neural networks

A forest ages in different ways. In one spot the trees thin out gradually, as if they have grown tired of growing, while in another they cling stubbornly to life, spending their strength repairing damaged branches. The aging of the brain's cortex looks much the same when you view it through the lens of thousands of MRI scans.

Imagine an interpreter at a meeting where everyone speaks a language they don't know. At first, they have to listen to every word, write it down verbatim, and then check against the original. That's how simulations for the IceCube neutrino telescope work: they track every photon born in the Antarctic ice, traveling hundreds of meters to hit a sensor.

A cartographer who draws not mountains and rivers but invisible bonds between electrons: that's one way to describe the new neural network. Instead of atomic coordinates, it takes molecular orbitals and draws a graph where nodes are orbitals and edges are measures of their quantum entanglement.

Diamond is not just a gemstone. Hidden inside its crystal lattice are defects that sense magnetic fields better than many instruments. One such defect, the NV center, acts as a tiny compass, but its needle wavers from heat and noise. For the compass to point accurately, calibration is needed.

Getting lost in a hall of mirrors is easy: every wall reflects another, and you feel like you've been here before. The brain gets similarly confused when surrounded by many similar places. Neurons responsible for the spatial map can fire the same signal for two different corners of a room. This is called spatial ambiguity.

Every day, the brain sounds a little different. Yesterday, the thought of moving your left hand produced one pattern of electrical waves; today, it's slightly different. For a brain-computer interface (a device that turns mental commands into actions), this is a big problem: yesterday's settings don't work today.

A single DNA molecule, squeezed into a tiny metal slit, trembles and flickers under the laser. Its signal is not a clear string of letters but a chaotic mix of flashes and shadows. Deciphering this noise is like trying to make out a whisper in a crowded room. The new neural network works like an attentive interpreter.

A drop of ink in a glass of water spreads in intricate swirls. Similarly, a quantum particle exchanging energy with its environment changes its state in a complex and entangled manner. Describing this dance between particle and environment has long baffled scientists.

When an antibody meets a virus, it doesn't latch on with a single death grip. Rather, it's like two bunches of grapes tumbling in water, catching each other with dozens of short tendrils. Each tendril is weak on its own, easily torn by the thermal jitter of water molecules, but together they hold tight.

A cookbook without a shopping list: that's what a scientist faces when looking at a scheme of chemical reactions. The arrows and formulas on paper look neat, but once you start hunting in the lab for molecules that will actually behave that way, a real quest begins.

Every night, the brain cycles through several sleep stages — from drowsiness to deep sleep and back. Some transitions happen abruptly, like a light switch flipping, while others are smooth, like a slow slide down a slope.

A magnetoencephalograph, a helmet-like device with hundreds of sensors, picks up the weak magnetic fields generated by active neurons. When a person listens to speech, these signals contain imprints of the heard words. But extracting them is tricky: signals from thousands of sources merge into a tangled mess.

The brain doesn't just react to the world: it's constantly guessing what will happen next. This principle is called predictive coding: neurons compare expectations with reality and update their internal picture when an error occurs. But how such a complex system could be wired into the living tissue of the cortex remained unclear.

A stadium packed with fans hears the announcer’s voice for the first time, and instantly the whole place erupts. The message sounds again and again. Only a handful of people in nearby rows respond. That’s roughly how neural networks behave in brain organoids — tiny lab-grown replicas of the brain.

A web where lions eat zebras and hyenas finish the leftovers is not just a list of dinners. It's a survival map for an entire region. When the climate shifts, animals move, and the map tears. To understand where it will tear and where it will hold, you need to find its unchanging 'skeleton'—the connections that repeat across different places.

The human mind is like a construction set that builds itself. New ideas don't die with their creators: they are passed on, mixed, and selected. This process is called cultural evolution: useful inventions stick, useless ones are forgotten. That's how a ratchet works — a mechanism that only turns forward. But what exactly happens in the head when one thought displaces another?

Each morning, dozens of telescopes swing toward the Sun. Their cameras catch a narrow band of red light — the Hα line, discovered by Johann Balmer. The images reveal dark, whimsically curved threads. They look like stitches in a giant tapestry sewn through the blazing corona.

A neuron receives thousands of signals on its branching processes — the dendrites. Some signals push the cell toward firing (excitation), others hold it back (inhibition). For a long time, it was thought that the neuron simply adds up all the 'fors' and 'againsts.' But in real dendrites, inhibition works differently: it can not subtract but divide the excitatory signal.

The cosmos resembles silk fabric with threads of the dark web showing through. We only glimpse tiny swatches of the real tapestry — through telescopes, in actual galaxy catalogs. To separate the fundamental signal from astrophysical noise in the cosmic pattern, statistical analysis demands thousands of plausible sketches — synthetic sky maps.

Assembling the puzzle of the Universe, astronomers are used to every new detail fitting perfectly into the already completed picture. But sometimes there are pieces that seem cut from another jigsaw. Twenty thousand active galactic nuclei, and eleven percent of them the neural network confidently rejects as alien.

Biologists are increasingly trusting computers to read the "user manuals" of living cells. Six recent AI models (Nicheformer, CellPLM, scGPT-spatial, GenePT, scELMo, and Novae) are like six translators working from different dialects of the same cellular language.

An artist makes a quick charcoal sketch, and the face in the portrait is already recognizable. Astrophysicists face a similar challenge: the spectrum of a star is its individual portrait, revealing temperature, composition, and gravity.

Every time a child with cerebral palsy is about to move their leg, a distinctive electrical blip appears in the brain — a slow voltage shift. Scientists call it a movement-related potential. A brain-computer interface (a system that reads intentions from brain signals) can pick up this blip and turn it into a command for a training device.

Imagine a vast library where every book is a precise instruction manual for assembling one protein molecule. AlphaFold2 read millions of such books and learned to instantly produce a ready-made 3D model. But inside this network, in its very 'brain,' something more remained — not just assembly rules, but an entire atlas of possible protein motions, its hidden life.

A city at night: lights on in some windows, dark in others. If you connect with lines the windows that light up simultaneously, you get a web of connections. Researchers studied such a web in tiny brain organoids — living clusters of nerve cells grown in the lab.

Many natural processes are described by differential equations, but scientists often have only fragmentary data — a sort of torn map. The new computational method works like a cartographer who reconstructs a complete map of the terrain from a few landmarks.

A typical tracking program resembles a navigator steering a ship by the stars. But as soon as the sky clouds over, coordinates drift, and entropy (a measure of uncertainty) builds up in the data. The new algorithm gets a ‘co‑pilot’ — a module that monitors how confident the main navigator is.

When biologists measure the activity of thousands of genes, they usually just see a list of coincidences, like two ingredients in a soup that often end up together. The standard method looks for such pairwise connections but doesn't show who influences whom. A new approach, like a detector of dark matter, uncovers hidden threads of causation.

The modern standard approach to AI training is like a child locked in a library: he remembers millions of books but doesn't know that fire burns and falling hurts.

At the heart of every neutron star lies a symphony — an intricate interplay of quantum fields and relativistic gravity.

The brain communicates in short electrical clicks. Previously, to learn this language, thousands of examples with translations from the experimenter were needed. MOJO takes a different path: like learning a language through immersion, it first listens to the 'stream of consciousness' without any hints and finds recurring patterns on its own.

A bee-sized quadcopter autonomously charts its route indoors, like a space probe through an asteroid field. Its camera works as a photometry instrument, capturing reflected light, while the processor decides where to turn at the speed of light.

Evolution resembles not just a tree with diverging branches, but a woven tapestry. Threads of ancestry cross when species exchange genes — for example, bacteria pass drug resistance to each other, and plants crossbreed to produce hybrids.

A child exploring an unfamiliar apartment crawls from object to object and remembers what is visible from each corner. This is how the brain builds a mental map — an internal model of space. The gradCSCG algorithm works on the same principle: it receives a video stream from a camera and independently draws a map of the room, relying only on the changing images.

A city signal bounces between walls like a ball, and your phone catches dozens of its 'reflections'—echoes. Each microsecond of delay adds 300 meters to the path. The signal's speed is constant, like that of light (speed of light).

When a giant star collapses into a supernova or two neutron spheres merge in a cosmic dance, trillions of neutrinos carry away the cataclysm's energy.

Neutron stars are the last clumps of visible matter before collapsing into a black hole. In their interiors, matter is squeezed to trillion-fold densities. Here, nuclear forces and gravity weave into an exotic substance inaccessible to any earthly particle accelerator.

In a kitchen with gas burners, each heats differently. If the cook moves the pots, food may burn. Just so in a wireless network: the antenna-burners and user-pots require precise placement. Ordinary neural networks don’t distinguish positions, treating all burners as identical. So they struggle to estimate signal quality or adjust transmission.

A family tree becomes a tangle if you account for adopted children and remarriages. Evolution often resembles such a tangle: although the Standard Model, the traditional view of divergent evolution where species branch like a tree, paints a neat tree of species, in reality genes travel not only by inheritance but also directly between unrelated organisms — a process…

An experienced detective doesn't calculate a criminal's path using the laws of physics: he checks a file of similar cases. The new prediction method works the same way: instead of complex equations, it has a vast archive of trajectories that have already happened — planetary motions, currency exchange rates, signals from space.