Researchers have developed a new kind of lidar system that simultaneously measures the location, speed and material properties of objects in a scene. This type of information could be useful for applications such as robotics, autonomous driving and remote sensing.
Lidar uses laser pulses to measure distances and create highly detailed 3D maps of objects and terrain. However, most commercial lidar systems, such as those used in autonomous cars, primarily measure distance.
“Although some emerging lidar technologies can also measure velocity, real-world perception often requires understanding an object’s surface as well,” said Dongyu Du from the University of Toronto in Canada. “Our new system uses a single measurement at each scanned point to capture millimeter-accurate distance, velocity and surface material while using eye-safe laser power.”
Social media is being consumed by AI from the inside out.
Over half of all new written content online is now AI-generated, and more than half of all internet traffic is bots.
Facebook’s most-viewed images are AI slop, YouTube recommends brainrot to new users, and global content farms churn out synthetic shock content for pennies.
The platforms aren’t fighting it because engagement is engagement, whether it comes from humans or machines.
Korean researchers have secured flexible electronic skin technology that can be fabricated directly in the field. This achievement has increased the feasibility of commercializing electronic skin for use in various fields, including robots and wearable devices.
In collaboration with the research team of Professor Ahn Jun Seong from the Department of Control and Instrumentation Engineering at Korea University’s Sejong Campus, the Electronics and Telecommunications Research Institute (ETRI) has developed an in-situ process-based electronic skin fabrication technology capable of producing large-area multimodal sensors without a clean room, a dedicated semiconductor processing facility.
The research is published in npj Flexible Electronics.
If you’ve been in tech circles lately, you’ve probably heard of “Vibecoding.” Most people treat it like an industry joke—lazy developers throwing sloppy prompts at a screen until an app magically pops out. To traditional gatekeepers, it looks like dangerous, uncompilable chaos.
The “vibe” isn’t a loose, careless emotion. It’s data. Specifically, it is the human-facing interface for what advanced computer science calls Intent Orchestration.
I just published a definitive deep dive into the actual math, physics, and mechanics under the hood of this movement. We break down exactly why the traditional “Filing Cabinet” architecture of multi-agent AI is fundamentally broken, and how Holographic AI Frameworks are the solution.
We are stepping into an era of Decentralized Coherence that liberates creators from traditional development bottlenecks, transforming your role from a low-level syntax translator into a High-Dimensional Intent Architect.
The era of manual syntax is drawing to a close. The computer has finally spent enough time engineering its systems to understand our language.
But make no mistake—if your structural thinking is sloppy, your application will still fail.
The race toward an imminent intelligence explosion has escalated from a sci-fi thought experiment into a high-stakes global debate.
Accelerating progress across model reasoning and compute infrastructure forces a critical question: is Artificial General Intelligence already arriving?
Silicon Valley insiders frequently claim human-level AI has passed us by, though critics warn these declarations are heavily warped by financial incentives.
If an AI system successfully achieves recursive self-improvement, the resulting technological singularity could compress centuries of human progress into mere hours.
A best-case takeoff promises staggering rewards like clean fusion energy, automated economic abundance, and radical medical breakthroughs that extend human lifespans indefinitely.
And don’t assume “cheaper” means “worse.” On the SWE-bench Pro—the gold standard benchmark for coding agent capabilities—Zhipu’s GLM 5.2 scored a 62.1, beating OpenAI’s GPT-5.5 at 58.6.
Running the same AI workload through Anthropic’s Claude costs $4,811. Running it through Zhipu’s GLM model costs $544. That’s nearly a 9x price difference for equivalent work, and enterprise customers have started doing the math.
Chinese AI companies are undercutting OpenAI and Anthropic so aggressively on price that the two most prominent US AI firms are now scrambling to respond. OpenAI is reportedly considering major token price cuts, and Anthropic is expected to follow. The timing could not be worse: both companies are preparing for public market debuts.
A comparison of workload costs across leading AI models paints a stark picture. Anthropic’s Claude rings in at $4,811 per workload. OpenAI’s ChatGPT comes in lower at $3,357, but still far above the Chinese alternatives. DeepSeek prices the same workload at $1,071. Moonshot’s Kimi model does it for $948. And Zhipu’s GLM sits at just $544.
In the neonatal intensive care unit, the most fragile patients in medicine are often the most heavily wired. Premature babies, some weighing less than a pound, can be tethered to a tangle of cables, monitors and sensors. Each blood draw to check sugar levels or electrolytes means another needle, another bandage, another moment of stress for an infant whose skin is still forming.
A team of researchers from Tufts University’s Silklab, Helmholtz Munich, Ludwig Maximilian University (LMU) Munich and the Technical University of Munich have developed a radically gentler alternative: a featherlight, silk-based sticker, smaller than a coin, that quietly reads four critical health signals at once just by changing color.
The work, published in ACS Sensors, describes a wearable patch that captures temperature, pH, sodium and glucose from the wisps of fluid that pass naturally through a baby’s still-developing skin. An AI system reads the patch’s color shifts through any standard camera, even in the dim, humid, hard-to-photograph environment of an incubator, and translates them into precise numbers a clinician can act on.
Google has unveiled a quantum computing breakthrough that could reshape the future of artificial intelligence, cryptography, medicine, and global technology. But does this really mean AI is becoming obsolete?
In this video, we break down Google’s Willow quantum chip, the revolutionary error-correction milestone it achieved, and why experts believe this could be one of the biggest advances in computing history. We also explain what the headlines get wrong, how quantum computing actually differs from AI, and why the future is likely to be a combination of both technologies rather than a competition.
You’ll discover: • What makes Google’s Willow chip so significant. • How quantum computers differ from classical AI • Why the \.
Photonic chips are no longer just a lab experiment, and in this video, we break down why a new photonic NPU could become one of the biggest shifts in AI hardware, data centers, and supercomputing. Instead of using electricity and transistors like a traditional GPU, this new class of processor uses light to perform computation, opening the door to dramatically faster matrix math, far lower energy use, and almost no on-chip heat. From the growing power crisis in AI infrastructure to the limits of silicon, Moore’s Law, and the memory wall, this story explores why photonic computing is suddenly becoming one of the most important technologies to watch. If you’re interested in photonic chips, optical computing, AI chips, NPUs, GPUs, data center efficiency, and the future of semiconductor technology, this video gives you the full picture. We also explore what makes these chips different from conventional silicon. The video covers photons instead of electrons, wavelength-division multiplexing, optical interference, thin-film lithium niobate, and why companies like Q.ANT are now deploying photonic processors in real supercomputing environments instead of just talking about them on research slides. We look at Q.ANT’s Native Processing Unit at the Leibniz Supercomputing Centre in Germany, the jump from first-generation to second-generation performance, and why benchmarks showing huge gains in throughput, AI inference, and energy efficiency are making people take photonic hardware much more seriously. More importantly, this is not just another faster chip story. It is about whether the AI industry can keep scaling without running straight into an energy wall. With GPUs demanding more power, more cooling, and more data movement every year, photonic co-processors may be the first real alternative that changes the economics of compute itself. The technology still has serious challenges, especially memory and optical-electrical conversion, but this may be the moment when computing with light stopped sounding like science fiction and started becoming real infrastructure.
From cosmic rays to solar storms, space travel is a radiation gauntlet… but water may be the simplest, smartest solution. Discover how future starships might turn their life-support systems into life-saving armor.
Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthur. Watch my exclusive video Nearby Supernovae: https://nebula.tv/videos/isaacarthur–… out Gods & Monsters: https://nebula.tv/curiousarchive/gods… 🛒 SFIA Merchandise: https://isaac-arthur-shop.fourthwall… 🌐 Visit our Website: http://www.isaacarthur.net ❤️ Support us on Patreon: / isaacarthur ⭐ Support us on Subscribestar: https://www.subscribestar.com/isaac-a… 👥 Facebook Group: / 1,583,992,725,237,264 📣 Reddit Community: / isaacarthur 🐦 Follow on Twitter / X: / isaac_a_arthur 💬 SFIA Discord Server: / discord Credits: Fishbowl Starships Water As Shielding Episode 721; June 1, 2025; Nebula Exclusive Written, Produced, & Narrated by: Isaac Arthur Graphics: Bryan Versteeg, Jeremy Jozwik, Udo Schroeter Select imagery/video supplied by Getty Images Music Courtesy of Epidemic Sound http://epidemicsound.com/creator Taras Harkavyi, “Alpha and…” Chris Zabriskie, “Unfoldment, Revealment”, “A New Day in a New Sector” “Oxygen Garden”, “Wonder Cycle” Stellardrone, “Red Giant”, “Billions and Billions” Chapters: 0:00 Intro 1:45 The Threat — Radiation In Space 2:36 Galactic Cosmic Rays (GCRs) 3:44 Solar Particle Events (SPEs) 4:16 Van Allen Belt Radiation 5:19 Radiation’s Impact on Humans and Equipment 8:18 Radiation Shielding Basics 9:18 Water as a Radiation Shield 11:19 Effectiveness of Water 15:42 Difficulties Using Water 17:29 Beyond Water: Alternative Radiation Shielding Methods 17:59 Metallic Shielding 18:58 Regolith & Asteroid-Based Shielding 20:27 Hydrogen-Rich Polymers 21:22 Graphene, CNTs, and BNNTs 23:54 Active Shielding: Magnetic & Plasma Barriers 24:49 Fusion Fuel Shielding 25:27 Hybrid Shielding Approaches 28:16 God & Monsters 29:26 The Future of Radiation Shielding 30:00 Smart & Self-Healing Shielding 31:29 Artificial Magnetospheres 33:22 Biological Adaptation 35:35 Radiation-Resistant AI & Robotics 37:45 The Future of Space Radiation Protection 38:55 The Future of Water-Based Shielding. Check out Gods \& Monsters: https://nebula.tv/curiousarchive/gods…
🛒 SFIA Merchandise: https://isaac-arthur-shop.fourthwall… 🌐 Visit our Website: http://www.isaacarthur.net. ❤️ Support us on Patreon: / isaacarthur. ⭐ Support us on Subscribestar: https://www.subscribestar.com/isaac-a… 👥 Facebook Group: / 1583992725237264 📣 Reddit Community: / isaacarthur. 🐦 Follow on Twitter / X: / isaac_a_arthur. 💬 SFIA Discord Server: / discord. Credits: Fishbowl Starships Water As Shielding. Episode 721; June 1, 2025; Nebula Exclusive. Written, Produced, \& Narrated by: Isaac Arthur. Graphics: Bryan Versteeg, Jeremy Jozwik, Udo Schroeter. Select imagery/video supplied by Getty Images. Music Courtesy of Epidemic Sound http://epidemicsound.com/creator. Taras Harkavyi, \
