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Google Is Mapping the Human Brain… and It Gets Terrifying

Google is using AI to map the human brain, generate synthetic neurons, and speed up one of the most ambitious neuroscience projects ever attempted. But as brain mapping, connectomics, and AI brain decoding move forward, a terrifying question appears: what happens to mental privacy when machines can understand the brain better than we do?

This mini-documentary explores Google’s brain mapping research, synthetic neurons, AI mind decoding, neural privacy, and the future of human thought in the age of artificial intelligence.

CHAPTERS:
00:00 Google’s Brain Mapping Project.
02:00 The Scale of the Human Brain.
04:36 Synthetic Neurons Explained.
06:40 AI Is Already Decoding Thoughts.
10:15 The Rise of Neural Privacy.
14:51 Brain Maps and the Future of AI
17:11 Who Owns Your Mind?

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At AI Uncovered, we’re passionate about uncovering the most captivating stories in AI, including the marvels of ChatGPT and advancements by organizations like OpenAI. Our content spans a wide range of topics, from science news and AI innovations to in-depth discussions on the ethical implications of artificial intelligence. Our mission is to enlighten, inspire, and inform our audience about the rapidly evolving technology landscape.

Scientists Put a Fruit Fly’s Brain in a Computer Simulation… What It Did Is Now Scaring Scientists

Scientists have achieved an incredible breakthrough by recreating the brain of a fruit fly inside a computer simulation. By mapping around 140,000 neurons and millions of connections, they built a digital brain that can sense its environment, process information, and even control a virtual body. In the simulation, the digital fly was able to search for food, respond to stimuli, and show behaviors that were not directly programmed by scientists. This discovery shows how powerful neural connections are in generating behavior. It also raises fascinating questions about the nature of intelligence, consciousness, and whether complex brains—including ours—could one day be simulated in computers.

sources

https://eon.systems/updates/embodied-brain-emulation.

Research Paper for more information.
https://marginalrevolution.com/margin

#Science.
#Neuroscience.
#ArtificialIntelligence.
#BrainSimulation.
#FruitFlyBrain.
#Connectome.
#FutureTech.
#ComputerSimulation.
#NeuralNetworks.
#ScienceDiscovery

New art test could help museums spot fake Van Goghs without touching paintings

A new study published in the peer-reviewed journal Surface Topography: Metrology and Properties introduces a pioneering, noninvasive technique that can distinguish authentic artworks from forgeries, offering museums, collectors, and auction houses a major advantage in tackling art fraud.

The study, developed at the Université Polytechnique Hauts-de-France, introduces a method that analyzes the microscopic “texture” of a painting by converting high-resolution images into 3D-like maps, allowing researchers to measure how rough or detailed the surface is using fractal dimensions. This measurement captures subtle patterns created by an artist’s brushwork—patterns so consistent that they act like a morphological signature unique to that artist.

Using works attributed to Vincent van Gogh, the researchers showed that the method can reliably distinguish between authentic paintings and known forgeries. In tests, the well-documented fake “The Plowmen” was identified as a strong outlier, while the recently authenticated “Sunset at Montmajour” aligned closely with Van Gogh’s known works.

Bridging the gap between Minds & Machines

Michal Irani (Weizmann Institute)
https://simons.berkeley.edu/talks/mic
Topics in Intelligence: World Models and Social Reasoning.

In this talk I will present my vision of how combining the power of Brains & Deep-Networks (DNNs) can lead to significant breakthroughs in both domains and potentially bridge the gap between Brains & Machines. I will show how combining the power of Multiple Brains (“the Wisdom of a Crowd of Brains”) may lead to new breakthrough discoveries in Brain-Science, allow mapping of information between different brains (with NO shared data), and lead to new ways of training and interpreting artificial DNNs.

Enhancing soil science research with multi-agent artificial intelligence systems

Soil science is entering a new era characterized by the integration of artificial intelligence (AI) multi-agent systems, extending the field beyond traditional machine learning (ML) applications such as digital soil mapping and spectroscopy. While current ML tools are effective for specific tasks, they often lack the reasoning, contextual integration, and adaptability required to address complex, dynamic soil systems. We propose multi-agent AI systems—autonomous, interactive software agents capable of perceptual processing, planning, and scientific reasoning—as a novel framework to support and accelerate soil science research. These agents can fulfill diverse roles, including synthesizing data from field sensors and remote sensing to create dynamic digital soil twins, generating hypotheses, designing experiments, and simulating climate-driven changes in soil function.

Quantum memory surpasses classical limits for storing unknown quantum operations

Quantum memories, systems that store and retrieve information leveraging quantum mechanical effects, can outperform classical storage systems on some existing tasks. Yet these promising memories could also complete operations that are very difficult or impossible for classical systems, including the storage and retrieval of so-called isometry channels.

Isometry channels are transformations that entail mapping a smaller quantum system onto a larger one while preserving quantum information.

In a paper published in Physical Review Letters, researchers at the University of Tokyo showed that quantum methods significantly outperform classical ones in the storage and retrieval of these transformations.

Lunar orbiter concept could reveal five key elements across moon in two years

Researchers from Tokyo Metropolitan University have used simulations to show that a newly developed, compact X-ray telescope could be used to map the chemical composition of the entire lunar surface, a vital breakthrough for understanding its geological evolution. Detailed modeling of the detector and a realistic satellite mission show that two years would be enough to map five key elements, while an array of 5-by-5 detectors could improve resolution and get results faster.

The geological evolution of the moon remains a mystery to scientists. This reflects how challenging it is to get accurate information, such as a complete map of the geochemistry of the lunar surface. Since we cannot readily go and collect samples from anywhere, scientists use a technology known as X-ray fluorescence imaging, in which detectors directed at the moon are used to pick up X-rays released by specific elements when they are hit by solar rays.

While observations during the Apollo and Chandrayaan missions have successfully yielded partial maps, we are nowhere near a comprehensive map that might illuminate lunar geology. This is due to significant technical challenges, including a lack of sufficient illumination by solar rays during the lifetime of a mission and degradation of the detector. The illumination issue is particularly pronounced in polar regions, where solar X-rays are much weaker.

Jumping spiders inspire ultra-efficient 3D camera

This 3D camera estimates depth by comparing blur across two differently focused images of the same scene. The prototype generates real-time 3D maps while using less than a watt of power, sidestepping more energy-intensive approaches.


By borrowing a trick from tiny jumping spiders, Northwestern University engineers have developed an extremely energy-efficient 3D camera. Called SpiderCam, the new device senses depth the same way that jumping spiders judge distances before making a high-precision hop. To estimate depth, the system captures two images of the same scene with slightly different focus settings and measures subtle differences in blurriness between the two images.

With this strategy, the camera produces real-time 3D maps while consuming less than a watt of power. That’s less energy than used by a standard nightlight.

The innovation could enable a new generation of battery-powered devices that need to gauge their surroundings, like wearable technologies, assistive devices, robots and drones.

Polyamine homeostasis in Caenorhabditis elegans relies primarily on transport

Chang and Jain develop a genetically encoded reporter to measure polyamines at single-cell resolution in C. elegans. By mapping polyamine control across tissues and development, they uncover organizing principles of in vivo polyamine regulation, including widespread reliance on transport and a central role for the intestine in coordinating systemic homeostasis.

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