<![CDATA[Scivillage.com Casual Discussion Science Forum - Gadgets & Technology]]> https://www.scivillage.com/ Tue, 25 Aug 2026 07:16:24 +0000 MyBB <![CDATA[Portland's amazing weather machine]]> https://www.scivillage.com/thread-21176.html Tue, 25 Aug 2026 00:22:13 +0000 Magical Realist]]> https://www.scivillage.com/thread-21176.html
https://www.youtube.com/shorts/_EPOA4hbo4w]]>
https://www.youtube.com/shorts/_EPOA4hbo4w]]> <![CDATA[A smartphone navigation app for people with blindness and low vision]]> https://www.scivillage.com/thread-21168.html Mon, 24 Aug 2026 17:45:10 +0000 C C]]> https://www.scivillage.com/thread-21168.html https://www.eurekalert.org/news-releases/1140973

EXCERPTS: For people with blindness or who have low vision, moving around independently is a daily challenge. Harvard researchers have developed a new tool that could help such people navigate more quickly and safely, using nothing but a device they likely already have – a smartphone.

Engineers at the John A. Paulson School of Engineering and Applied Sciences (SEAS) have invented a new smartphone app called Mobilio that combines machine learning; algorithms that streamline input from multiple sensors; and personalized audio cues to provide a blind or low-vision person turn-by-turn directions, path guidance, and obstacle avoidance. The research was led by Ph.D. student Raymond Liu in collaboration with Patrick Slade, assistant professor of bioengineering.

The research is published in Nature Biomedical Engineering. [...] “Our system uses the sensors in a smartphone, GPS information, and the actual motion of the person to create what’s essentially a small autonomous vehicle plan on how to navigate them from where they are to where they want to go,” Slade said.

Since most publicly available street-scene datasets are captured from cars, many standard models misclassify pedestrian-relevant infrastructure, explained first author Liu. To address this issue, Liu trained a semantic segmentation model specifically on pedestrian-view images so it could reliably recognize sidewalks, crosswalks, roads, and other key surfaces during walking.

“There’s a need for more data that comes from the perspective of humans walking along sidewalks, or walking outdoors,” Liu added. Liu said a major design challenge was ensuring all the algorithms and models could run in real time on a standard smartphone, which has far less computing power than a laptop or specialized hardware.

Instead of just spoken prompts, Mobilio provides continuous audio cues in the form of beeps as the user walks. The beeps originate from a direction, such as the user’s left or right, to indicate steering, and the guidance is personalized in real time using human-in-the-loop optimization. As a person walks, the system measures how accurately they follow the audio cues and automatically adjusts the cues and pitch patterns to work best for that individual.

[...] Compared to using Google Maps and a cane, participants using Mobilio and a cane completed the outdoor route about 13% faster, and reduced contact with obstacles in the indoor route by about 41%. In terms of reliability, or how consistently the system guided users to the destination without major errors, Mobilio performed comparably to a human guide... (MORE - missing details, no ads)]]> https://www.eurekalert.org/news-releases/1140973

EXCERPTS: For people with blindness or who have low vision, moving around independently is a daily challenge. Harvard researchers have developed a new tool that could help such people navigate more quickly and safely, using nothing but a device they likely already have – a smartphone.

Engineers at the John A. Paulson School of Engineering and Applied Sciences (SEAS) have invented a new smartphone app called Mobilio that combines machine learning; algorithms that streamline input from multiple sensors; and personalized audio cues to provide a blind or low-vision person turn-by-turn directions, path guidance, and obstacle avoidance. The research was led by Ph.D. student Raymond Liu in collaboration with Patrick Slade, assistant professor of bioengineering.

The research is published in Nature Biomedical Engineering. [...] “Our system uses the sensors in a smartphone, GPS information, and the actual motion of the person to create what’s essentially a small autonomous vehicle plan on how to navigate them from where they are to where they want to go,” Slade said.

Since most publicly available street-scene datasets are captured from cars, many standard models misclassify pedestrian-relevant infrastructure, explained first author Liu. To address this issue, Liu trained a semantic segmentation model specifically on pedestrian-view images so it could reliably recognize sidewalks, crosswalks, roads, and other key surfaces during walking.

“There’s a need for more data that comes from the perspective of humans walking along sidewalks, or walking outdoors,” Liu added. Liu said a major design challenge was ensuring all the algorithms and models could run in real time on a standard smartphone, which has far less computing power than a laptop or specialized hardware.

Instead of just spoken prompts, Mobilio provides continuous audio cues in the form of beeps as the user walks. The beeps originate from a direction, such as the user’s left or right, to indicate steering, and the guidance is personalized in real time using human-in-the-loop optimization. As a person walks, the system measures how accurately they follow the audio cues and automatically adjusts the cues and pitch patterns to work best for that individual.

[...] Compared to using Google Maps and a cane, participants using Mobilio and a cane completed the outdoor route about 13% faster, and reduced contact with obstacles in the indoor route by about 41%. In terms of reliability, or how consistently the system guided users to the destination without major errors, Mobilio performed comparably to a human guide... (MORE - missing details, no ads)]]> <![CDATA[First test flight of largest all-electric aircraft used just $5 of electricity]]> https://www.scivillage.com/thread-21112.html Mon, 17 Aug 2026 16:15:38 +0000 C C]]> https://www.scivillage.com/thread-21112.html So is Trump some kind of secret or in-the-closet electric vehicle lover after all, via starting the Iran War?
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First test flight of largest all-electric aircraft used just $5 of electricity
https://arstechnica.com/gadgets/2026/08/...ectricity/

INTRO: The first flight of the largest battery-electric aircraft to take to the skies lasted nearly half an hour while costing just $5 of electricity. That aviation feat comes at a time when jet fuel prices have skyrocketed because of the US war with Iran.

The test flight of Heart Aerospace’s X1 demonstrator aircraft took place at Plattsburgh International Airport in upstate New York on August 12. The X1 aircraft is comparable in size to a small regional airliner and can achieve a maximum takeoff weight exceeding 25,000 pounds with the help of four wing-mounted electric motors. The battery-electric propulsion system delivered more than one megawatt of power during the maiden flight.

All-electric aircraft can offer quieter and cleaner flight without the emissions that come from burning jet fuel. They may also prove more reliably cost-effective than conventional aircraft that come with jet fuel costs subject to geopolitical disruptions.

But the initial success of the X1 demonstrator does not mean Heart Aerospace is planning to commercialize an all-electric aircraft. Current battery-electric systems can only typically sustain short flights of about 100 to 200 miles, which is why they have been limited to air taxi operations by companies such as Joby and Archer.

Instead, testing of the X1 and a planned follow-on X2 aircraft will shape development of Heart Aerospace’s main offering to the airline industry—a 30-seat hybrid-electric regional airliner known as the ES-30.

That planned production aircraft for commercial flights would combine two inboard electric motors with commercial turboprop engines that run on jet fuel, enabling 125 miles of all-electric flight and 500 miles of flight range when operating in hybrid mode... (MORE - details)

Aerospace’s X1 demonstrator ... https://youtu.be/yWDgOZjvFws

https://www.youtube-nocookie.com/embed/yWDgOZjvFws]]> So is Trump some kind of secret or in-the-closet electric vehicle lover after all, via starting the Iran War?
- - - - - - - - - - - -

First test flight of largest all-electric aircraft used just $5 of electricity
https://arstechnica.com/gadgets/2026/08/...ectricity/

INTRO: The first flight of the largest battery-electric aircraft to take to the skies lasted nearly half an hour while costing just $5 of electricity. That aviation feat comes at a time when jet fuel prices have skyrocketed because of the US war with Iran.

The test flight of Heart Aerospace’s X1 demonstrator aircraft took place at Plattsburgh International Airport in upstate New York on August 12. The X1 aircraft is comparable in size to a small regional airliner and can achieve a maximum takeoff weight exceeding 25,000 pounds with the help of four wing-mounted electric motors. The battery-electric propulsion system delivered more than one megawatt of power during the maiden flight.

All-electric aircraft can offer quieter and cleaner flight without the emissions that come from burning jet fuel. They may also prove more reliably cost-effective than conventional aircraft that come with jet fuel costs subject to geopolitical disruptions.

But the initial success of the X1 demonstrator does not mean Heart Aerospace is planning to commercialize an all-electric aircraft. Current battery-electric systems can only typically sustain short flights of about 100 to 200 miles, which is why they have been limited to air taxi operations by companies such as Joby and Archer.

Instead, testing of the X1 and a planned follow-on X2 aircraft will shape development of Heart Aerospace’s main offering to the airline industry—a 30-seat hybrid-electric regional airliner known as the ES-30.

That planned production aircraft for commercial flights would combine two inboard electric motors with commercial turboprop engines that run on jet fuel, enabling 125 miles of all-electric flight and 500 miles of flight range when operating in hybrid mode... (MORE - details)

Aerospace’s X1 demonstrator ... https://youtu.be/yWDgOZjvFws

https://www.youtube-nocookie.com/embed/yWDgOZjvFws]]> <![CDATA[Smart TV apps are hijacking your internet connection?]]> https://www.scivillage.com/thread-21088.html Thu, 13 Aug 2026 19:19:14 +0000 C C]]> https://www.scivillage.com/thread-21088.html Samsung is cracking down on TV apps that quietly shared users’ internet connections
https://www.digitaltrends.com/home-theat...nnections/

I’ve never once suspected my smart TV of moonlighting as someone else’s internet connection. However, that’s apparently been happening to millions of Samsung smart TV users.

Norwegian cybersecurity firm Mnemonic discovered that several popular Samsung smart TV apps, some claiming installs on hundreds of millions of devices, contain code that quietly shares the owner’s internet connection without permission.

One of the apps flagged was a Pac-Man game that, ironically, Samsung had featured in its own “Editor’s Choice” section. That game contained code from Bright Data, which is an Israel-based internet company that runs proxy networks. It claims access to millions of residential connections across the world, along with a marketplace selling scraped datasets pulled from those networks.

Once you open an app carrying such code and accept a consent screen, which most people probably click through without reading, your smart TV turns into what’s called a residential proxy in technical lingo. Essentially, the code routes outsiders’ web traffic through your home connection in the background.

And that’s not even the worst part. The routing remains active even after you close the app. It stays active until you uninstall it entirely from your smart TV. Harrison Sand, the offensive security consultant at Mnemonic, warned that a single code change on a remote web server could theoretically flip hundreds of millions of these TVs into a botnet all at once, with no user consent whatsoever.

It gets more interesting. Sand also observed that much of the traffic passing through his own TV (without his consent) appeared linked to mass scraping of LinkedIn profiles and collecting AI training data. However, he says he only glimpsed a small slice of Bright Data’s overall network.

Samsung, for its part, told TechCrunch it’s now banning apps that share users’ connections (which it should), has already restricted new app registrations using proxy functionality, and is working to identify and pull existing offenders from its store.

This follows LG’s own ban last month, as similar reporting found roughly 42% of apps on LG’s store were doing the exact same thing. After writing this, I’m going to check my smart TV for apps I don’t remember installing, or I don’t use that frequently, and will uninstall them rightaway, and you should do it too.]]> Samsung is cracking down on TV apps that quietly shared users’ internet connections
https://www.digitaltrends.com/home-theat...nnections/

I’ve never once suspected my smart TV of moonlighting as someone else’s internet connection. However, that’s apparently been happening to millions of Samsung smart TV users.

Norwegian cybersecurity firm Mnemonic discovered that several popular Samsung smart TV apps, some claiming installs on hundreds of millions of devices, contain code that quietly shares the owner’s internet connection without permission.

One of the apps flagged was a Pac-Man game that, ironically, Samsung had featured in its own “Editor’s Choice” section. That game contained code from Bright Data, which is an Israel-based internet company that runs proxy networks. It claims access to millions of residential connections across the world, along with a marketplace selling scraped datasets pulled from those networks.

Once you open an app carrying such code and accept a consent screen, which most people probably click through without reading, your smart TV turns into what’s called a residential proxy in technical lingo. Essentially, the code routes outsiders’ web traffic through your home connection in the background.

And that’s not even the worst part. The routing remains active even after you close the app. It stays active until you uninstall it entirely from your smart TV. Harrison Sand, the offensive security consultant at Mnemonic, warned that a single code change on a remote web server could theoretically flip hundreds of millions of these TVs into a botnet all at once, with no user consent whatsoever.

It gets more interesting. Sand also observed that much of the traffic passing through his own TV (without his consent) appeared linked to mass scraping of LinkedIn profiles and collecting AI training data. However, he says he only glimpsed a small slice of Bright Data’s overall network.

Samsung, for its part, told TechCrunch it’s now banning apps that share users’ connections (which it should), has already restricted new app registrations using proxy functionality, and is working to identify and pull existing offenders from its store.

This follows LG’s own ban last month, as similar reporting found roughly 42% of apps on LG’s store were doing the exact same thing. After writing this, I’m going to check my smart TV for apps I don’t remember installing, or I don’t use that frequently, and will uninstall them rightaway, and you should do it too.]]> <![CDATA[Making robots faster by helping them think ahead]]> https://www.scivillage.com/thread-20970.html Wed, 29 Jul 2026 01:21:25 +0000 C C]]> https://www.scivillage.com/thread-20970.html https://www.eurekalert.org/news-releases/1137936

INTRO:  A new method developed by MIT researchers makes robots better at thinking ahead while they are acting, leading to smoother motions and quicker reactions. This technique enables the artificial intelligence model that plans a robot’s motion to forecast its future position. The model uses this prediction to seamlessly transition current movements into the next actions.

Many existing methods cause a robot to stop and think about what it needs to do next, leading to slow and jerky motions. By basing its calculations on the future state of the robot, rather than its current position, the MIT method helps robots operate much faster.

Importantly, the technique does not add any computational overhead to the planning process and can be applied to varied robotic hardware.

This new method doubled the speed of robots performing activities like pick-and-place tasks, while significantly reducing lag time between motions. It also boosted the performance of robotic arms in highly dynamic activities, such as playing table tennis and Whack-a-Mole.

The system could be especially useful for robots that perform fast and agile maneuvers in challenging real-world environments, like emergency response or search-and-rescue. It could also allow robots to react more quickly when recovering from mistakes.

“This work sets up a good foundation for efficient, fast, accelerated, and low-cost robotics applications. We look forward to expanding our work into the latest world action models, so it has even stronger capabilities as we keep pushing to make physical AI faster,” says Song Han, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), member of the Research Laboratory of Electronics, and lead author of a paperon this method.

Han is joined on the paper by co-lead authors Jiaming Tang, an MIT EECS graduate student, and Yufei Sun, a student at Tsinghua University; as well as others at Nvidia, the University of California at Berkeley, the University of California at San Diego, and Caltech. The research will be presented at the Intelligent Robots and Systems Conference... (MORE - no ads)]]> https://www.eurekalert.org/news-releases/1137936

INTRO:  A new method developed by MIT researchers makes robots better at thinking ahead while they are acting, leading to smoother motions and quicker reactions. This technique enables the artificial intelligence model that plans a robot’s motion to forecast its future position. The model uses this prediction to seamlessly transition current movements into the next actions.

Many existing methods cause a robot to stop and think about what it needs to do next, leading to slow and jerky motions. By basing its calculations on the future state of the robot, rather than its current position, the MIT method helps robots operate much faster.

Importantly, the technique does not add any computational overhead to the planning process and can be applied to varied robotic hardware.

This new method doubled the speed of robots performing activities like pick-and-place tasks, while significantly reducing lag time between motions. It also boosted the performance of robotic arms in highly dynamic activities, such as playing table tennis and Whack-a-Mole.

The system could be especially useful for robots that perform fast and agile maneuvers in challenging real-world environments, like emergency response or search-and-rescue. It could also allow robots to react more quickly when recovering from mistakes.

“This work sets up a good foundation for efficient, fast, accelerated, and low-cost robotics applications. We look forward to expanding our work into the latest world action models, so it has even stronger capabilities as we keep pushing to make physical AI faster,” says Song Han, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), member of the Research Laboratory of Electronics, and lead author of a paperon this method.

Han is joined on the paper by co-lead authors Jiaming Tang, an MIT EECS graduate student, and Yufei Sun, a student at Tsinghua University; as well as others at Nvidia, the University of California at Berkeley, the University of California at San Diego, and Caltech. The research will be presented at the Intelligent Robots and Systems Conference... (MORE - no ads)]]> <![CDATA[Chocolate syrup-like fluid stores multiple interacting memories]]> https://www.scivillage.com/thread-20946.html Sun, 26 Jul 2026 22:19:58 +0000 C C]]> https://www.scivillage.com/thread-20946.html https://www.psu.edu/news/eberly-college-...g-memories

PRESS RELEASE: Animals and electronic devices aren’t the only things with memory. Materials can retain memories of past deformations in their microscopic structure. A common example is a crease in a sheet of paper that has been folded then unfolded. Understanding this type of memory could benefit the design of materials that respond to changes in their environment in predictable ways. It can also be a source of ideas about the various types of memory studied by neuroscientists, including how short-term and long-term memories interact and influence each other. Now, researchers at Penn State have shown that two different types of material memory can coexist in a simple mixture of small particles suspended in a viscous liquid. Like long- and short-term memories, these material memories interact and compete.

A paper describing the research was recently published and highlighted as an editors’ suggestion in the journal Physical Review Letters.

“When you save a file on your computer, that new memory does not influence any of the other files that are already there,” said Surendra Padamata, a graduate student in physics in the Penn State Eberly College of Science and first author of the paper. “But in neuroscience, we know that, for example, a long-term memory might change over time, influenced by new short-term memories gained in the intervening years. For example, a novel read in adolescence may seem to be a simple story. Recalling it later in life, after personal experiences that echo its themes, can reveal layers of meaning that went unnoticed the first time. We were inspired by thinking about how memories interact in this way to see if we could find an analogous situation in a material.”

The research team studies memory in non-Brownian suspensions. Like chocolate syrup or fresh concrete, non-Brownian suspensions are composed of relatively large particles in a viscous liquid. The particles are large enough that their movement is not influenced by Brownian motion — the random movement of thermally energetic atoms — so any movement of the particles would be due to their experimental design. They first showed that their suspension could remember the direction it was stirred, and if it was rocked back and forth, the suspension of particles remembered how vigorously it was rocked — the amplitude.

“Each of these memories had been studied on its own,” Padamata said. “So, in our new experiments, we first stirred the mixture, imprinting a memory of direction, then rocked it back and forth at varying intensities to see how the memories interact.”

The team found that at lower rocking intensities, the mixture retained memory of the direction of stirring in addition to the memory of amplitude — the two memories can, in fact, occupy the same material at the same time. But as the rocking intensified, the memory of direction weakened and was eventually erased.

“At a certain threshold of intensity, the rocking completely erased any memory of direction in the suspension, returning it to a perfectly symmetric state, but beyond that threshold, the rocking itself begins to write a new directional memory” Padamata said. “We are interested in how this model can inform biological memory and, potentially, geophysical processes as well. Changes in temperature and vibrations might impart memories in rock that influence risk for earthquakes and sink holes, for example. It could be possible to find some way to erase these memories and reduce the risk or make better predictive models.”

The researchers suggested that the competition between the memories could happen when encounters between particles become too numerous — whereas for smaller rocking motions, these encounters can be rare. However, that detail might be specific to particles suspended in liquid and it depends on the ratio of particles to liquid. Similar memory phenomena have been observed in solid materials, where neighboring particles are always in contact.

“A similar combination of directional memory and amplitude memory appears in soft glasses and granular packings with very different microscopic physics,” said Nathan Keim, associate professor of physics at Penn State and the leader of the research team. “This suggests that there may be a general principle for how disordered matter behaves under simple conditions like stirring or rocking and why they have a limited memory capacity.”]]> https://www.psu.edu/news/eberly-college-...g-memories

PRESS RELEASE: Animals and electronic devices aren’t the only things with memory. Materials can retain memories of past deformations in their microscopic structure. A common example is a crease in a sheet of paper that has been folded then unfolded. Understanding this type of memory could benefit the design of materials that respond to changes in their environment in predictable ways. It can also be a source of ideas about the various types of memory studied by neuroscientists, including how short-term and long-term memories interact and influence each other. Now, researchers at Penn State have shown that two different types of material memory can coexist in a simple mixture of small particles suspended in a viscous liquid. Like long- and short-term memories, these material memories interact and compete.

A paper describing the research was recently published and highlighted as an editors’ suggestion in the journal Physical Review Letters.

“When you save a file on your computer, that new memory does not influence any of the other files that are already there,” said Surendra Padamata, a graduate student in physics in the Penn State Eberly College of Science and first author of the paper. “But in neuroscience, we know that, for example, a long-term memory might change over time, influenced by new short-term memories gained in the intervening years. For example, a novel read in adolescence may seem to be a simple story. Recalling it later in life, after personal experiences that echo its themes, can reveal layers of meaning that went unnoticed the first time. We were inspired by thinking about how memories interact in this way to see if we could find an analogous situation in a material.”

The research team studies memory in non-Brownian suspensions. Like chocolate syrup or fresh concrete, non-Brownian suspensions are composed of relatively large particles in a viscous liquid. The particles are large enough that their movement is not influenced by Brownian motion — the random movement of thermally energetic atoms — so any movement of the particles would be due to their experimental design. They first showed that their suspension could remember the direction it was stirred, and if it was rocked back and forth, the suspension of particles remembered how vigorously it was rocked — the amplitude.

“Each of these memories had been studied on its own,” Padamata said. “So, in our new experiments, we first stirred the mixture, imprinting a memory of direction, then rocked it back and forth at varying intensities to see how the memories interact.”

The team found that at lower rocking intensities, the mixture retained memory of the direction of stirring in addition to the memory of amplitude — the two memories can, in fact, occupy the same material at the same time. But as the rocking intensified, the memory of direction weakened and was eventually erased.

“At a certain threshold of intensity, the rocking completely erased any memory of direction in the suspension, returning it to a perfectly symmetric state, but beyond that threshold, the rocking itself begins to write a new directional memory” Padamata said. “We are interested in how this model can inform biological memory and, potentially, geophysical processes as well. Changes in temperature and vibrations might impart memories in rock that influence risk for earthquakes and sink holes, for example. It could be possible to find some way to erase these memories and reduce the risk or make better predictive models.”

The researchers suggested that the competition between the memories could happen when encounters between particles become too numerous — whereas for smaller rocking motions, these encounters can be rare. However, that detail might be specific to particles suspended in liquid and it depends on the ratio of particles to liquid. Similar memory phenomena have been observed in solid materials, where neighboring particles are always in contact.

“A similar combination of directional memory and amplitude memory appears in soft glasses and granular packings with very different microscopic physics,” said Nathan Keim, associate professor of physics at Penn State and the leader of the research team. “This suggests that there may be a general principle for how disordered matter behaves under simple conditions like stirring or rocking and why they have a limited memory capacity.”]]> <![CDATA[Biggest probabilistic computer turns noise into answers]]> https://www.scivillage.com/thread-20895.html Mon, 20 Jul 2026 16:06:53 +0000 C C]]> https://www.scivillage.com/thread-20895.html https://spectrum.ieee.org/biggest-probab...tent=hero4

INTRO: Probabilistic computers might one day tackle certain problems well beyond standard computers while at the same time avoiding the many hardware challenges that currently vex quantum computing. Now scientists reveal they have created the largest probabilistic computer yet, one with 1 million “probabilistic bits,” a new study they suggest reveals the way forward to building even bigger machines.

Probabilistic bits, or p-bits, bridge the gap between the bits underlying regular computers and the qubits upon which quantum computers are based. Bits symbolize data as either a 0 or 1. Qubits, because of the bizarre nature of quantum physics, can exist in a state where they are either 0 or 1 or any state in between simultaneously. In contrast, p-bits flip between 0 or 1 with a tunable probability.

A bit that flips back and forth between 0 and 1 might seem useless—indeed, in a regular computer this would be too noisy to operate. However, when many such noisy bits operate together in a correlated fashion, they can be used to solve a whole class of problems—stochastic problems—that operate on probabilities rather than concrete numbers. This includes optimization problems to, for instance, find the shortest route with which one can deliver a set of packages.

There are other kinds of machines that are also designed to tackle stochastic problems, such as quadratic unconstrained binary optimization (QUBO) devices or Ising machines. However, unlike those devices, probabilistic computers are not hardwired for a single problem, but are instead programmable general-purpose machines, says Kerem Çamsarı, an associate professor of electrical and computer engineering at the University of California, Santa Barbara.

In a 2019 Nature study, scientists developed a probabilistic computer with eight p-bits. By 2023, researchers had built a machine with 7,200 p-bits. However, these devices were each confined to a single chip. Networking together multiple such chips is not as simple as it is for regular GPUs or CPUs: the machine functions on correlated fluctuations, and syncing up those fluctuations across a set of wires is no easy feat. This raised questions as to whether probabilistic computers could scale to larger sizes, and what problems they might face if they tried... (MORE - details)]]> https://spectrum.ieee.org/biggest-probab...tent=hero4

INTRO: Probabilistic computers might one day tackle certain problems well beyond standard computers while at the same time avoiding the many hardware challenges that currently vex quantum computing. Now scientists reveal they have created the largest probabilistic computer yet, one with 1 million “probabilistic bits,” a new study they suggest reveals the way forward to building even bigger machines.

Probabilistic bits, or p-bits, bridge the gap between the bits underlying regular computers and the qubits upon which quantum computers are based. Bits symbolize data as either a 0 or 1. Qubits, because of the bizarre nature of quantum physics, can exist in a state where they are either 0 or 1 or any state in between simultaneously. In contrast, p-bits flip between 0 or 1 with a tunable probability.

A bit that flips back and forth between 0 and 1 might seem useless—indeed, in a regular computer this would be too noisy to operate. However, when many such noisy bits operate together in a correlated fashion, they can be used to solve a whole class of problems—stochastic problems—that operate on probabilities rather than concrete numbers. This includes optimization problems to, for instance, find the shortest route with which one can deliver a set of packages.

There are other kinds of machines that are also designed to tackle stochastic problems, such as quadratic unconstrained binary optimization (QUBO) devices or Ising machines. However, unlike those devices, probabilistic computers are not hardwired for a single problem, but are instead programmable general-purpose machines, says Kerem Çamsarı, an associate professor of electrical and computer engineering at the University of California, Santa Barbara.

In a 2019 Nature study, scientists developed a probabilistic computer with eight p-bits. By 2023, researchers had built a machine with 7,200 p-bits. However, these devices were each confined to a single chip. Networking together multiple such chips is not as simple as it is for regular GPUs or CPUs: the machine functions on correlated fluctuations, and syncing up those fluctuations across a set of wires is no easy feat. This raised questions as to whether probabilistic computers could scale to larger sizes, and what problems they might face if they tried... (MORE - details)]]> <![CDATA[Anti-capitalists now attacking tech giants for selective science fiction bias?]]> https://www.scivillage.com/thread-20865.html Wed, 15 Jul 2026 17:02:49 +0000 C C]]> https://www.scivillage.com/thread-20865.html Taking the Fiction out of Science Fiction
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The looting of science fiction
https://aeon.co/essays/silicon-valley-ha...on-problem

EXCERPTS: Musk has spoken of how science fiction shaped his ambitions. Reading sci-fi as a child, he said, inspired his desire to develop ‘cleaner energy technology or [build] spaceships to extend the human species’ reach.’ He has cited Isaac Asimov’s Foundation series as particularly influential to his work at SpaceX. [...] The novels are genuinely extraordinary works of democratic imagination. [...] Musk’s reading discards all of this...

[...] Science fiction provides the aesthetic cover for this anti-democratic vision. It makes rolling back the franchise sound like bold futurism rather than Victorian regression. It transforms rejection of democratic accountability into escape velocity, frontier expansion, civilisational survival. The future isn’t being shaped by democratic debate but through highly selective, often reactionary, fantasy. Under this model, the nation-state isn’t merely sidelined but actively hollowed out, replaced by corporate city-states and private digital jurisdictions – Snow Crash’s franchise nation made real.

The central question isn’t whether science fiction will shape reality – that process is already underway. The question is: whose version will prevail?

Silicon Valley’s power rests on presenting a narrow, reactionary fantasy as inevitable progress. But other futures are possible, and other science fictions exist. Ursula K Le Guin’s The Dispossessed (1974) imagines an anarchist Moon colony built on mutual aid rather than extraction. Octavia Butler’s Parable series (1993-98) depicts communities surviving collapse through adaptation and care rather than escape to Mars. Kim Stanley Robinson’s Mars trilogy (1992-96) shows planetary settlement as collective democratic project, not billionaire venture. These are not naive or utopian texts – they are demanding, difficult and honest about the costs of building anything new. They refuse the consolation of the lone visionary and insist, over and over, that the future is made by people working together.

These stories remind us that the future is not neutral inevitability but choice – one we have the right to reclaim from boardrooms treating dystopia as a business plan. When Thiel, Musk, Zuckerberg and Andreessen mine science fiction for blueprints, they are not finding the only possible futures. They are selecting the futures that justify their power.

Science fiction has always been political. Gibson’s Neuromancer was a warning about corporate power, not a pitch deck. Stephenson’s Snow Crash was satire, not strategy. Asimov’s Foundation explored the limits of individual genius and the necessity of democratic institutions. Star Trek imagined overcoming capitalism, not retrofitting it with better spaceships.

If the future is to be made from stories, our task is ensuring those stories are worthy of the people who will live within them. That means recognising the selective deployment of science fiction as a political tactic – seeing the militarised drone and the privatised city charter not as neutral tools but as crystallisations of specific, narrow stories about power. It means demanding accountability not to curated fantasies of a literary past but to the pluralistic needs of the present. It means asking: whose futures are being built? Who benefits? Who pays the cost? What was left behind in the looting? (MORE - missing details)]]> Taking the Fiction out of Science Fiction
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The looting of science fiction
https://aeon.co/essays/silicon-valley-ha...on-problem

EXCERPTS: Musk has spoken of how science fiction shaped his ambitions. Reading sci-fi as a child, he said, inspired his desire to develop ‘cleaner energy technology or [build] spaceships to extend the human species’ reach.’ He has cited Isaac Asimov’s Foundation series as particularly influential to his work at SpaceX. [...] The novels are genuinely extraordinary works of democratic imagination. [...] Musk’s reading discards all of this...

[...] Science fiction provides the aesthetic cover for this anti-democratic vision. It makes rolling back the franchise sound like bold futurism rather than Victorian regression. It transforms rejection of democratic accountability into escape velocity, frontier expansion, civilisational survival. The future isn’t being shaped by democratic debate but through highly selective, often reactionary, fantasy. Under this model, the nation-state isn’t merely sidelined but actively hollowed out, replaced by corporate city-states and private digital jurisdictions – Snow Crash’s franchise nation made real.

The central question isn’t whether science fiction will shape reality – that process is already underway. The question is: whose version will prevail?

Silicon Valley’s power rests on presenting a narrow, reactionary fantasy as inevitable progress. But other futures are possible, and other science fictions exist. Ursula K Le Guin’s The Dispossessed (1974) imagines an anarchist Moon colony built on mutual aid rather than extraction. Octavia Butler’s Parable series (1993-98) depicts communities surviving collapse through adaptation and care rather than escape to Mars. Kim Stanley Robinson’s Mars trilogy (1992-96) shows planetary settlement as collective democratic project, not billionaire venture. These are not naive or utopian texts – they are demanding, difficult and honest about the costs of building anything new. They refuse the consolation of the lone visionary and insist, over and over, that the future is made by people working together.

These stories remind us that the future is not neutral inevitability but choice – one we have the right to reclaim from boardrooms treating dystopia as a business plan. When Thiel, Musk, Zuckerberg and Andreessen mine science fiction for blueprints, they are not finding the only possible futures. They are selecting the futures that justify their power.

Science fiction has always been political. Gibson’s Neuromancer was a warning about corporate power, not a pitch deck. Stephenson’s Snow Crash was satire, not strategy. Asimov’s Foundation explored the limits of individual genius and the necessity of democratic institutions. Star Trek imagined overcoming capitalism, not retrofitting it with better spaceships.

If the future is to be made from stories, our task is ensuring those stories are worthy of the people who will live within them. That means recognising the selective deployment of science fiction as a political tactic – seeing the militarised drone and the privatised city charter not as neutral tools but as crystallisations of specific, narrow stories about power. It means demanding accountability not to curated fantasies of a literary past but to the pluralistic needs of the present. It means asking: whose futures are being built? Who benefits? Who pays the cost? What was left behind in the looting? (MORE - missing details)]]> <![CDATA[It’s disturbingly easy to trick AI into seeing aliens]]> https://www.scivillage.com/thread-20806.html Mon, 06 Jul 2026 23:58:53 +0000 C C]]> https://www.scivillage.com/thread-20806.html https://www.eurekalert.org/news-releases/1135009

EXCERPT: So Adami and Gupta did an experiment where they created artificial forms of life using a computer program called Avida, and then trained an AI to detect them.

In the Avida universe, digital organisms written in computer code — essentially strings of commands — copy themselves over and over again in a virtual Petri dish inside the computer. Each time they replicate, the copying process is imperfect and their computer code changes, just like the genetic code of real organisms mutates when they reproduce.

Such forms of “digital life” have been used for several decades to study evolution, Adami explained. For the study, the researchers used Avida to generate tens of thousands of digital organisms, some of which contained the instructions needed to copy themselves and others not. They then used them to train a neural network to distinguish between the two with 99.97% accuracy.

However, when the researchers put the neural network to the test on examples it had never seen before, the results looked far less impressive.

In their experiments, the researchers started by presenting the neural network with a digital organism that the AI correctly deemed incapable of copying itself. Then by gradually swapping out one operation for another in the organism’s computer code, the researchers were able to trick the AI into misclassifying the organism as self-replicating, in as few as 150 tries.

In other words, with just a few tweaks, the team showed that it was possible to convince the AI that it was seeing signs of life where they didn’t exist.

"No matter what sequence of commands we started with, we were able to fool the AI 100% of the time," said Gupta, a PhD student in computer science and engineering at MSU. The number of sequences that could potentially trip up the network is vast. “So the likelihood of encountering such a sequence is substantial,” Adami added.

This risk of false positives raises the likelihood that space missions could be fooled into thinking they’d made a discovery by the data they gather, only to be proven wrong later.

Having trained an AI on computer-generated data, next the researchers plan to re-train the model with real-world data and see how easy it is to deceive, Gupta said. The findings underscore a known weakness in many contemporary AI models.

“AI has an Achilles heel,” said Adami, professor in MSU’s departments of microbiology and molecular genetics, and physics and astronomy. “It can see a pattern and completely misclassify it.”

Beyond the search for alien life, this weakness could also be problematic as AI continues to move into medical scanners, security cameras, self-driving cars and other devices in everyday use here on Earth... (MORE - no ads)]]> https://www.eurekalert.org/news-releases/1135009

EXCERPT: So Adami and Gupta did an experiment where they created artificial forms of life using a computer program called Avida, and then trained an AI to detect them.

In the Avida universe, digital organisms written in computer code — essentially strings of commands — copy themselves over and over again in a virtual Petri dish inside the computer. Each time they replicate, the copying process is imperfect and their computer code changes, just like the genetic code of real organisms mutates when they reproduce.

Such forms of “digital life” have been used for several decades to study evolution, Adami explained. For the study, the researchers used Avida to generate tens of thousands of digital organisms, some of which contained the instructions needed to copy themselves and others not. They then used them to train a neural network to distinguish between the two with 99.97% accuracy.

However, when the researchers put the neural network to the test on examples it had never seen before, the results looked far less impressive.

In their experiments, the researchers started by presenting the neural network with a digital organism that the AI correctly deemed incapable of copying itself. Then by gradually swapping out one operation for another in the organism’s computer code, the researchers were able to trick the AI into misclassifying the organism as self-replicating, in as few as 150 tries.

In other words, with just a few tweaks, the team showed that it was possible to convince the AI that it was seeing signs of life where they didn’t exist.

"No matter what sequence of commands we started with, we were able to fool the AI 100% of the time," said Gupta, a PhD student in computer science and engineering at MSU. The number of sequences that could potentially trip up the network is vast. “So the likelihood of encountering such a sequence is substantial,” Adami added.

This risk of false positives raises the likelihood that space missions could be fooled into thinking they’d made a discovery by the data they gather, only to be proven wrong later.

Having trained an AI on computer-generated data, next the researchers plan to re-train the model with real-world data and see how easy it is to deceive, Gupta said. The findings underscore a known weakness in many contemporary AI models.

“AI has an Achilles heel,” said Adami, professor in MSU’s departments of microbiology and molecular genetics, and physics and astronomy. “It can see a pattern and completely misclassify it.”

Beyond the search for alien life, this weakness could also be problematic as AI continues to move into medical scanners, security cameras, self-driving cars and other devices in everyday use here on Earth... (MORE - no ads)]]> <![CDATA[NASA’s X-59 “frankenjet” tests supersonic flight without the sonic boom]]> https://www.scivillage.com/thread-20760.html Tue, 30 Jun 2026 16:49:03 +0000 C C]]> https://www.scivillage.com/thread-20760.html https://arstechnica.com/gadgets/2026/06/...onic-boom/

INTRO: More than two decades since the Concorde supersonic airliner last took to the skies, NASA has been flying an experimental aircraft designed to replace loud sonic booms with a quieter thump equivalent to a car door slamming shut 20 feet away. A successful NASA flight test program could influence the design of future supersonic airliners capable of flying overland routes without rattling buildings—and people’s nerves.

The Lockheed Martin X-59 Quesst—an acronym for Quiet SuperSonic Technology—first took flight late last year and recently began supersonic test flights. But unlike with many experimental “X-plane” aircraft that may never leave restricted airspace near Edwards Air Force Base in California, NASA plans to eventually take the X-59 on a tour around the United States so residents of various cities and towns can provide feedback on the quieter sonic “thumps” it produces.

“Usually an X plane is kind of bare-bones—‘cobble it together from a bunch of parts from other airplanes and just demonstrate one thing,’” said Jim “Clue” Less, a NASA test pilot and aerospace engineer, in an interview with Ars. “We need to demonstrate that one thing, but then we need a plane that’s robust enough that we can fly it all over the place and gather that data.”

The move comes at a time when the US Congress has been advancing legislation that could legalize overland supersonic travel. That would reverse a 1973 ban implemented by the US Federal Aviation Administration, which was informed by the public backlash and noise complaints following US military tests of supersonic flights over Oklahoma City, Chicago, and St. Louis in the 1960s.

But even if the X-59 program shows that quieter supersonic travel is possible, any potential revival of commercial supersonic flights would still have to prove financially viable despite challenges such as massive fuel consumption costs... (MORE - details)

https://youtu.be/lmwKBaVFNps

https://www.youtube-nocookie.com/embed/lmwKBaVFNps]]> https://arstechnica.com/gadgets/2026/06/...onic-boom/

INTRO: More than two decades since the Concorde supersonic airliner last took to the skies, NASA has been flying an experimental aircraft designed to replace loud sonic booms with a quieter thump equivalent to a car door slamming shut 20 feet away. A successful NASA flight test program could influence the design of future supersonic airliners capable of flying overland routes without rattling buildings—and people’s nerves.

The Lockheed Martin X-59 Quesst—an acronym for Quiet SuperSonic Technology—first took flight late last year and recently began supersonic test flights. But unlike with many experimental “X-plane” aircraft that may never leave restricted airspace near Edwards Air Force Base in California, NASA plans to eventually take the X-59 on a tour around the United States so residents of various cities and towns can provide feedback on the quieter sonic “thumps” it produces.

“Usually an X plane is kind of bare-bones—‘cobble it together from a bunch of parts from other airplanes and just demonstrate one thing,’” said Jim “Clue” Less, a NASA test pilot and aerospace engineer, in an interview with Ars. “We need to demonstrate that one thing, but then we need a plane that’s robust enough that we can fly it all over the place and gather that data.”

The move comes at a time when the US Congress has been advancing legislation that could legalize overland supersonic travel. That would reverse a 1973 ban implemented by the US Federal Aviation Administration, which was informed by the public backlash and noise complaints following US military tests of supersonic flights over Oklahoma City, Chicago, and St. Louis in the 1960s.

But even if the X-59 program shows that quieter supersonic travel is possible, any potential revival of commercial supersonic flights would still have to prove financially viable despite challenges such as massive fuel consumption costs... (MORE - details)

https://youtu.be/lmwKBaVFNps

https://www.youtube-nocookie.com/embed/lmwKBaVFNps]]> <![CDATA[Electric car batteries last much longer than researchers and people thought. Why?]]> https://www.scivillage.com/thread-20707.html Wed, 24 Jun 2026 15:25:53 +0000 C C]]> https://www.scivillage.com/thread-20707.html https://www.sciencenorway.no/battery-car...hy/2675418

EXCERPT: Until recently, it was widely believed that the batteries would limit the lifespan of an electric car. Many people expected that replacing the large main battery would be extremely expensive if an electric car were to last as long as a fossil-fuel car. After all, smartphone batteries wear out relatively quickly.

So why were both consumers and researchers so mistaken? A widely discussed 2024 study by a group of researchers at Stanford University provides a clue. It showed that batteries in real-world electric cars can last up to 40 per cent longer than researchers had previously concluded from lab testing of similar batteries.

What on earth is the explanation for this? The researchers found that several factors are at play. Drivers constantly accelerate and brake. They take both short trips and long journeys. Most importantly, real-world electric cars spend a great deal of time parked, allowing their batteries long periods of rest.

All of this places less strain on electric car batteries than the steady, continuous operation researchers subjected them to in lab tests. The fact that frequent acceleration and braking could be beneficial for the battery was the exact opposite of what researchers had expected.

“We’ve not been testing EV batteries the right way,” researcher Simona Onori told Stanford Report... (MORE - details)]]> https://www.sciencenorway.no/battery-car...hy/2675418

EXCERPT: Until recently, it was widely believed that the batteries would limit the lifespan of an electric car. Many people expected that replacing the large main battery would be extremely expensive if an electric car were to last as long as a fossil-fuel car. After all, smartphone batteries wear out relatively quickly.

So why were both consumers and researchers so mistaken? A widely discussed 2024 study by a group of researchers at Stanford University provides a clue. It showed that batteries in real-world electric cars can last up to 40 per cent longer than researchers had previously concluded from lab testing of similar batteries.

What on earth is the explanation for this? The researchers found that several factors are at play. Drivers constantly accelerate and brake. They take both short trips and long journeys. Most importantly, real-world electric cars spend a great deal of time parked, allowing their batteries long periods of rest.

All of this places less strain on electric car batteries than the steady, continuous operation researchers subjected them to in lab tests. The fact that frequent acceleration and braking could be beneficial for the battery was the exact opposite of what researchers had expected.

“We’ve not been testing EV batteries the right way,” researcher Simona Onori told Stanford Report... (MORE - details)]]> <![CDATA[Scientists made a car paint so black it looks like a hole in reality]]> https://www.scivillage.com/thread-20670.html Fri, 19 Jun 2026 15:52:27 +0000 C C]]> https://www.scivillage.com/thread-20670.html https://gizmodo.com/scientists-made-a-ca...2000773588

INTRO: Vantablack inspires awe and disquiet. When BMW used this “blackest black” paint on one of its 2019 concept cars, the BMW X6, the German automaker noted that any surface coated in this carbon nanotube-based emulsion “loses its defining features to the human eye, with objects appearing two-dimensional.” The result, BMW added, “can be interpreted by the brain as staring into a hole or even a void.”

Vantablack never made it onto a commercial BMW vehicle, becoming instead a glare-reduction coating proposed for satellites and spookier applications, like stealth submarines. But that hasn’t deterred Singapore-based coatings developer Nipsea Group, whose R&D wing has now announced a more resilient blacker-than-black paint that it hopes will meet China’s burgeoning demand for deep-black luxury vehicles. Nipsea’s Vantablack-inspired composite, the researchers said, has proven capable of absorbing an average of 99.9% of all visible light wavelengths.

This new “ultra-black coating,” as the team wrote in its new paper for the journal Matter & Light, also remained “notably stable” even after humidity and water resistance tests—qualifying it for “application as ultra-black automotive coating.”

“In China, car color has become a key selling point,” Nipsea research chemist Zhiwei Liu said in a statement. “Deep black finishes have long been the premium choice and signature color for luxury cars due to their elegant appearance, powerful visual impact, and luxurious undertone.” (MORE - details)

https://youtu.be/akv3ip3kLng

https://www.youtube-nocookie.com/embed/akv3ip3kLng]]> https://gizmodo.com/scientists-made-a-ca...2000773588

INTRO: Vantablack inspires awe and disquiet. When BMW used this “blackest black” paint on one of its 2019 concept cars, the BMW X6, the German automaker noted that any surface coated in this carbon nanotube-based emulsion “loses its defining features to the human eye, with objects appearing two-dimensional.” The result, BMW added, “can be interpreted by the brain as staring into a hole or even a void.”

Vantablack never made it onto a commercial BMW vehicle, becoming instead a glare-reduction coating proposed for satellites and spookier applications, like stealth submarines. But that hasn’t deterred Singapore-based coatings developer Nipsea Group, whose R&D wing has now announced a more resilient blacker-than-black paint that it hopes will meet China’s burgeoning demand for deep-black luxury vehicles. Nipsea’s Vantablack-inspired composite, the researchers said, has proven capable of absorbing an average of 99.9% of all visible light wavelengths.

This new “ultra-black coating,” as the team wrote in its new paper for the journal Matter & Light, also remained “notably stable” even after humidity and water resistance tests—qualifying it for “application as ultra-black automotive coating.”

“In China, car color has become a key selling point,” Nipsea research chemist Zhiwei Liu said in a statement. “Deep black finishes have long been the premium choice and signature color for luxury cars due to their elegant appearance, powerful visual impact, and luxurious undertone.” (MORE - details)

https://youtu.be/akv3ip3kLng

https://www.youtube-nocookie.com/embed/akv3ip3kLng]]> <![CDATA[This jacket pulls drinking water from thin air]]> https://www.scivillage.com/thread-20632.html Sat, 13 Jun 2026 00:49:21 +0000 C C]]> https://www.scivillage.com/thread-20632.html https://www.eurekalert.org/news-releases/1131994

INTRO: Engineers at The University of Texas at Austin have developed a jacket that harvests drinking water directly from the air. The technology could benefit anyone who spends much time in areas without easy access to drinking water, from hobbyist hikers, campers and runners to agricultural workers, emergency responders and soldiers.

“Water harvesting from air is usually imagined as a stationary device such as a box, a panel or a large sorbent bed,” said Guihua Yu, chair professor of the Cockrell School of Engineering’s Walker Department of Mechanical Engineering and Texas Materials Institute and one of the leaders of the new research in Science Advances. “Here, we wanted to rethink the form of the technology. If the fabric itself can collect water from air, it opens a new direction for personal and portable water access.”

The textile incorporated into the jacket collects moisture and funnels it to detachable harvesting units. Those units are placed in a foldable collector piece and heated to produce the water.

The jacket produced between 400 and 900 milliliters of drinkable water per day, about 14 to 30 ounces, depending on humidity levels.

Compared with conventional water-harvesting materials, the textile showed a three- to 10-fold improvement at scale. By focusing on the fibers rather than building another bulky device, the researchers overcame a common problem in the field... (MORE - no ads)]]> https://www.eurekalert.org/news-releases/1131994

INTRO: Engineers at The University of Texas at Austin have developed a jacket that harvests drinking water directly from the air. The technology could benefit anyone who spends much time in areas without easy access to drinking water, from hobbyist hikers, campers and runners to agricultural workers, emergency responders and soldiers.

“Water harvesting from air is usually imagined as a stationary device such as a box, a panel or a large sorbent bed,” said Guihua Yu, chair professor of the Cockrell School of Engineering’s Walker Department of Mechanical Engineering and Texas Materials Institute and one of the leaders of the new research in Science Advances. “Here, we wanted to rethink the form of the technology. If the fabric itself can collect water from air, it opens a new direction for personal and portable water access.”

The textile incorporated into the jacket collects moisture and funnels it to detachable harvesting units. Those units are placed in a foldable collector piece and heated to produce the water.

The jacket produced between 400 and 900 milliliters of drinkable water per day, about 14 to 30 ounces, depending on humidity levels.

Compared with conventional water-harvesting materials, the textile showed a three- to 10-fold improvement at scale. By focusing on the fibers rather than building another bulky device, the researchers overcame a common problem in the field... (MORE - no ads)]]> <![CDATA[Artificial eyes could bring human-like sight to self-driving cars, robots]]> https://www.scivillage.com/thread-20611.html Tue, 09 Jun 2026 20:19:20 +0000 C C]]> https://www.scivillage.com/thread-20611.html https://www.eurekalert.org/news-releases/1130994

INTRO: Although self-driving cars and sophisticated robots use advanced cameras, computer algorithms and artificial intelligence (AI) to picture their surroundings, these artificial eyes struggle to remain reliable in mixed lighting conditions. A team of researchers, co-led by an engineer from Penn State, has proposed a solution that mimics the mechanics of the human eye to adapt from bright to dark light in seconds.

They did this by adjusting how one of the main electrical components used in these optical systems are built, employing a new design that swells or desorbs with water depending on the light levels present. The approach, detailed in a paper published in Nature Communications, illuminates a road to building systems that could potentially process light data faster and more adaptively than humans.

The improved components are known as memory resistors, or “memristors” — tiny electrical devices that can store information or data in a system, even if the original power source fueling the application is removed. These devices mimic the complex way neurons process and store data in the brain. Photomemristors are a type of memristor capable of sensing and collecting light information then translating it into an electrical current, a process that could more effectively power advanced cameras and optical systems.

According to Larry Cheng, James L. Henderson Jr. Memorial Associate Professor of Engineering Science and Mechanics at Penn State and co-corresponding author on the paper, traditional photomemristors are calibrated and optimized for consistent lighting conditions. Although this allows the systems to work well in both bright and dark environments, maintaining recognition accuracy in changing or mixed lighting can be challenging.

“Self-driving cars are exposed to a mixture of light levels in use — imagine the contrast of the dark sky with the bright headlights of other cars when driving at night,” Cheng explained. “It can be difficult for an artificial optical system to distinguish details, like the glow of a red light, in these mixed lightning conditions.”

Inside the human eye, a series of rod and cone cells helps adjust vision to different lighting conditions. Specific pigments in the rod cells allow the eye to distinguish details, even in the dark. In bright light, though, these pigments in the rod cells “bleach” before slowly regenerating, while the cone cells remain to allow the eye to discern contrasting details. The team theorized that this process, mimicked in a photomemristor, could offer monitoring more adaptive and accurate than traditional designs.

To achieve this, the team mainly built their photomemristors out of two different materials... (MORE - no ads)]]> https://www.eurekalert.org/news-releases/1130994

INTRO: Although self-driving cars and sophisticated robots use advanced cameras, computer algorithms and artificial intelligence (AI) to picture their surroundings, these artificial eyes struggle to remain reliable in mixed lighting conditions. A team of researchers, co-led by an engineer from Penn State, has proposed a solution that mimics the mechanics of the human eye to adapt from bright to dark light in seconds.

They did this by adjusting how one of the main electrical components used in these optical systems are built, employing a new design that swells or desorbs with water depending on the light levels present. The approach, detailed in a paper published in Nature Communications, illuminates a road to building systems that could potentially process light data faster and more adaptively than humans.

The improved components are known as memory resistors, or “memristors” — tiny electrical devices that can store information or data in a system, even if the original power source fueling the application is removed. These devices mimic the complex way neurons process and store data in the brain. Photomemristors are a type of memristor capable of sensing and collecting light information then translating it into an electrical current, a process that could more effectively power advanced cameras and optical systems.

According to Larry Cheng, James L. Henderson Jr. Memorial Associate Professor of Engineering Science and Mechanics at Penn State and co-corresponding author on the paper, traditional photomemristors are calibrated and optimized for consistent lighting conditions. Although this allows the systems to work well in both bright and dark environments, maintaining recognition accuracy in changing or mixed lighting can be challenging.

“Self-driving cars are exposed to a mixture of light levels in use — imagine the contrast of the dark sky with the bright headlights of other cars when driving at night,” Cheng explained. “It can be difficult for an artificial optical system to distinguish details, like the glow of a red light, in these mixed lightning conditions.”

Inside the human eye, a series of rod and cone cells helps adjust vision to different lighting conditions. Specific pigments in the rod cells allow the eye to distinguish details, even in the dark. In bright light, though, these pigments in the rod cells “bleach” before slowly regenerating, while the cone cells remain to allow the eye to discern contrasting details. The team theorized that this process, mimicked in a photomemristor, could offer monitoring more adaptive and accurate than traditional designs.

To achieve this, the team mainly built their photomemristors out of two different materials... (MORE - no ads)]]> <![CDATA[How the antihumanism movement is being outpaced by tech companies]]> https://www.scivillage.com/thread-20581.html Thu, 04 Jun 2026 22:32:59 +0000 C C]]> https://www.scivillage.com/thread-20581.html https://hedgehogreview.com/issues/humani...ts-authors

EXCERPTS: This area of scholarship is new enough that it doesn’t have a name yet, but I will call it Queer Chemical Studies (QCS). QCS begins by noting a phenomenon widely decried by environmental activists and studied by biologists, ecologists, and medical researchers: the impact of plastics, pesticides, and other synthetic materials in the environment on reproduction, human and animal...

[...] QCS scholars instead invite us ... to view “the queering of the body” brought about by environmental toxins “as opening on to new, and ecological, possibilities rather than reasserting a threatened heteronormative configuration.” The remarkable implication of this is that pervasive pollution can be recast as a vector of queer liberation. ... The QCS discovery that queer liberation is being realized by the petrochemical industry may seem like a niche matter, but it is emblematic of a broader impasse faced by the academic humanities.

For the past half century, humanists have deconstructed, subverted, problematized, and queered every normativity and supremacy they could find. The ultimate target of this systematic critical project was, paradoxically, the value that originally founded and gave shape to their disciplines: humanism.

The dismantling of “Man” [antihumanism] was the impetus for some of the founding polemical statements of what came to be called “theory.” In recent decades, this project was reinvigorated in the form of “posthumanism” and the “posthumanities,” which launched an attack on the most centric of all centrisms: anthropocentrism. In line with this project, QCS discards any idea of a fixed, natural human essence to which synthetic substances pose a threat.

The early parts of the story of how the humanities turned against “the human” are well told in two intellectual histories...

[...] But what if academic antihumanists turn out to be dispensable to the realization of antihumanist goals? That is the unsettling conclusion QCS points us to, without acknowledging it. ... I am referring to the creation of generative artificial intelligence and the pursuit of artificial general intelligence (AGI) and artificial superintelligence (ASI) by a number of the world’s most highly valued companies.

Like so many humanities scholars before them, the entrepreneurs and engineers pursuing AGI openly seek to “decenter the human” and explore the possibilities of nonhuman agency. But their plan for doing so has far vaster resources behind it than all academic humanities departments combined...

[...] In other words, the humanities have spent half a century decentering the human but now face steep competition in that effort from tech companies with more than trillion-dollar valuations... (MORE - details)]]> https://hedgehogreview.com/issues/humani...ts-authors

EXCERPTS: This area of scholarship is new enough that it doesn’t have a name yet, but I will call it Queer Chemical Studies (QCS). QCS begins by noting a phenomenon widely decried by environmental activists and studied by biologists, ecologists, and medical researchers: the impact of plastics, pesticides, and other synthetic materials in the environment on reproduction, human and animal...

[...] QCS scholars instead invite us ... to view “the queering of the body” brought about by environmental toxins “as opening on to new, and ecological, possibilities rather than reasserting a threatened heteronormative configuration.” The remarkable implication of this is that pervasive pollution can be recast as a vector of queer liberation. ... The QCS discovery that queer liberation is being realized by the petrochemical industry may seem like a niche matter, but it is emblematic of a broader impasse faced by the academic humanities.

For the past half century, humanists have deconstructed, subverted, problematized, and queered every normativity and supremacy they could find. The ultimate target of this systematic critical project was, paradoxically, the value that originally founded and gave shape to their disciplines: humanism.

The dismantling of “Man” [antihumanism] was the impetus for some of the founding polemical statements of what came to be called “theory.” In recent decades, this project was reinvigorated in the form of “posthumanism” and the “posthumanities,” which launched an attack on the most centric of all centrisms: anthropocentrism. In line with this project, QCS discards any idea of a fixed, natural human essence to which synthetic substances pose a threat.

The early parts of the story of how the humanities turned against “the human” are well told in two intellectual histories...

[...] But what if academic antihumanists turn out to be dispensable to the realization of antihumanist goals? That is the unsettling conclusion QCS points us to, without acknowledging it. ... I am referring to the creation of generative artificial intelligence and the pursuit of artificial general intelligence (AGI) and artificial superintelligence (ASI) by a number of the world’s most highly valued companies.

Like so many humanities scholars before them, the entrepreneurs and engineers pursuing AGI openly seek to “decenter the human” and explore the possibilities of nonhuman agency. But their plan for doing so has far vaster resources behind it than all academic humanities departments combined...

[...] In other words, the humanities have spent half a century decentering the human but now face steep competition in that effort from tech companies with more than trillion-dollar valuations... (MORE - details)]]>