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Category: physics – Page 32

What Happens After Superintelligence? (with Anders Sandberg)

Anders Sandberg joins me to discuss superintelligence and its profound implications for human psychology, markets, and governance. We talk about physical bottlenecks, tensions between the technosphere and the biosphere, and the long-term cultural and physical forces shaping civilization. We conclude with Sandberg explaining the difficulties of designing reliable AI systems amidst rapid change and coordination risks.

Learn more about Anders’s work here: https://mimircenter.org/anders-sandberg.

Timestamps:
00:00:00 Preview and intro.
00:04:20 2030 superintelligence scenario.
00:11:55 Status, post-scarcity, and reshaping human psychology.
00:16:00 Physical limits: energy, datacenter, and waste-heat bottlenecks.
00:23:48 Technosphere vs biosphere.
00:28:42 Culture and physics as long-run drivers of civilization.
00:40:38 How superintelligence could upend markets and governments.
00:50:01 State inertia: why governments lag behind companies.
00:59:06 Value lock-in, censorship, and model alignment.
01:08:32 Emergent AI ecosystems and coordination-failure risks.
01:19:34 Predictability vs reliability: designing safe systems.
01:30:32 Crossing the reliability threshold.
01:38:25 Personal reflections on accelerating change.

Physicists observe image rotation in plasma

Light sometimes appears to be “dragged” by the motion of the medium through which it is traveling. This phenomenon, referred to as “light dragging,” is typically imperceptible when light is traveling in most widely available materials, as the movement is significantly slower than the speed of light. So far, it has thus proved difficult to observe in experimental settings.

Researchers at the University of Toulouse, University of California-Los Angeles (UCLA), University of Paris-Saclay and Princeton University recently observed a specific type of dragging known as image rotation in a plasma-based system.

Their observation, outlined in a paper published in Physical Review Letters, was made using magnetohydrodynamic (MHD) that propagate in a magnetized plasma, known as Alfvén waves.

Rethinking the Anomalous Hall Effect: A Symmetry Revolution

A new symmetry-breaking scenario provides a comprehensive description of magnetic behavior associated with the anomalous Hall effect.

In 1879 Edwin Hall discovered that a flat conductor carrying current, when placed in a magnetic field, will develop a transverse voltage caused by the deflection of charge carriers. Two years later he discovered that the same effect arises in ferromagnets even without an applied magnetic field. Dubbed the anomalous Hall effect (AHE), that phenomenon, alongside the ordinary Hall effect, not only catalyzed the rise of semiconductor physics and solid-state electronics but also laid the groundwork for a revolutionary convergence of topology and condensed-matter physics a century after Hall’s discoveries. Recent experiments, however, have uncovered behavior that cannot be explained with current theories for the AHE.

Dark dwarfs lurking at the center of our galaxy might hint at the nature of dark matter

Celestial objects known as dark dwarfs may be hiding at the center of our galaxy and could offer key clues to uncover the nature of one of the most mysterious and fundamental phenomena in contemporary cosmology: dark matter.

A paper published in the Journal of Cosmology and Astroparticle Physics by a team of researchers based in the UK and Hawaii describes these objects for the first time and proposes how to verify their existence using current observational tools such as the James Webb Space Telescope. The paper is titled “Dark Dwarfs: Dark Matter-Powered Sub-Stellar Objects Awaiting Discovery at the Galactic Center.”

The Anglo-U.S. team behind the study named them dark dwarfs. Not because they are dark bodies—on the contrary—but because of their special link with dark matter, one of the most central topics in current cosmology and astrophysics research.

Machine learning outpaces supercomputers for simulating galaxy evolution coupled with supernova explosion

Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the origins of our own galaxy, particularly the elements essential for life in the Milky Way.

The findings are published in The Astrophysical Journal.

The team was led by Keiya Hirashima at the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) in Japan, along with colleagues from the Max Planck Institute for Astrophysics (MPA) and the Flatiron Institute.

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