Working in connectomics means creating comprehensive maps of brain and nervous system networks. Your research includes the identification and measurement of all parts of each neuron: the soma, dendrites, axonal path and branching patterns and combining that data with the synapses and gap junctions of the entire circuit.
Your microscopy challenges are extensive; submicron resolution is required over long distances inside large volumes of dense and complicated tissues.
We establish a fundamental, non-zero lower bound for thermodynamic entropy by mapping Ludwig Boltzmann’s classical relation onto the rigid topological boundaries of GLAB chronal dynamics. In standard statistical mechanics, the number of microstates is treated as an abstract mathematical variable capable of reducing to unity , which phenomenologically implies an absolute zero entropy state . We demonstrate that this boundary condition is physically unattainable because the minimal, topologically closed space-phase cell possesses an irreversible internal structure dictated by the free proton configuration. Characterizing the stable proton as an asymmetric quantum “pure top” subject to the Janibekov instability, we prove that it inherently occupies a degenerate phase space composed of 2 intrinsic spin projections and 3 spatial rotational axes. This yields a strict, immutable minimum statistical weight of. Consequently, the absolute minimum entropy of any isolated domain in our universe is bounded by the Proton Constant:. We mathematically demonstrate that if this lower bound were violated, the phase-locking mechanism governing stellar nucleosynthesis would collapse, rendering the existence of periodic nuclear cycles and stable matter impossible.
Google is rolling out new privacy controls for Search services and Google Play, giving you more control over saved history and personalized recommendations.
In an email titled “New privacy settings for Search services,” sent to users and seen by Bleeping Computer, Google said it is “updating our settings to give you even more control over saved history and personalized recommendations across Google Search services and Google Play.”
Google noted that Search services include “Search, Maps, Shopping, Hotels, Flights, Translate, and News,” and users will see the change in their Google Account in the next few days.
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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Welcome to AI Uncovered, your ultimate destination for exploring the fascinating world of artificial intelligence! Our channel delves deep into the latest AI trends and technology, providing insights into cutting-edge AI tools, AI news, and breakthroughs in artificial general intelligence (AGI). We simplify complex concepts, making AI explained in a way that is accessible to everyone.
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.
Schreiver, I., Hesse, B., Seim, C. et al. Sci Rep 7, 11,395 (2017). https://doi.org/10.1038/s41598-017-11721-z.
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
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.
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.
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 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.