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2025-11-15 17:39:58

The post This Week’s Awesome Tech Stories From Around the Web (Through November 15) appeared first on SingularityHub.

2025-11-15 04:06:11

Robotic surgery has dramatically improved surgical precision, but it could also help surgeons treat people on the other side of the world. A surgeon in Florida has now used a robot to remove a simulated brain clot from a cadaver in Scotland, with near-instant feedback across 4,000 miles.

In the US, someone has a stroke roughly every 40 seconds, totally more than 795,000 cases each year and costing the health system more than $56 billion annually, according to the Centers for Disease Control and Prevention.

Ischemic strokes block blood flow to the brain and account for 87 percent of cases. These strokes often require an emergency surgery called a thrombectomy to remove the offending blood clot. However, the procedure requires highly skilled specialists and advanced imaging setups, which means they’re only available to a fraction of stroke patients.

That could soon change thanks to a breakthrough experiment carried out by doctors on either side of the Atlantic. Ricardo Hanel, a neurosurgeon at the Baptist Medical Center in Jacksonville, Florida used a surgical robot to carry out a thrombectomy on a human cadaver at the University of Dundee in Scotland.

“To operate from the US to Scotland with a 120 millisecond (blink of an eye) lag is truly remarkable,” Hanel said in a press release.

“Tele neurointervention [robotic surgery at a distance] will allow us to decrease the gap and further our reach to provide one of the most impactful procedures in humankind.”

The robotic system used in the experiment was developed by Lithuanian company Sentante. The system translates a surgeon’s hand movements into fine robotic control of the standard tools used in the procedure. It also provides haptic feedback, giving the surgeon the same sensations they would feel if doing the procedure by hand.

This feedback makes it possible for the operators to recognize subtle but crucial cues—such as the softness of clot material or the transition into more delicate vessels in the brain. Study leader Iris Grunwald at the University of Dundee also used the robot to carry out a thrombectomy on a cadaver from a remote site within the same hospital, as a precursor to the transatlantic experiment.

“It is remarkable to feel the same fine control and resistance through a robotic interface as during a live procedure,” she said in the press release. “Sentante’s robotic platform redefines what is possible in endovascular treatment today.”

The technology could greatly expand access to this life saving procedure, as it only requires a medical professional trained to gain access to the patient’s arteries before a neurosurgical specialist can take over remotely. The robotic system can also be wheeled to a patient’s bedside within minutes—a critical capability given that every minute counts when it comes to strokes.

“For an ischemic stroke, the difference between walking out of hospital and a lifetime of disability can be just two to three hours,” Edvardas Satkauskas, co-founder and CEO of Sentante, said in the press release.

“Today, patients are often transported long distances to reach one of a limited number of thrombectomy centers. With Sentante, the specialist comes to the patient over a secure network and performs the entire procedure remotely—with the same tactile feel and control they have at the bedside.”

Of course, the experiments took place on cadavers rather than living patients, and bridging the gap could still be tricky. Also, a reliable internet connection—plus good backup plans should it fail—will be as crucial as a smoothly operating robot.

But these experiments suggest that your chances of surviving a stroke may soon no longer be reliant on how close you are to the nearest specialist hospital.

The post In Wild Experiment, Surgeon Uses Robot to Remove Blood Clot in Brain 4,000 Miles Away appeared first on SingularityHub.

2025-11-14 01:48:00

Artificial intelligence is increasingly being used to preserve the voices and stories of the dead. From text-based chatbots that mimic loved ones to voice avatars that let you “speak” with the deceased, a growing digital afterlife industry promises to make memory interactive and, in some cases, eternal.

In our research, recently published in Memory, Mind & Media, we explored what happens when remembering the dead is left to an algorithm. We even tried talking to digital versions of ourselves to find out.

“Deathbots” are AI systems designed to simulate the voices, speech patterns, and personalities of the deceased. They draw on a person’s digital traces—voice recordings, text messages, emails, and social media posts—to create interactive avatars that appear to “speak” from beyond the grave.

As the media theorist Simone Natale has said, these “technologies of illusion” have deep roots in spiritualist traditions. But AI makes them far more convincing and commercially viable.

Our work is part of a project called Synthetic Pasts, which explores the impact technology has on the preservation of personal and collective memory. For our study, we looked at services that claim to preserve or recreate a person’s voice, memories, or digital presence using AI. To understand how they work, we became our own test subjects. We uploaded our own videos, messages, and voice notes, creating “digital doubles” of ourselves.

In some cases, we played the role of users preparing our own synthetic afterlives. In others, we acted as the bereaved trying to talk to a digital version of someone who has passed away.

What we found was both fascinating and unsettling. Some systems focus on preserving memory. They help users record and store personal stories, organized by theme, such as childhood, family, or advice for loved ones. AI then indexes the content and guides people through it, like a searchable archive.

Others use generative AI to create ongoing conversations. You upload data about a deceased person—messages, posts, even voice samples – and the system builds a chatbot that can respond in their tone and style. It uses a subset of AI called machine learning (which improves through practice) to make its avatars evolve over time.

Some present themselves as playful (“host a séance with AI”), but the experience can feel eerily intimate. All the platforms claim to offer an “authentic” emotional connection. Yet the more personalization we attempted, the more artificial it felt.

When prompted by these systems we provided more information about ourselves, only to have the bot repeat the exact phrasing we had used in stiff, scripted replies. At times, the tone was incongruous, such as when cheerful emojis or upbeat phrasing appeared even when discussing death—a clear reminder that algorithms are poor at handling the emotional weight of loss:

Oh hun… it (the death) is not something I’d wish for anyone to dwell on. It’s all a bit foggy now, to be honest. Let’s chat about something a bit cheerier, yeah?

The more archival-based tools we tested offered a calmer experience but also imposed rigid categories and limited nuance. As digital media scholar Andrew Hoskins has observed, memory in the age of AI becomes “conversational”—shaped by interactions between human and machine. But in our experiments, those conversations often felt flat, exposing the limits of synthetic intimacy:

Human: You were always so encouraging and supportive. I miss you.

Deathbot: I’m right here for you, always ready to offer encouragement and support whenever you need it. And I miss you too… Let’s take on today together, with positivity and strength.

Behind these experiences lies a business model. These are not memorial charities, they are tech startups. Subscription fees, “freemium” tiers, and partnerships with insurers or care providers reveal how remembrance is being turned into a product.

As the philosophers Carl Öhman and Luciano Floridi have argued, the digital afterlife industry operates within a “political economy of death,” where data continues to generate value long after a person’s life ends.

Platforms encourage users to “capture their story forever,” but they also harvest emotional and biometric data to keep engagement high. Memory becomes a service—an interaction to be designed, measured, and monetized. This, as the professor of technology and society Andrew McStay has shown, is part of a wider “emotional AI” economy.

Digital Resurrection?

The promise of these systems is a kind of resurrection—the reanimation of the dead through data. They offer to return voices, gestures, and personalities, not as memories recalled but as presences simulated in real time. This kind of “algorithmic empathy” can be persuasive, even moving, yet it exists within the limits of code and quietly alters the experience of remembering, smoothing away the ambiguity and contradiction.

These platforms demonstrate a tension between archival and generative forms of memory. All platforms, though, normalize certain ways of remembering, placing privilege on continuity, coherence, and emotional responsiveness, while also producing new, data-driven forms of personhood.

As the media theorist Wendy Chun has observed, digital technologies often conflate “storage” with “memory,” promising perfect recall while erasing the role of forgetting—the absence that makes both mourning and remembering possible.

In this sense, digital resurrection risks misunderstanding death itself: replacing the finality of loss with the endless availability of simulation, where the dead are always present, interactive, and updated.

AI can help preserve stories and voices, but it cannot replicate the living complexity of a person or a relationship. The “synthetic afterlives” we encountered are compelling precisely because they fail. They remind us that memory is relational, contextual, and not programmable.

Our study suggests that while you can talk to the dead with AI, what you hear back reveals more about the technologies and platforms that profit from memory—and about ourselves—than about the ghosts they claim we can talk to.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post Can You Really Talk to the Dead Using AI? We Tried Out ‘Deathbots’ So You Don’t Have To appeared first on SingularityHub.

2025-11-11 23:00:00

One the biggest challenges for quantum computers is the incredibly short time that qubits can retain information. But a new qubit from Princeton University lasts 15 times longer than industry standard versions in a major step towards large-scale, fault-tolerant quantum systems.

A major bottleneck for quantum computing is decoherence—the rate at which qubits lose stored quantum information to the environment. The faster this happens, the less time the computer has to perform operations and the more errors are introduced to the calculations.

While companies and researchers are developing error-correction schemes to mitigate this problem, qubits with greater stability could be a more robust solution. Trapped-ion and neutral-atom qubits can have coherence times on the order of seconds, but the superconducting qubits used by companies like Google and IBM remain below the 100-microsecond threshold.

These so-called “transmon” qubits have other advantages such as faster operation speeds, but their short shelf life remains a major disadvantage. Now a team from Princeton has designed novel transmon qubits with coherence times of up to 1.6 milliseconds—15 times longer than those used in industry and three times longer than the best lab experiment.

“This advance brings quantum computing out of the realm of merely possible and into the realm of practical,” Princeton’s Andrew Houck, who co-led the research, said in a press release. “Now we can begin to make progress much more quickly.”

The team’s new approach, detailed in a paper in Nature, tackles a long-standing problem in the design of transmon qubits. Tiny surface defects in the metal used to make them, typically aluminium, can absorb energy as it travels through the circuit, resulting in errors in the underlying computations.

The new qubit instead uses the metal tantalum, which has far fewer of these defects. The researchers had already experimented with this material as far back as 2021, but earlier versions were built on top of a layer of sapphire. The researchers realized the sapphire was also leading to significant energy loss and so replaced it with a layer of silicon, which is commercially available at extremely high purity.

Creating a clean enough interface between the two materials to maintain superconductivity is challenging, but the team solved the problem with a new fabrication process. And because silicon is the computing industry’s material of choice, the new qubits should be easier to mass-produce than earlier versions.

To prove out the new process, the researchers built a fully functioning quantum chip with six of the new qubits. Crucially, the new design is similar enough to the qubits used by companies like Google and IBM that it could easily slot into existing processors to boost performance, the researchers say.

This could chip away at the main barrier preventing existing quantum computers from solving larger problems—the fact that short coherence times mean qubits are overwhelmed by errors before they can do any useful calculations.

The process of getting the design from the lab bench to the chip foundry is likely to be long and complicated though, so it’s unclear if companies will switch to this new qubit architecture any time soon. Still, the research has made dramatic progress on one of the biggest challenges holding back superconducting quantum computers.

The post Record-Breaking Qubits Are Stable for 15 Times Longer Than Google and IBM’s Designs appeared first on SingularityHub.

2025-11-11 01:44:09

Like the seeds of a forest, a few cells in embryos eventually sprout into an ecosystem of brain cells. Neurons get the most recognition for their computing power. But a host of other cells provides nutrition, clears the brain of waste, and wards off dangers, such as toxic protein buildup or inflammation.

This rich diversity underlies our ability to process information, transforming perception of the world and our internal dialogues into thoughts, emotions, memories, and decisions. Mimicking the brain could potentially lead to energy-efficient computers or AI systems. But we’re still decoding how the brain works.

One way to understand a machine is to first examine its parts. The landmark project BRAIN Initiative Cell Atlas Network (BICAN), launched in 2022, has parsed the brains of multiple species and compiled a census of adult brain cells with unprecedented resolution.

But brains are not computers. Their components aren’t engineered and glued on. They develop and interact cohesively over time.

Building on previous work, the BICAN consortium has now released results that peek inside the developing brain. By tracking genes and their expression in the cells of developing human and mouse brains, the researchers have built a dynamic picture of how the brain constructs itself.

This herculean effort could help scientists unravel the causes of neurodevelopmental disorders. In one study, led by Arnold Kriegstein at the University of California, San Francisco, scientists found brain stem cells that are potentially co-opted to form a deadly brain cancer in adulthood. Other studies shed light on imbalances between excitatory and inhibitory neurons—these ramp up or tone down brain activity, respectively—which could contribute to autism and schizophrenia.

“Many brain diseases begin during different stages of development, but until now we haven’t had a comprehensive roadmap for simply understanding healthy brain development,” said Kriegstein in a press release. “Our map highlights the genetic programs behind the growth of the human brain that go awry during specific forms of brain dysfunction.”

Shifting Landscape

Over a century ago, the first neuroscientists used brain cell shapes to categorize their identities. BICAN collaborators have a much larger arsenal of tools to map the brain’s cells.

A key technology called single-cell spatial transcriptomics detects which genes are turned on in cells at any given time. The results are then combined with the cells’ physical location in the brain. The result is a gene expression “heat map” that provides clues about a cell’s lineage and final identity. Like genealogical tracking, the technology traces the heritage of different types of brain cells and when they emerge while at the same time providing their physical address.

Like other organs, the brain grows from stem cells.

In early developmental stages, stem cells are nudged into different fates: Some turn into neurons, some turn into other cell types. So far, no single technology can “film” their journey. But BICAN’s new releases measuring gene expression through development offer a glimpse.

In one tour-de-force study, Kriegstein and team used a technique that maps gene variants to single cells during multiple stages of development. Many variants were previously linked to neurodevelopmental disorders, including autism, but their biological contribution remained mysterious.

The team gathered 38 donated human cortex samples—the outermost part of the brain—that spanned all three trimesters of pregnancy, after birth, and early adolescence.

They then grouped individual cells using gene expression data across samples. They found roughly 30 different types of cells that emerge during brain development, including excitatory and inhibitory neurons, supporting cells such as glia, and immune cells called microglia.

Some were linked to a single source. This curious cell type, dubbed tripotential intermediate progenitor cells, spawned an inhibitory neuron, star-shaped glia, and brain cells that wrap around neurons as protective sheathes of electrical insulation. The latter break down in neurological diseases like multiple sclerosis, resulting in fatigue, pain, and memory problems.

Many genes related to autism were turned on in immature neurons as they began their brain-wiring journey. Gene mutations, environmental influences, and other disruptions could interfere with their growth.

“These programs of gene expression became active when young neurons were still migrating throughout the growing brain and figuring out how to build connections with other neurons,” said study author Li Wang. “If something goes wrong at this stage, those maturing neurons might become confused about where to go or what to do.”

The mother cells also have a dark side. Scientists have long thought that glioblastoma, a fatal brain cancer, stems from multiple types of neural precursor cells. Because mother cells, marked by their distinctive gene expression profiles, develop into all three types of cells involved in the cancer, they’re essentially cancer stem cells that could be targeted for future treatments.

“By understanding the context in which one stem cell produces three cell types in the developing brain, we could be able to interrupt that growth when it reappears during cancer,” said Wang.

A Wealth of Data

Other BICAN studies also zeroed in on inhibitory neurons.

The authors of one hunted down a group of immature cells that shifted from making excitatory neurons to inhibitory ones during the middle of gestation, proving to be a balance between both forces. In another, in mice, researchers followed inhibitory neurons as they diversified and spread across the developing brain. More subtypes with unique gene expression profiles appeared in the cortex compared to deeper regions, which are more evolutionarily ancient.

Other studies investigated gene expression in neurodevelopment and how changes can lead to inflammation. Environmental influences such as social interactions played a role, especially in forming brain circuits tailored to gauging others’ behaviors. In developing mice, several genes related to social demands abruptly changed their activity during developmental milestones, including puberty.

Some cell types were shape-shifters. In mice, an immune challenge briefly changed microglia—the brain’s immune cells—back into a developmental-like state, suggesting these cells have the ability to turn back the clock.

The collection of studies only skims the surface of what BICAN’s database offers. Although the project mainly focused on the cortex, ongoing initiatives are detailing a cell atlas of the entire developing brain across dozens of timepoints and multiple species.

“Taken together, this collection from the BICAN turns the static portrait of cell types into a dynamic story of the developing brain,” wrote Emily Sylwestrak at the University of Oregon, who was not involved in the studies.

The post Scientists Map the Brain’s Construction From Stem Cells to Early Adolescence appeared first on SingularityHub.

2025-11-08 23:00:00

The post This Week’s Awesome Tech Stories From Around the Web (Through November 8) appeared first on SingularityHub.