Injectable magnetoelectric nanodiscs may activate neurons in localized brain regions when stimulated by a weak external magnetic field, say MIT scientists.
As artificial intelligence (AI) becomes more common and sophisticated, its effects on human lives and societies raises new questions. A new paper published in The Quarterly Review of Biology posits how these new technologies might affect human evolution.
In “How Might Artificial Intelligence Influence Human Evolution?” author Rob Brooks considers the inevitable but incremental evolutionary consequences of AI’s everyday use and human-AI interactions—without “dramatic but perhaps unlikely events, including possibilities of human annihilation, assimilation, or enslavement.”
In the paper, Brooks considers (“often with considerable speculation”) some possible forms of human-AI interaction and the evolutionary implications of such interactions via natural selection, including forms of selection that resemble the inadvertent and deliberate selection that occurred when humans domesticated crops, livestock, and companion animals.
Visual scans of the world have helped Niantic build what it calls a “Large Geospatial Model.”
Researchers propose that time is a result of quantum entanglement, the mysterious connection between particles separated by vast distances. Their findings, published in the journal Physical Review A, could offer a clue to solving the problem of time.
“There exists a way to introduce time which is consistent with both classical laws and quantum laws, and is a manifestation of entanglement,” explained Alessandro Coppo, a physicist at the National Research Council of Italy and the study’s lead author. “The correlation between the clock and the system creates the emergence of time, a fundamental ingredient in our lives.”
In quantum mechanics, time is a fixed phenomenon, an unchanging flow from past to present. It remains external to the ever-changing quantum systems it measures and can only be observed through changes in external entities, like the hands of a clock.
From repairing deadly brain bleeds to tackling tumors with precise chemotherapy, micro/nano-robots (MNRs) are a promising, up-and-coming tool that have the power to substantially advance health care. However, this tool still has difficulty navigating within the human body—a limitation that has prevented it from entering clinical trials.
Mathematical models are crucial to the optimal design and navigation of MNRs, but the current models are inadequate. Now, new, promising research from the University of Saskatchewan (USask) may allow MNRs to overcome the limitations that previously prevented their widespread use.
USask College of Engineering professor Dr. Chris Zhang (Ph. D.) and two Ph.D. students (Lujia Ding, N.N Hu) along with two USask alumni (Dr. Bing Zhang (Ph. D.), Dr. R. Y. Yin (Ph. D.)) are the first team to develop a highly accurate mathematical model that optimizes the design of MNRs which improves their navigation, allowing them to travel efficiently through the bloodstream. Their work was recently published in Nature Communications.
Scientists are combining AI machine learning with mechanical testing to improve plant-based meat.
By Adam Protz
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Gravity has shaped our cosmos. Its attractive influence turned tiny differences in the amount of matter present in the early universe into the sprawling strands of galaxies we see today. A new study using data from the Dark Energy Spectroscopic Instrument (DESI) has traced how this cosmic structure grew over the past 11 billion years, providing the most precise test to date of gravity at very large scales.
DESI is an international collaboration of more than 900 researchers from over 70 institutions around the world and is managed by the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab).
Continue reading “New DESI data shed light on gravity’s pull in the universe” »
MIT physicists have taken a key step toward solving the puzzle of what leads electrons to split into fractions of themselves. Their solution sheds light on the conditions that give rise to exotic electronic states in graphene and other two-dimensional systems.
The new work is an effort to make sense of a discovery that was reported earlier this year by a different group of physicists at MIT, led by Assistant Professor Long Ju. Ju’s team found that electrons appear to exhibit “fractional charge” in pentalayer graphene—a configuration of five graphene layers that are stacked atop a similarly structured sheet of boron nitride.
Ju discovered that when he sent an electric current through the pentalayer structure, the electrons seemed to pass through as fractions of their total charge, even in the absence of a magnetic field.
Flying with Photons: Rendering Novel Views of Propagating Light https://arxiv.org/abs/2404.
Close your eyes and picture the iconic “bullet time” scene from “The Matrix”—the one where Neo, played by Keanu Reeves, dodges bullets in slow motion. Now imagine being able to witness the same effect, but instead of speeding bullets, you’re watching something that moves one million times faster: light itself.
Continue reading “Novel AI algorithm captures photons in motion” »
