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AUSTIN (KXAN) — The most sensitive dark matter detector in the world is showing results in the hunt for the hypothetical particle. The results: they can’t find it.

“If you think of the search for dark matter like searching for buried treasure,” said Scott Kravitz, an associate professor in the physics department at the University of Texas, “we’ve basically dug part of the way down to where it might be, it could still be deeper below what we’ve searched so far.”

Kravitz is part of the LEX-ZEPLIN project, a Department of Energy hunt for dark matter in a cavern in South Dakota.

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The nature of Earth’s deep past can often feel intangible. From our modern moment, eons billions of years in the past seem hard to touch. Among some of our planet’s rocks, however, are tatters and fragments from those distant times that can offer us a peek at what our planet was like when our ancestors were single-celled organisms. By studying some of these vestiges, geologists have been able to detect what was transpiring under the Earth’s crust over 2.5 billion years ago.

Below our feet—and our planet’s outer crust— Earth’s mantle makes up the vast majority of the planet’s volume. Different layers of the mantle are made up of different rock types, and one of the most common is an igneous rock high in silica content called peridotite. In the past, when geologists have compared samples of prehistoric peridotite from Earth’s mantle and their modern equivalents, they’ve found a significant discrepancy.

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TAMPA, Fla. — Verizon is launching satellite-enabled emergency text and location services this fall for compatible Android smartphones in the United States at no extra cost for customers.

The telecoms giant announced a partnership Aug. 28 to deliver the service with Skylo, which has developed ground infrastructure enabling L-band geostationary satellites to reach devices using the latest standards-based chipsets.

Google’s family of Pixel Pro devices and the Samsung Galaxy S25 are set to be among the first to get access to Skylo’s partner satellites, enabling emergency narrowband connectivity when cell towers are out of reach.

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TOC 00:00:00 Intro 00:03:38 Reasoning 00:13:09 Potential AI Breakthroughs Reducing Computation Needs 00:20:39 Memorization vs. Generalization in AI 00:25:19 Approach to the ARC Challenge 00:29:10 Perceptions of Chat GPT and AGI 00:58:45 Abstract Principles of Jurgen’s Approach 01:04:17 Analogical…

Jürgen Schmidhuber, the father of generative AI shares his groundbreaking work in deep learning and artificial intelligence. In this exclusive interview, he discusses the history of AI, some of his contributions to the field, and his vision for the future of intelligent machines. Schmidhuber offers unique insights into the exponential growth of technology and the potential impact of AI on humanity and the universe.

MLST is sponsored by Brave:

Continue reading “Neural and Non-Neural AI, Reasoning, Transformers, and LSTMs” | >

Nanobots are tiny, ~50–100 nm wide robots that perform a single, highly specialized task. They work incredibly well for administering drugs. Drugs typically act throughout the body before entering the diseased area. The medication can be precisely targeted with nanotechnology, increasing its effectiveness and lowering the possibility of negative side effects. Special sensor nanobots can be inserted into the blood under the skin where microchips, coated with human molecules and designed to emit an electrical impulse signal, monitor the sugar level in the blood.

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In recent years, there have been many reviews investigating neuromorphic computing from the perspectives of device electrical properties,[ 9, 10 ] resistive switching materials,[ 11, 12 ] memristive synapses and neurons,[ 13 ] algorithm optimization,[ 14 ] and circuit design.[ 15 ] Different from the existing literature, we discuss the possibility of achieving brain-like computing from the perspective of memristor technology and review the establishment of spiking neural network neuromorphic computing systems. In this article, we first review the resistive switching mechanisms of different types of memristors and focus on factors, which affect device stability and the corresponding optimization measures that have been applied. Furthermore, we study the stochasticity, power consumption, switching speed, retention, endurance, and other properties of memristors, which are the basis for neuromorphic computing implementations. We then review various memristor-based neural networks and the building of spike neural network neuromorphic computing systems. Finally, we shed light upon the major challenges and offer our perspectives and opinions for memristor-based brain-like computing systems.

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