Over the years, passing spacecraft have observed mystifying weather patterns at the poles of Jupiter and Saturn. The two planets host very different types of polar vortices, which are huge atmospheric whirlpools that rotate over a planet’s polar region. On Saturn, a single massive polar vortex appears to cap the north pole in a curiously hexagonal shape, while on Jupiter, a central polar vortex is surrounded by eight smaller vortices, like a pan of swirling cinnamon rolls.
Given that both planets are similar in many ways—they are roughly the same size and made from the same gaseous elements—the stark difference in their polar weather patterns has been a longstanding mystery.
Now, MIT scientists have identified a possible explanation for how the two different systems may have evolved. Their findings could help scientists understand not only the planets’ surface weather patterns, but also what might lie beneath the clouds, deep within their interiors.
Observations compiled from several Mars observation missions suggest a significant but short-lived dust storm during the Northern hemisphere summer of Mars Year 37 drove substantial vertical transport of water vapor into the upper atmosphere.
PRESS RELEASE — Los Alamos National Laboratory has formed the Center for Quantum Computing, which will bring together the Lab’s diverse quantum computing research capabilities. Headquartered in downtown Los Alamos, the Center for Quantum Computing will consolidate the Laboratory’s expertise in national security applications, quantum algorithms, quantum computer science and workforce development in a shared research space.
“This new center of excellence will bring together the Laboratory’s quantum computing research capabilities that support Department of Energy, Defense and New Mexico state initiatives to achieve a critical mass of expertise greater than the individual parts,” said Mark Chadwick, associate Laboratory director for Simulation, Computing and Theory. “This development highlights our commitment to supporting the next generation of U.S. scientific and technological innovation in quantum computing, especially as the technology can support key Los Alamos missions.”
The center will bring together as many as three dozen quantum researchers from across the Lab. The center’s formation occurs at a pivotal time for the development of quantum computing, as Lab researchers partner with private industry and on a number of state and federal quantum computing initiatives to bring this high-priority technology closer to fruition. Laboratory researchers may include those working with the DARPA Quantum Benchmarking Initiative, the DOE’s Quantum Science Center, the National Nuclear Security Administration Advanced Simulation and Computing program’s Beyond Moore’s Law project, and multiple Laboratory Directed Research and Development projects.
The A320 involved suffered a flight-control issue that caused a sudden drop in altitude, leaving some passengers with non-life-threatening injuries. During the investigation, a vulnerability to solar flares emerged.
As the aviation industry grows more automated and electronics-dependent, understanding space-weather threats is increasingly vital.
Recent NASA studies suggest that space weather is becoming more intense and frequent, with the Sun currently in a stronger-than-expected activity cycle (solar cycle 25) and potentially entering a period of elevated activity that could last decades.
In a new study published in Physical Review Letters, scientists have performed the first global simulations of monster shocks—some of the strongest shocks in the universe—revealing how these extreme events in magnetar magnetospheres could be responsible for producing fast radio bursts (FRBs).
Magnetars are young neutron stars with extremely strong magnetic fields, reaching up to 1015 Gauss on their surfaces. These cosmic powerhouses produce prolific X-ray activity and have emerged as candidates for explaining FRBs, mysterious millisecond-duration radio bursts detected from across the cosmos. The connection between magnetars and FRBs was strengthened in 2020 when a simultaneous X-ray and radio burst was observed from the galactic magnetar SGR 1935+2154.
The study explores monster shock formation in realistic magnetospheric geometry and was led by Dominic Bernardi, a graduate student at Washington University in St. Louis.
Through new experiments, researchers in Japan and Germany have recreated the chemical conditions found in the subsurface ocean of Saturn’s moon, Enceladus. Published in Icarus, the results show that these conditions can readily produce many of the organic compounds observed by the Cassini mission, strengthening evidence that the distant world could harbor the molecular building blocks of life.
Beneath its thick outer shell of ice, astronomers widely predict that Saturn’s sixth largest moon hosts an ocean of liquid water in its south polar region. The main evidence for this ocean is a water-rich plume which frequently erupts from fractures in Enceladus’ surface, leaving a trail of ice particles in its orbital paths which contributes to one of its host planet’s iconic rings.
Between 2004 and 2017, NASA’s Cassini probe passed through this E-ring and plume several times. Equipped with instruments including mass spectrometers and an ultraviolet imaging spectrograph, it detected a diverse array of organic compounds: from simple carbon dioxide to larger hydrocarbon chains, which on Earth are essential molecular precursors to complex biomolecules.
Bach reframes AI as the endpoint of a long philosophical project to “naturalize the mind,” arguing that modern machine learning operationalizes a lineage from Aristotle to Turing in which minds, worlds, and representations are computational state-transition systems. He claims computer science effectively re-discovers animism—software as self-organizing, energ†y-harvesting “spirits”—and that consciousness is a simple coherence-maximizing operator required for self-organizing agents rather than a metaphysical mystery. Current LLMs only simulate phenomenology using deepfaked human texts, but the universality of learning systems suggests that, when trained on the right structures, artificial models could converge toward the same internal causal patterns that give rise to consciousness. Bach proposes a biological-to-machine consciousness framework and a research program (CIMC) to formalize, test, and potentially reproduce such mechanisms, arguing that understanding consciousness is essential for culture, ethics, and future coexistence with artificial minds.
Key takeaways.
▸ Speaker & lens: Cognitive scientist and AI theorist aiming to unify philosophy of mind, computer science, and modern ML into a single computationalist worldview. ▸ AI as philosophical project: Modern AI fulfills the ancient ambition to map mind into mathematics; computation provides the only consistent language for modeling reality and experience. ▸ Computationalist functionalism: Objects = state-transition functions; representations = executable models; syntax = semantics in constructive systems. ▸ Cyber-animism: Software as “spirits”—self-organizing, adaptive control processes; living systems differ from dead ones by the software they run. ▸ Consciousness as function: A coherence-maximizing operator that integrates mental states; second-order perception that stabilizes working memory; emerges early in development as a prerequisite for learning. ▸ LLMs & phenomenology: Current models aren’t conscious; they simulate discourse about consciousness using data full of “deepfaked” phenomenology. A Turing test cannot detect consciousness because performance ≠ mechanism. ▸ Universality hypothesis: Different architectures optimized for the same task tend to converge on similar internal causal structures; suggests that consciousness-like organization could arise if it’s the simplest solution to coherence and control. ▸ Philosophical zombies: Behaviorally identical but non-conscious agents may be more complex than conscious ones; evolution chooses simplicity → consciousness may be the minimal solution for self-organized intelligence. ▸ Language vs embodiment: Language may contain enough statistical structure to reconstruct much of reality; embodiment may not be strictly necessary for convergent world models. ▸ Testing for machine consciousness: Requires specifying phenomenology, function, search space, and success criteria—not performance metrics. ▸ CIMC agenda: Build frameworks and experiments to recreate consciousness-like operators in machines; explore implications for ethics, interfaces, and coexistence with future minds.
