Elon Musk predicts that programming will "die" by the end of the year due to AI. @science

💻 Classical Computers Just Overturned a Major Quantum Advantage Claim

In 2025, researchers used D-Wave’s Advantage2 quantum annealer to simulate the dynamics of hundreds of interacting qubits — and argued that the task was beyond the reach of classical computers.

A team from the Flatiron Institute and Boston University has now reproduced those results using classical algorithms and relatively modest hardware. Some of the initial calculations even ran on a personal laptop.

The challenge involved quantum spin glasses: disordered systems in which hundreds of interacting qubits evolve across two- and three-dimensional lattices. Tracking the complete quantum wave function directly would require an amount of memory that grows exponentially with the number of qubits.

The researchers avoided that explosion using tensor networks — mathematical structures that compress a quantum state by retaining its most important correlations.

Think of it as a highly specialized zip file for quantum information.

They combined tensor networks with belief propagation, an algorithm developed in the 1980s and recently adapted for quantum systems. The calculations were implemented using ITensor, a high-performance tensor-network software library.

The classical simulations:

• reproduced the quantum computer’s results
• matched theoretical predictions and exact benchmarks
• scaled to systems containing hundreds of qubits
• captured quantum dynamics in complex 3D lattice geometries

There is one important caveat: the entire study was not completed on an ordinary laptop. A laptop was sufficient for some early calculations, while the largest simulations required more powerful conventional processors and GPUs.

Still, the result directly challenges the earlier claim that this particular problem was beyond classical computation.

It does not mean quantum computers are useless. It means that demonstrating genuine quantum advantage requires beating the best classical algorithms available — not merely the best ones researchers happened to test previously.

The boundary between classical and quantum computing is not fixed. Every improvement in quantum hardware gives classical researchers a new target, while every better classical algorithm raises the bar for quantum advantage.

Sometimes the strongest competitor to a quantum computer is not another quantum computer.

It is better mathematics.

📄 Paper: Dynamics of disordered quantum systems with two- and three-dimensional tensor networks
https://www.science.org/doi/10.1126/science.adx2728

#QuantumComputing #Physics #TensorNetworks #ClassicalComputing #QuantumPhysics

🌿 Ordinary Moss Produces Electrical Waves That Travel Across Its Tissue

Moss may look like one of nature’s quieter creations. Electrically, however, it appears to be surprisingly active.

Computer scientist Andy Adamatzky inserted electrodes into cushions of the common moss Brachythecium rutabulum and recorded their electrical activity continuously for 178 hours.

The moss produced several distinct patterns: rapid spikes, slower rhythmic oscillations, and very slow depolarization waves. Some signals appeared first at one electrode and later at another, suggesting that electrical activity was travelling across the tissue rather than occurring everywhere simultaneously.

Some spikes resembled action potentials and neuron-like spike trains. But resemblance is not equivalence: moss has no neurons, no brain, and the study provides no evidence that it thinks or possesses anything resembling consciousness.

What it may show is that a moss cushion behaves as a distributed, electrically connected system. One day, such living networks could potentially be used in biohybrid sensors, responsive building materials, or unconventional computing.

The interpretation remains preliminary. For now, the moss is not solving equations — but it may be coordinating electrical activity beneath our feet.

Could future computers be partly grown rather than manufactured?

📄 Royal Society Open Science
DOI: 10.1098/rsos.252341

#PlantBiology #Moss #BioComputing #LivingMaterials #UnconventionalComputing

🦷 Scientists May Have Found a Way to Regrow Tooth Enamel

For decades, dentists have faced a frustrating reality: once tooth enamel is lost, it never naturally grows back. Researchers at the University of Nottingham may have found a way to change that.

In a study published in Nature Communications, the team developed a protein-based biomaterial that mimics the way enamel forms during early childhood—the only time our bodies naturally produce it.

Instead of simply coating the tooth like conventional treatments, the material acts as a microscopic scaffold. It penetrates tiny defects in damaged enamel, then recruits calcium and phosphate ions from saliva, guiding them to grow new enamel crystals that integrate seamlessly with the existing tooth.

In laboratory tests on extracted human teeth, the regenerated enamel closely matched the natural material in both structure and mechanical performance. It also withstood simulated brushing, chewing, and repeated exposure to acidic conditions, suggesting it could be durable enough for everyday use.

Unlike today’s fluoride treatments—which mainly slow further damage—this approach is designed to restore enamel rather than simply protect what’s left.

The researchers have launched a startup, Mintech-Bio, to commercialize the technology and hope to bring the first products toward clinical use in the coming year. However, human clinical trials are still needed before the treatment can become widely available.

If future trials confirm these results, dentistry could gradually shift from “drill and fill” to actually rebuilding damaged teeth.

📖 Source: Nature Communications (2025)
https://www.nature.com/articles/s41467-025-64982-y

#Dentistry #Biomaterials #Enamel #RegenerativeMedicine #Science

🧬 AI Discovers a Natural Peptide That Could Rival Ozempic

Researchers at Stanford Medicine have used artificial intelligence to identify a naturally occurring human peptide that suppresses appetite and promotes weight loss in mice—while avoiding the major side effects commonly associated with GLP-1 drugs like Ozempic.

The newly discovered molecule, called BRP, is only 12 amino acids long. Yet in early laboratory experiments, it activated appetite-regulating neurons far more strongly than existing GLP-1 peptides.

Unlike semaglutide, which acts on receptors throughout the brain, gut, pancreas, and other tissues, BRP appears to target primarily the hypothalamus—the brain region responsible for regulating hunger and metabolism. That more focused mechanism may explain why researchers observed no signs of nausea, constipation, anxiety, or muscle loss in the animal studies.

The discovery itself was powered by AI. Stanford’s Peptide Predictor analyzed more than 20,000 human protein-coding genes, searching for hidden biologically active peptides. From 2,683 candidates, researchers narrowed the list to just 100 for laboratory testing—and BRP emerged as the standout.

In obese mice, a single injection reduced food intake by up to 50% within one hour. After two weeks of treatment, the animals lost significant body fat while untreated mice continued gaining weight. The peptide also improved glucose tolerance and insulin sensitivity.

“Nothing we’ve tested before has compared to semaglutide’s ability to decrease appetite and body weight. We are very eager to learn if it is safe and effective in humans.” — Dr. Katrin Svensson

The findings are still preclinical, meaning BRP has not yet been tested in humans. But if future clinical trials confirm these results, it could represent a new generation of obesity treatments: delivering GLP-1-like benefits through a much more targeted biological pathway—with fewer unwanted side effects.

📄 Nature (2025)

#AI #Obesity #WeightLoss #Ozempic #Neuroscience #StanfordMedicine #science

📊 The U-Curve of Happiness: Why Life Often Gets Better After 50
For decades, the “midlife crisis” was dismissed as little more than a cultural stereotype. But large-scale research suggests it reflects a real statistical pattern.
Economist David Blanchflower (Dartmouth College) analyzed well-being data from 145 countries, controlling for income, education, employment, and marital status. Published in the Journal of Population Economics (2021), the study found a remarkably consistent U-shaped relationship between age and life satisfaction.

Finding Detail

🌍 Scope
145 countries across Europe, Asia, Africa, and the Americas

📉 Lowest point
Life satisfaction typically reaches its minimum in the late 40s (around age 47 in developed countries)

📈 Recovery
Happiness generally rises again through the 50s and 60s, often returning to — or even exceeding — earlier levels

🔁 Consistency
The U-shaped pattern appears across a wide range of cultures and economies, although its strength varies

⚖️ Controls
Results remain after accounting for income, education, marital status, and employment
Why might this happen?

Several explanations have been proposed:
• During midlife, expectations often collide with reality as career growth slows and responsibilities peak — raising children, caring for aging parents, and managing financial pressures.
• Later in life, many people experience fewer competing demands, adjust their expectations, and become more emotionally resilient.
• Neuroscience may offer part of the explanation as well. Separate studies suggest that older adults tend to respond less strongly to negative experiences and naturally focus more on positive ones — although this was not the primary focus of Blanchflower’s research.
One important caveat: this is a population-level trend, not a prediction for any individual. Physical health, close relationships, financial security, and life events remain far more important determinants of happiness than age itself.
Blanchflower’s analysis suggests that the U-shaped pattern of well-being is surprisingly widespread across countries, although its exact shape varies between populations.

📄 Source: Blanchflower D.G. Is happiness U-shaped everywhere? Age and subjective well-being in 145 countries. Journal of Population Economics (2021). DOI: 10.1007/s00148-020-00797-z
#Psychology #Happiness #WellBeing #Science #Aging

👁️ Your Eyes May Have Evolved From an Ancient “Cyclops” Organ

Every vertebrate eye — including yours — may trace its origins to a single light-sensitive organ that sat in the middle of the head of a distant ancestor nearly 600 million years ago.

In a new Current Biology study, researchers from Lund University and the University of Sussex propose that an early worm-like ancestor lost its paired eyes after adopting a sedentary lifestyle. What remained was a simple median light-sensitive organ.

Millions of years later, as its descendants became active swimmers, evolution may have repurposed this central organ to form the paired retinas of vertebrates. The same ancestral system also appears to have given rise to the pineal gland, which today regulates our circadian rhythms and melatonin production.

If correct, this model could explain why vertebrate eyes are fundamentally different from those of insects and squid — and why the systems controlling vision and sleep may share a common evolutionary origin.

One important caveat: this is an evolutionary reconstruction, supported by anatomy, developmental biology, and neuroscience, rather than the discovery of a fossil “cyclops.”

📄 Paper: https://www.cell.com/current-biology/fulltext/S0960-9822(25)01676-8

#Evolution #Biology #Vision #Neuroscience #Science

🧠 An Ordinary Laptop Just Solved a Quantum Problem That Challenged a Quantum Computer

Last year, researchers using D-Wave’s quantum annealer argued that a particularly difficult quantum simulation was beyond the reach of classical computers.

Now physicists at the Flatiron Institute have shown otherwise.

Using tensor networks together with belief propagation—an algorithm first developed in the 1980s—they reproduced the same results using classical hardware, with some of the calculations running on a personal laptop.

The challenge involved simulating hundreds of interacting qubits arranged in complex 2D and 3D lattices. Instead of storing the impossibly large quantum wave function directly, the researchers compressed it into a far more efficient mathematical representation.

The work doesn’t diminish quantum computing. Instead, it raises the bar for what counts as quantum advantage. Every breakthrough in classical algorithms forces quantum hardware to tackle even harder problems—and advances in quantum computing continue to inspire smarter classical methods in return.

Paper (Science): https://www.science.org/doi/10.1126/science.adx2728

#QuantumComputing #Physics #TensorNetworks #Science

👀 “You’ve been spotted.”

NASA’s Curiosity rover was captured from orbit by the Mars Reconnaissance Orbiter (MRO) as it continued its journey across the Martian surface.

🔭 The Largest Eye on Earth Is Rising Above the Atacama

At an altitude of 3,046 metres on Cerro Armazones in Chile’s Atacama Desert, engineers are building the most powerful optical telescope ever attempted: ESO’s Extremely Large Telescope, or ELT.

Its primary mirror will span an astonishing 39 metres — far too large to manufacture as a single piece. Instead, it will function as one perfectly synchronised surface made from 798 hexagonal segments, each about 1.45 metres across. The ELT will collect roughly 100 million times more light than the human eye and more than all existing 8–10-metre-class telescopes combined, observing the Universe in visible and infrared light.

But size is only part of the story.

Earth’s turbulent atmosphere makes stars twinkle — beautiful to us, disastrous for precision astronomy. The ELT’s 2.4-metre adaptive mirror, M4, will be controlled by more than 5,000 actuators, reshaping its surface as often as 1,000 times per second to cancel atmospheric distortion and vibrations almost in real time.

The result could transform the search for life beyond Earth. The ELT will directly image some exoplanets, including potentially rocky worlds in nearby habitable zones, and examine their atmospheres for molecules such as water, methane, carbon dioxide and even oxygen.

First test observations are currently planned for March 2029, followed by the first scientific observations in December 2030.

What will it see first: an Earth-like world, the earliest galaxies — or something astronomers have not yet imagined?

#Astronomy #Space #ELT #Exoplanets #Science #Atacama