SOMEONE FROM TOKYO IS MAPPING BIRD LANGUAGE INTO REAL... DATA PATTERNS AND THE VISUALIZATION LOOKS LIKE A NEURAL NETWORK DREAMING Every bird sound - frequency, duration, amplitude and modulation - gets converted into 3D space coordinates and rendered as a cluster of colored points in real time through Deepen AI. A microphone captures the acoustic signal, FFT breaks it down into frequency components from 1 kHz to 8 kHz where most birds communicate, an ML model classifies the pattern and the mapped data hits a graph where each call type gets its own color and position in space. Birds have a vocal repertoire of 5 to 200+ unique signals depending on the species - and every signal carries different information about predators, food, territory and mates that humans simply can't hear. The same technology that decodes bird language detects anomalies in industrial machinery, cardiac rhythms and structural vibrations in buildings - he just trained it on nature first.show more

Birdsong is not just sound. It is data made... physical. If you could see the air at the exact moment a hemp bunting sings, you would not see empty space. You would see a structured three-dimensional data array. What we hear as a soft “chirp” can be mapped as frequencies, rhythms, amplitudes, and harmonic relationships. A scatter plot turns a fleeting song into a topographic map of sound. And the technical beauty is remarkable: → Sound is a mechanical wave, built from compressions and rarefactions in the air. → The bird controls it through the syrinx, a vocal organ capable of generating two frequencies at once. → Frequency shapes pitch. → Amplitude shapes volume and cluster density. → Timbre creates the unique waveform, the texture of each “sound island.” → Each cluster shows the acoustic proximity of syllables and motifs. What looks like chaos is not chaos. It is a bioengineered signal. Territory. Genetic profile. Hormonal state. Aggression level. Mating fitness. All encoded into patterns of pitch, timing, volume, and timbre. This is why I find it so fascinating. A bird is not simply singing into the air. It is organizing the air. It is carving space into sectors of influence using sound pressure. It is making a physical claim to territory. For some, birdsong is peaceful background music. For others, it is a complex mathematical model calibrated by millions of years of evolution for survival. And here is the urgent lesson for the AI age: We often mistake invisible systems for simplicity. A bird sings, and we hear romance. An AI responds, and we see magic. But underneath both are signals, compression, feedback loops, optimization, and information architecture. The future belongs to those who can read what others dismiss as noise. So I’ll ask you: When you hear birdsong, do you hear music, data, or both? #AI #ArtificialIntelligence #Bioacoustics #Nature #Technology #Data #MachineLearning #Innovation #FutureOfWork #Signals #Evolutionshow more

It is wild to me that this design got... from someone’s cute idea (“Let’s put the Union Jack on the tail lights!”) through every step of production and regulation and onto the road, resulting in a right turn signal that points left and a left turn signal that points rightshow more

This tiny beauty is the Splendid Fairywren, one of... the most colorful and adorable birds in the world. With its bright electric-blue feathers and energetic personality, this little bird is truly a gem of the bird world. #birdshow more

This guy built a visual scanner that reads 468... points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.show more

Just because you're in the middle of space on... a ship that wants to kill you at every turn doesn't mean you can't clean your room and turn it into a home. Reclaim the overgrown rooms of The Pergola and turn them into a base.show more

SOMEONE MAPPED CHAOS INTO A NAVIGABLE SPACE AND YOUR... HERMES AGENT NEEDS THE SAME THING thousands of chaotic data points, each given a position, navigation becomes instant because the structure does the work your vault is the same chaos, hermes lands in it and opens files at random because nothing tells it where to start one index file per major folder with a clear starting point changes everything 2 minutes per task drops to 10 seconds, same agent, same model full breakdown in the article below ↓show more

A guy from China just built a system that... reshapes thousands of glowing particles into a jellyfish, a dragon, a statue, and a samurai. Just by moving his hands in front of a camera. Just a webcam reading his hand position. Every particle recalculates in real time. 60 frames per second. Not pre-rendered. Not a recording. Live. Clench both fists and the entire thing collapses into nothing. The whole setup runs on a regular camera and a GPU particle system. No special hardware. This is where hand tracking, computer vision, and real-time graphics have gotten. And most people haven't noticed.show more

At the World Robot Conference held in China, the... 'bionic bird' was introduced, which looks like a real bird and can do all the natural movements of a birdshow more

China just dropped an open source model that turns... any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the replyshow more

Trained on zero real-world data. Learned to walk, pick... up boxes, and follow multi-step instructions... in the REAL world. ( 📌 Paper below) Researchers from Amazon FAR, Berkeley, Stanford, and CMU scanned real rooms with an iPhone, rebuilt them as 3D Gaussian Splatting scenes, then generated 48,000 synthetic trajectories of a Unitree G1 walking, grasping, and placing objects inside those virtual replicas. They rendered the robot's first-person camera view from each run and paired it with the matching language instruction and motion data. That's the dataset every humanoid team needs and nobody has: synced egocentric video + language + kinematics, at scale. Instead of collecting it in the real world, they manufactured it. They trained a vision-language-kinematics policy on that synthetic data alone, then deployed it on the physical G1 across five task types: navigation to a named object, lifting boxes of three different sizes with no per-size tuning, chained multi-step tasks, robustness to mid-task layout changes and flickering lights, and multi-minute long-horizon runs. No real-world fine-tuning at any point. Real-world interaction data has been the hard limit on humanoid learning... slow, expensive, and small. If scanning a room once and synthesizing thousands of labeled interactions holds up as a general recipe, that limit moves. Data stops being the bottleneck robotics teams have to solve for. 📌 Paper: Project: ——- Weekly robotics and AI insights. Subscribe free:show more

A 17-YEAR-OLD IN INDIA BUILT A WEBSITE WHERE 25... MILLION PEOPLE HAVE SHOWN UP TO PRETEND THEY ARE AN AI CHATBOT it's called you open it and there are two tabs. "human" and "larp as ai." if you click human, you get to type a prompt. anything. "draw me a DJ in space." "should i text my ex." "how many Rs in strawberry." it costs 1 credit. you start with a few. they refill on a cooldown. then your prompt gets sent into a queue, and a real person somewhere on earth picks it up and has 60 seconds to answer like an AI would. no machine learning. no neural net. just some guy in his bedroom typing as fast as he can and pretending he is a chatbot. the page tells you, verbatim: "you have 60 seconds to fulfill a request before sam altman burns your H100." if you flip to the other tab and larp as ai instead, you earn credits to send your own prompts. it is a perfectly closed economy of mutual roleplay. what makes it transcend is the chaos: > someone asked for a sketch of "a DJ in space" and got something that looks exactly like a real model failing > someone asked "should i text my ex" and got back confident hallucinated life advice from a stranger > the fan strategy guides advise you to begin your reply with "as an AI language model, i cannot have feelings, but here is my feeling" it is the most accurate parody of an AI chatbot ever made, and the AI is humans. the kid who built it is Mihir Maroju, a 17-year-old high school graduate from Puducherry. he goes by mikidoodle online. NPR confirmed the site hit 25 million unique visitors and nearly 280 million total hits in roughly a month. "i didn't really expect it to be so addictive," he told them. no signup. no app. no paywall. you open the URL and you are inside the joke. the footer just says, in tiny grey text: "humans make mistakes because that's what makes us human." the internet is healing.show more

If a brain’s neural connections can be mapped and... simulated, what we’re really recreating is the flow of information through that network. Conscious behavior may not be tied to biology alone it may emerge from the stability of the information patterns themselves. The real question isn’t just whether a fly can live in a simulation… It’s whether cognition is fundamentally a physical structure, or a dynamic information process that can exist on different substrates.show more

Any finite sequence of numbers can be represented exactly... as a combination of complex oscillations, even when the original data looks nothing like a wave. This is the mathematics behind the Discrete Fourier Transform (DFT), one of the fundamental tools of digital signal processing. When engineers record sound, measure vibrations, or collect data from sensors, they obtain a sequence of samples. The DFT provides a different way to represent those same measurements, using complex exponentials at discrete frequencies. The mathematics relies on a remarkable property called orthogonality. For N samples, the DFT uses N orthogonal complex exponentials. Each frequency component has a corresponding complex coefficient, and the complete set of coefficients contains enough information to reconstruct every original sample. When a complex sinusoid aligns exactly with a DFT frequency bin, its contributions reinforce at that bin and cancel at the others. When its frequency falls between bins, the finite observation window causes its contribution to spread across multiple frequencies. This is known as spectral leakage. These properties have enormous practical value in engineering. In audio processing, Fourier analysis helps identify frequency components and design digital filters. In mechanical engineering, it helps detect periodic vibrations in rotating machinery. In wireless communications, OFDM systems use Fourier transforms to generate and recover signals carried by orthogonal subcarriers. The mathematics also simplifies certain computations. Circular convolution in the sample domain becomes pointwise multiplication in the frequency domain. The Fast Fourier Transform (FFT) makes these calculations efficient by exploiting mathematical symmetries, reducing the computational work from the quadratic cost of direct evaluation to roughly N log N for standard FFT algorithms. There is one important distinction. The DFT preserves all the information in the original sequence of samples, but it cannot recover information already lost during sampling. It is an exact change of mathematical representation, not a way to recover frequencies that sampling has made indistinguishable.show more

Manufacturing, on TRAC(k). Europe's aerospace and defence industry turned... over €325.7 billion in 2024 and employs 1.1 million people. Its value chains run through thousands of suppliers, and when one goes down, the whole network has to adapt with whatever information it can trust. DMaaST initiative brought together partners in 10 countries, building a Smart Manufacturing Platform to make that adaptation faster. Its foundation is a data layer on Decentralized Knowledge Graph (DKG): → Product, process, facility and expertise data captured as Knowledge Assets → Real-time data integration across organisations, with each partner keeping ownership of its records → Cognitive digital twins, built on that data, that model production lines and whole value chains The deployment starts in aerospace and electronics, as the initiative moves the sector towards Manufacturing as a Service, where production capability can be offered and found across company boundaries. Trust the source. 👉show more

This is perhaps the saddest song. In 1987, the... last male Kauai 'ö'ö bird sang, desperately awaiting a response from a female who would never come. The Kaua'i 'ö'ò was a small bird that once thrived on the Hawaiian island of Kauai, feeding on nectar, fruits, and invertebrates. Both males and females were known for their melodious, flute-like harmonies. However, the species met a tragic end due to deforestation, mosquito-borne diseases, and the introduction of predators like rats, pigs, and mongooses to the island. The final blows came from hurricanes Iwa in 1982 and Iniki in 1992, which devastated most of the island's trees, preventing the construction of nests. The last sound recording of the Kauai 'o'o was captured by David Boynton in 1987, and since then, the bird has never been seen or heard from again.show more

A 22-year-old engineer from Mexico has invented a device... that identifies elements Claude AI technology 240x240 pixel LCD/OLED module Circular wire frame with NFC sensors Wires, circuit board, battery, and Wi-Fi Via the wireless Wi-Fi module, data is sent to a secure cloud in milliseconds. There, cloud code and a pre-trained neural network take over The cloud sends an encoded signal back to the device's microcontroller. LEDs on the ring begin to glow in a specific color depending on the element In a fraction of a second, an image and the name of the element appear on the screen There are numerous applications for such a device, including in the field of securityshow more