Is a cutting-edge application that unveils the political biases embedded in artificial intelligence systems. Explore and analyze the political leanings of AIs with our intuitive platform, designed to foster transparency in the world of artificial intelligence. Stay informed and uncover the political inclinations shaping the algorithms behind the technology revolution.
Stephen Wolfram is a physicist, mathematician, and programmer who believes he has discovered the computational rules that organize the universe at the finest grain. These rules are not physical rules like the equations of state or Maxwell’s equations. According to Wolfram, these are rules that govern how the universe evolves and operates at a level at least one step down below the reality that we inhabit. His computational principles are inspired by the results observed in cellular automata systems, which show that it’s possible to take a very simple system, with very simple rules, and end up at complex patterns that often look organic and always look far more intricate than the black and white squares that the game started with. He believes that the hyperspace relationships that emerge when he applies a computational rule over and over again represent the nature of the universe — and that the relationships that emerge contain everything from the seed of human experience to the equations for relativity, evolution, and black holes. We sit down with him for a conversation about the platonic endeavor that he has undertaken, where to draw the line between lived experience and the computational universe, the limits of physics, and the value of purpose and the source of consciousness.
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A new material bends that rule.
Researchers in South Korea say they have built a soft, magnetic artificial muscle that hits hard numbers without turning into a stiff piston. The material flexes, contracts and relaxes like flesh, yet ramps up stiffness on demand when asked to do real work. That mix has long sat out of reach for humanoid robots that need both agility and strength.
Most humanoids move with a cocktail of motors, gears and pneumatic lines. These systems deliver power, but they also add bulk and make contact risky. Soft actuators change the equation. They integrate into limbs, cushion impacts and tolerate misalignment. They also weigh far less than hydraulic stacks and slot neatly inside compact forms like hands, faces and torsos.
GLUCOSE OXIDATION EQUATION Glucose + 6 O2 — 6 CO2 + 6 H2O + Energy (ATP + heat) • Most energy is generated in mitochondrial matrixCommon Abbreviations: • ATP: adenosine triphosphate • NADH: nicotinamide adenine dinucleotide • FADH2: flavin adenine dinucleotide • CoA: Coenzyme AKEY PROCESSES IN GLUCOSE OXIDATION • Glycolysis • Pyruvate decarboxylation • Citric acid cycle (also known as the Krebs’ cycle and the tri-carboxylic acid (TCA) cycle) • Oxidative phosphorylation (electron transport chain & chemiosmosis)CITRIC ACID CYCLE • 1 glucose molecule requires 2 citric acid cycle turns • Input for each turn: 1 Acetyl CoA • Output for each turn: 3 NADH + 2 CO2 + 1 ATP + 1 FADH2 • NADH & FADH2: electron transfer molecules for oxidative phosphorylation • Occurs in mitochondrial matrixSubstrate level phosphorylation • ATP generated from substrates in glycolysis and citric acid cycle • NOT from.
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Why haven’t we heard from aliens? That’s a question that sounds simple but turns into a mess the moment you try to answer it. Recently, a mathematician tried to simplify the equation by trying to calculate the odds that we’re the only intelligent life in the universe – according to his math, we shouldn’t be. Let’s take a look.
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🤓 Check out my new quiz app ➜ http://quizwithit.com/
📚 Buy my book ➜ https://amzn.to/3HSAWJW
💌 Support me on Donorbox ➜ https://donorbox.org/swtg.
📝 Transcripts and written news on Substack ➜ https://sciencewtg.substack.com/
👉 Transcript with links to references on Patreon ➜ / sabine.
📩 Free weekly science newsletter ➜ https://sabinehossenfelder.com/newsle…
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#science #sciencenews #aliens #maths
A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical units (AU), where an AU is the distance between Earth and the sun. This region consists mostly of icy objects and small rocky bodies, like Pluto. Scientists believe Kuiper belt objects (KPOs) are remnants left over from the formation of the solar system.
Now, a new preprint paper on arXiv describes a newly identified region that appears to be completely distinct from other parts of the Kuiper belt—but some uncertainty remains.
EGGROLL is a novel optimization algorithm that utilizes low-rank perturbations to significantly enhance the scalability and efficiency of Evolution Strategies for training large neural networks, achieving up to a hundredfold improvement in training throughput while maintaining competitive performance.
Soon, researchers may be able to create movies of their favorite protein or virus better and faster than ever before. Researchers at the Department of Energy’s SLAC National Accelerator Laboratory have pioneered a new machine learning method—called X-RAI (X-Ray single particle imaging with Amortized Inference)—that can “look” at millions of X-ray laser-generated images and create a three-dimensional reconstruction of the target particle. The team recently reported their findings in Nature Communications.
X-RAI’s ability to sort through a massive number of images and learn as it goes could unlock limits in data-gathering, allowing researchers to see molecules up close—and perhaps even on the move. “There is really no limit” to the dataset size it can handle, said SLAC staff scientist Frédéric Poitevin, one of the study’s principal investigators.
The research, published in Nature Communications, addresses one of the key challenges to engineering computers that run on light instead of electricity: making those devices small enough to be practical. Just as algorithms on digital computers require time and memory to run, light-based systems also require resources to operate, including sufficient physical space for light waves to propagate, interact and perform analog computation.
Lead authors Francesco Monticone, associate professor of electrical and computer engineering, and Yandong Li, Ph.D. ‘23, postdoctoral researcher, revealed scaling laws for free-space optics and photonic circuits by analyzing how their size must grow as the tasks they perform become more complex.
While atmospheric turbulence is a familiar culprit of rough flights, the chaotic movement of turbulent flows remains an unsolved problem in physics. To gain insight into the system, a team of researchers used explainable AI to pinpoint the most important regions in a turbulent flow, according to a Nature Communications study led by the University of Michigan and the Universitat Politècnica de València.
A clearer understanding of turbulence could improve forecasting, helping pilots navigate around turbulent areas to avoid passenger injuries or structural damage. It can also help engineers manipulate turbulence, dialing it up to help industrial mixing like water treatment or dialing it down to improve fuel efficiency in vehicles.
“For more than a century, turbulence research has struggled with equations too complex to solve, experiments too difficult to perform, and computers too weak to simulate reality. Artificial Intelligence has now given us a new tool to confront this challenge, leading to a breakthrough with profound practical implications,” said Sergio Hoyas, a professor of aerospace engineering at the Universitat Politècnica de València and co-author of the study.