. To avoid obvious plagiarism, he tried not to feed in existing articles or papers, and instead asked the chatbot open-ended questions. He picked out longer sentences, and asked ChatGPT to elaborate and give examples. Then he read through the piece and cleaned up any grammatical errors. The result wasn’t the smoothest, and there were a few logical gaps between paragraphs, but it was enough to complete the assignment. He submitted it and made $10. His second job was writing an economics paper. He glanced through the requirements, picked up a few important terms like “dichotomy,” and asked ChatGPT to explain these terms in easily understandable ways and give examples. He made around $40.

ChatGPT is not officially accessible to Chinese users. Emails with Chinese domains, like QQ or 163, can’t be used to sign up to the service. Nevertheless, there’s an enormous interest in the potential of the system. Youdao, a popular online education service operated by the tech giant NetEase, recently released an online course: “ChatGPT, from entry to proficiency,” promising to “increase your work efficiency by 10 times with the help of ChatGPT and Python.” On Zhihu, China’s quora, a forum website where questions are created and answered, users ask “how to make the first pot of gold using ChatGPT”; “how to make RMB1,000 using ChatGPT”; “how ordinary people can make money using ChatGPT?” The answer—which ChatGPT itself told me when I asked it how to make $100—is content. Lots of content.

Yin Yin, a young woman who has worked for a few social media influencers as a content creation assistant, came across ChatGPT after seeing a viral YouTube video. In April, she found a Taobao store selling home decor using traditional Yunnan tie-dye techniques. She approached the owner and offered to help him improve its layout and to do some social media promotion. The store’s product descriptions were plain and lacking in details, she says. She tracked down the most popular home decor items on Taobao, extracted their product descriptions, and fed them to ChatGPT for reference. To make the content even more eye-catching, she asked ChatGPT to specifically emphasize a few product features and to add a few emojis to make it more appealing to the younger generation. She is now paid monthly by the Taobao shop owner.

Others are using AI for way more than product descriptions. One user, Shirley, who also asked to be identified using only her first name because she writes under a pseudonym, Guyuetu, on the fashion and lifestyle sharing platform Little Red Book (Xiaohongshu), published a whole book written using AI. She decided on the subject: the correlation between blood type and personality (a pseudoscientific belief that is relatively common in Japan and Korea). She asked ChatGPT to “create an outline for a book about Japanese’s people’s take on blood type and personality,” then used it to generate an outline for each chapter, and then to generate different sections for each chapter. “If you don’t like what’s been written, you can always ask ChatGPT to rewrite, like rewrite a paragraph using a more fun, lighthearted tone,” she says. Within two days, she finished the book “The Little Book of Blood Type Personality: The Japanese Way of Understanding People,” with a cover and illustrations created by Midjourney, a service which creates images from text prompts. She published the book on Kindle.