Lifeboat Foundation

On Thursday, OpenAI and ASU announced the first-of-its-kind partnership, which has reportedly been in the works for six months.

Students, professors, and researchers are set to get access to the tech in February. The university plans to build personalized AI tutors and avatars for students and expand its prompt engineering course.

In a press release, Arizona State University said the partnership would set a new precedent for how universities “enhance learning, creativity and student outcomes.”

Quasicrystals are intermetallic materials that have garnered significant attention from researchers aiming to advance condensed matter physics understanding. Unlike normal crystals, in which atoms are arranged in an ordered repeating pattern, quasicrystals have non-repeating ordered patterns of atoms.

Their unique structure leads to many exotic and interesting properties, which are particularly useful for practical applications in spintronics and magnetic refrigeration.

A unique quasicrystal variant, known as the Tsai-type icosahedral quasicrystal (iQC) and their cubic approximant crystals (ACs), display intriguing characteristics. These include long-range ferromagnetic (FM) and anti-ferromagnetic (AFM) orders, as well as unconventional quantum critical phenomenon, to name a few.

Astronomers accidentally uncovered an extremely dark primordial galaxy — one of the faintest objects in the universe — because of a typo in their telescope coordinates.

It is widely accepted that consciousness or, more generally, mental activity is in some way correlated to the behavior of the material brain. Since quantum theory is the most fundamental theory of matter that is currently available, it is a legitimate question to ask whether quantum theory can help us to understand consciousness. Several approaches answering this question affirmatively, proposed in recent decades, will be surveyed. There are three basic types of corresponding approaches: consciousness is a manifestation of quantum processes in the brain, quantum concepts are used to understand consciousness without referring to brain activity, and matter and consciousness are regarded as dual aspects of one underlying reality. Major contemporary variants of these quantum-inspired approaches will be discussed.

Phenomenon could account for universe’s mysterious dark matter.

Whether end-spectral bias for red and blue in the visual cortex inherits from the pre-cortical stage or emerges within V1 remains incompletely understood. Here, the authors revealed a feedforward mechanism of end-spectral bias which is mainly transmitted through parvocellular pathway.

Heat resistant mimresister at room temperature.

Due to the heat generation during operations in high-density three-dimensional (3D) integrated chips, a high-temperature tolerant and high-performance self-rectifying memristor (SRM) is a promising candidate for 3D integration. Here, we investigated the high-temperature characteristics of Ta/TaO_X/HfO₂/Pt SRMs with a 250 nm feature size in an 8 × 8 crossbar array (CBA). The SRMs exhibit high uniformity and can be operated repeatedly at Set (4 V/2 μs) and Reset (−2 V/1 μs) pulses for more than 10⁴ cycles resulting in ultra-low switching energy (5.86 aJ for Set and 77.2 aJ for Reset). High yield of the array indicates the reliable preparation processes. Remarkably, the CBA is capable of stably resistive switching at high temperatures from 300 to 475 K. At 300 K, the SRM shows large nonlinearity (NL, ∼1.4 × 10⁴) and rectification ratio (RR, ∼8.8 × 10³) as well as high scalability (330 Mbit); at 475 K, the NL and RR of the SRM can still maintain above 400, and the scalability still reaches 71 Kbit. Moreover, our SRM passed a high-temperature retention test of over 5 × 10⁴ s at 438 K. Segmented fittings of the I–V curves of the SRM at different temperatures were performed, concluding that large NL and RR attributed to the Schottky barriers at TaO_X/HfO₂ and Pt/HfO₂ interfaces, respectively. Our work furnishes a feasible solution for high-density 3D integrated memristors in high-temperature application scenarios represented by automotive-grade chips.

Neuromorphic computing provides alternative hardware architectures with high computational efficiencies and low energy consumption by simulating the working principles of the brain with artificial neurons and synapses as building blocks. This process helps overcome the insurmountable speed barrier and high power consumption from conventional von Neumann computer architectures. Among the emerging neuromorphic electronic devices, ferroelectric-based artificial synapses have attracted extensive interest for their good controllability, deterministic resistance switching, large output signal dynamic range, and excellent retention. This Perspective briefly reviews the recent progress of two-and three-terminal ferroelectric artificial synapses represented by ferroelectric tunnel junctions and ferroelectric field effect transistors, respectively. The structure and operational mechanism of the devices are described, and existing issues inhibiting high-performance synaptic devices and corresponding solutions are discussed, including the linearity and symmetry of synaptic weight updates, power consumption, and device miniaturization. Functions required for advanced neuromorphic systems, such as multimodal and multi-timescale synaptic plasticity, are also summarized. Finally, the remaining challenges in ferroelectric synapses and possible countermeasures are outlined.

The possibility of direct interfacing between biological and technological information devices could result in a merger of mind and machine — Ultimate Computing. This book, a thorough consideration of this idea, involves a number of disciplines, including biochemistry, cognitive science, computer science, engineering, mathematics, microbiology, molecular biology, pharmacology, philosophy, physics, physiology, and psychology.