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Von Neumann Probes: The Self-Replicating Robots That Could Consume the Galaxy

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What happens when machines can build more of themselves—and never stop? In this episode of Entropy Rising, Jacob and Lucas unravel the strange, fascinating world of von Neumann probes: self-replicating systems that could mine asteroids, build Dyson swarms, and maybe even terraform entire planets. But the same tech could go off the rails—accidentally wiping out alien life, turning planets into grey goo, or mutating into something far worse. Are these machines the key to a post-scarcity future, or the seeds of cosmic disaster? We explore the science, the speculation, and the existential questions behind one of the most provocative ideas in futurism.

Stick around for a bonus post-show discussion—available free on our Patreon.

Website: https://www.entropy-rising.com/

There Is No Formula: Why AI Cannot Solve What Matters Most

There is no formula for love. No formula for meaning. No formula for great art, for grief, for living a life that matters.

But we keep looking for one anyway. Increasingly, we look for it in AI.

In my new essay, I argue that this is a category error with a real cost. Some problems lend themselves to calculation: fusion, protein folding, and route optimization. With enough compute, they yield. Other problems do not bend at all. They cannot be solved. They can only be lived.

When we mistake the second category for the first, we bring what I call the Hammer of AI to questions that ask for wisdom, presence, and judgment.

Then we are surprised when the hammer keeps breaking the very thing we were trying to mend.

The piece draws on Tolkien, Vaclav Havel, Carlos Castaneda, and the Japanese art of Kyudo to argue that what we actually need in the age of AI is not another formula. It is the wisdom to know when there is no formula at all.

When complexity arrives in your life, do you reach for the hammer or for something else?

Efficacy and Safety of Amifampridine in Myasthenia GravisA Randomized, Double-Blind, Placebo-Controlled Crossover Trial

Class I evidence that in patients with AChRAb+ myasthenia gravis, the addition of amifampridine to pyridostigmine was not superior to treatment with pyridostigmine alone and was associated with a higher incidence of adverse events.


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Teaching NeuroImage: Bilateral Posterior Limb Internal Capsule T2 Hyperintensity and Severe Cerebellar Atrophy in 2 Lifelong Friends

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Cellular and subcellular specialization enables biology-constrained deep learning

Galloni et al. introduce “dendritic target propagation”: a Dale’s law-compliant learning algorithm for cortical microcircuits with soma-and dendrite-targeting inhibition and realistic connectivity constraints. By combining experimentally derived BTSP and Hebbian rules, dendrites compute local error proxies via E/I mismatch, supporting gradient-based deep learning during simultaneous bottom-up and top-down signaling.

Silicon oscillators solve computer problems that would take thousands of years using semiconductors

In the era of big data and artificial intelligence, a new approach has emerged for solving combinatorial optimization problems, which involves finding the most efficient solution among many possible options and can otherwise take thousands of years to compute.

A KAIST research team has developed computational hardware that can be implemented entirely using existing silicon processes, enabling deployment on existing fabrication lines without additional facilities. This is expected to enable faster and more accurate decision-making across various industries, including logistics, finance, and semiconductor design.

The research is published in Science Advances.

Scientists program materials just by spinning them

There is something universally appealing about the slap bracelet, and the way a simple tap causes it to switch between a straight shape and a curled one. What you probably didn’t know is that a slap bracelet’s satisfying snap is the same principle behind bistable structures. These can toggle between two stable positions (one representing 0 and the other 1) to store data directly within their physical forms as mechanical bits (m-bits).

Because of their exciting potential for efficient control of robotic and other mechanical systems, researchers have been engineering special materials with programmable structures (programmable metamaterials) for years. But until now, actual programming of such systems has been a major challenge: mechanical bits must typically be controlled individually, which is extremely cumbersome and time-consuming.

Now, researchers in the Flexible Structures Laboratory (fleXLab) in EPFL’s School of Engineering, the Dutch research institute AMOLF, and Leiden University have found a way to program metamaterials globally with a surprisingly simple solution: rotation. By tuning a spinning platform’s speed, direction, and acceleration, the researchers can harness forces arising in a rotating system—such as centrifugal and Euler forces—to make elastic beams snap back and forth, creating a simple new way to “write” multiple mechanical bits at once.

Zuckerberg Trying to Simulate Human Biology at the Cellular Level

Mark Zuckerberg is following a path paved by fellow billionaires Bill Gates and Warren Buffet: laundering his untold billions through a health research prestige project.

Called the Chan Zuckerberg Biohub — his wife Priscilla Chan, a pediatrician, is also involved — the foundation’s stated long-term mission is to “cure and prevent all disease through AI-powered biology, frontier research, and state-of-the-art technology.”

True to those enormous goals, the Biohub recently announced a $500 million investment into AI models of human cells, specifically, in order to “accelerate the cure and prevention of all diseases,” Euronews reported.

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