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Aurora, the exascale supercomputer at Argonne National Laboratory, is now available to researchers worldwide, as announced by the system’s operators from the U.S. Department of Energy on January 28, 2025. One of the goals for Aurora is to train large language models for science.

According to official reports, among the world’s fastest supercomputers, there are currently only three systems that reach at least one exaflop. An exaflop is a quintillion (10¹⁸) calculations per second—that’s like a regular calculator computing continuously for 31 billion years, but completing everything in just a single second. Or, to put it briefly: exaflop supercomputers are incredibly fast.

The fastest among the swift three is El Capitan at the Lawrence Livermore National Laboratory with 1.742 exaflops per second under the HPL benchmark (High-Performance Linpack, a standardized test for measuring the computing power of supercomputers). It is followed by Frontier with 1.353 exaflops/s at the Oak Ridge National Laboratory. The trio is completed by Aurora with 1.012 exaflops/s. Incidentally, all three laboratories belong to the U.S. Department of Energy (DOE).

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Veteran comet hunters have called G3 (ATLAS) the “Great Comet of 2025” due to its daytime visibility and spectacular nighttime sightings. In these gorgeous photos from the Paranal Observatory, it’s not hard to see why.

Photographer Yuri Beletsky caught comet G3 (ATLAS) looking almost like a watercolor painting, ESO wrote in a statement accompanying Beletsky’s photo. The scene was captured on Jan. 19 beside one of the auxiliary telescopes that contribute to ESO’s Very Large Telescope Interferometer, a system of four telescopes working in unison.

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Scientists have developed a new type of compact camera engineered for computer vision. Developed by scientists from the University of Washington and Princeton University, the prototype uses optics for computing and reduces power consumption. It also enables the camera to identify objects at the speed of light.

Their device also represents a new approach to the field of computer vision, a type of artificial intelligence that allows computers to recognize objects in images and video.

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Scientists at Goethe University Frankfurt have identified a new way to probe the interior of neutron stars using gravitational waves from their collisions. By analyzing the “long ringdown” phase—a pure-tone signal emitted by the post-merger remnant—they have found a strong correlation between the signal’s properties and the equation of state of neutron-star matter. Their results were recently published in Nature Communications.

Neutron stars, with a mass greater than that of the entire solar system confined within a nearly perfect sphere just a dozen kilometers in diameter, are among the most fascinating astrophysical objects known to humankind. Yet, the in their interiors make their composition and structure highly uncertain.

The collision of two neutron stars, such as the one observed in 2017, provides a unique opportunity to uncover these mysteries. As binary neutron stars inspiral for millions of years, they emit , but the most intense emission occurs at and just milliseconds after the moment of merging.

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Every cell in the body normally has its fixed place as part of a tissue structure. Except for a few cell types, such as blood or immune cells. But cancer cells also cross established boundaries, grow into the surrounding tissue and multiply. And they can detach from the cell structure and spread via the blood or lymphatic vessels to other areas of the body, where they attach to new cells and form metastases.

The changes that undergo to metastasize are not yet fully understood. Rho (Ras-homologous) GTPases apparently play an important role. These proteins process signals within cells and regulate, among other things, growth, differentiation into the genetically predetermined cell type and cell migration.

Rho GTPases are molecular switches that switch between an active and an inactive state by binding to the phosphate compounds GTP and GDP. GTP corresponds to the ‘on’ position of the switch and starts the molecular biological processes, while GDP corresponds to the ‘off’ position and stops them.

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In this video, Dr. Ben Goertzel, CEO of SingularityNET, TrueAGI and the Artificial Superintelligence Alliance (ASI Alliance), analyzes DeepSeek LLM as an efficiency advancement rather than an AGI breakthrough. The model’s open-source implementation and technical architecture (mixture of experts and multi-token training) improve accessibility while maintaining performance. This development demonstrates the continued democratization of AI capabilities and may redirect industry focus toward alternative computing architectures and decentralized systems.

0:00 Intro.
00:33 Initial Thoughts on DeepSeek.
01:25 Efficiency Gains and Their Implications.
02:58 Technological Singularity and Rapid Advances.
04:07 DeepSeek’s Underlying Technology.
07:27 Open Source Approach and Its Benefits.
09:58 China’s Role in AI and Open Source.
12:20 Broader Implications for AI and AGI
15:42 Conclusion: The Path to Technological Singularity.

#AGI #Deepseek #AI
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SingularityNET was founded by Dr. Ben Goertzel with the mission of creating a decentralized, democratic, inclusive, and beneficial Artificial General Intelligence (AGI). An AGI is not dependent on any central entity, is open to anyone, and is not restricted to the narrow goals of a single corporation or even a single country.

Continue reading “Ben Goertzel on DeepSeek And The Path To AGI” | >

Moran Cerf disucssess why we dream, and goes deeper into explaining the different versions of the relevance of dreams in life.

FULL INTERVIEW — • moran cerf: neural implants, hacking…

ABOUT MORAN:
Prof. Moran Cerf is professor of business at Columbia business school. His academic research uses methods from neuroscience to understand the underlying mechanisms of our psychology, behavior changes, emotion, decisions, and dreams.

Learn More About Moran’s Work Here: https://www.morancerf.com.

Continue reading “‘AI Will Become Conscious’ — Top Neuroscientist on Artificial Intelligence and Consciousness” | >

Observations from the James Webb Space Telescope reveal monster black holes in the early universe that seem to have grown too big, too fast. New research points to a strange form of dark matter as a possible culprit.

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While reviewing a manuscript for the Journal of Organic Chemistry, Caroline Kervarc-Genre and her colleague, Thibault Cantat, researchers at the French Alternative Energies and Atomic Energy Commission, noticed something unusual.

The nuclear magnetic resonance (NMR) spectra buried in the supplementary information had striking irregularities: The baseline was interrupted in some parts, and the noise was the same from one spectrum to the next. “Noise being inherently random, repeating noise is only possible if the spectra are altered [or] fake,” Kervarc-Genre told Retraction Watch.

Starting to suspect something was wrong, she and Cantat, examined other papers by the lead author. They discovered data appeared to have been edited in several of the author’s latest publications. “The fraud was not subtle,” Kervarc-Genre said.

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