Lifeboat Foundation

Tesla is stacking a massive supply of Cybertruck castings at Gigafactory Texas, hinting the production is near, which means deliveries aren’t far behind either.

Tesla Cybertruck production has been nearing for months as the company has shown early-stage validation, public road testing, crash assessments, and some of the best-built Cybertruck units, all within the past few months.

Production is obviously getting close, especially when we base this thought on the fact that public-road testing of RC-labeled, or release candidate, Cybertrucks have been spotted throughout the country over the past month and a half.

Over the past few years, we have taken a gigantic leap forward in our decades-long quest to build intelligent machines: the advent of the large language model, or LLM.

This technology, based on research that tries to model the human brain, has led to a new field known as generative AI — software that can create plausible and sophisticated text, images and computer code at a level that mimics human ability.

Businesses around the world have begun to experiment with the new technology in the belief it could transform media, finance, law and professional services, as well as public services such as education. The LLM is underpinned by a scientific development known as the transformer model, made by Google researchers in 2017.

Missions to the Moon, missions to Mars, robotic explorers to the outer Solar System, a mission to the nearest star, and maybe even a spacecraft to catch up to interstellar objects passing through our system. If you think this sounds like a description of the coming age of space exploration, then you’d be correct! At this moment, there are multiple plans and proposals for missions that will send astronauts and/or probes to all of these destinations to conduct some of the most lucrative scientific research ever performed. Naturally, these mission profiles raise all kinds of challenges, not the least of which is propulsion.

Simply put, humanity is reaching the limits of what conventional (chemical) propulsion can do. To send missions to Mars and other deep space destinations, advanced propulsion technologies are required that offer high acceleration (delta-v), specific impulse (I_sp), and fuel efficiency. In a recent paper, Leiden Professor Florian Neukart proposes how future missions could rely on a novel propulsion concept known as the Magnetic Fusion Plasma Drive (MFPD). This device combines aspects of different propulsion methods to create a system that offers high energy density and fuel efficiency significantly greater than conventional methods.

Florian Neukart is an Assistant Professor with the Leiden Institute of Advanced Computer Science (LIACS) at Leiden University and a Board Member of the Swiss quantum technology developer Terra Quantum AG. The preprint of his paper recently appeared online and is being reviewed for publication in Elsevier. According to Neukart, technologies that can surmount conventional chemical propulsion (CCP) are paramount in the present era of space exploration. In particular, these technologies must offer greater energy efficiency, thrust, and capability for long-duration missions.

WIRED asked experts from all corners of society and academia to answer questions about the future of technology, artificial intelligence, and humanity itself.

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In a new Physical Review Letters study, scientists have successfully presented a proof of concept to demonstrate a randomness-free test for quantum correlations and non-projective measurements, offering a groundbreaking alternative to traditional quantum tests that rely on random inputs.

“Quantum correlation” is a fundamental phenomenon in quantum mechanics and one that is central to quantum applications like communication, cryptography, computing, and information processing.

Bell’s inequality, or Bell’s theory, named after physicist John Stewart Bell, is the standard test used to determine the nature of correlation. However, one of the challenges with using Bell’s theorem is the requirement of seed randomness for selecting measurement settings.

According to a new theory presented by researchers at HHMI’s Janelia Research Campus and their colleagues at University College London, how useful a memory is for future situations determines where it resides in the brain.

The theory offers a new way of understanding systems consolidation, a process that transfers certain memories from the hippocampus – where they are initially stored – to the neocortex — where they reside long term.

Under the classical view of systems consolidation, all memories move from the hippocampus to the neocortex over time. But this view doesn’t always hold up; research shows some memories permanently reside in the hippocampus and are never transferred to the neocortex.

The Nobel Physics Prize was awarded on Tuesday to three scientists for their work on attoseconds, which are almost unimaginably short periods of time.

Their work using lasers gives scientists a tool to observe and possibly even manipulate electrons, which could spur breakthroughs in fields such as electronics and chemistry, experts told AFP.

Attoseconds are a billionth of a billionth of a second.

Scientists testing a new method of sequencing single cells have unexpectedly changed our understanding of the rules of genetics.

The genome of a protist has revealed a seemingly unique divergence in the DNA code signaling the end of a gene, suggesting the need for further research to better understand this group of diverse organisms.

Dr. Jamie McGowan, a postdoctoral scientist at the Earlham Institute, analyzed the genome sequence of a microscopic organism—a protist—isolated from a freshwater pond at Oxford University Parks. The research was published in PLoS Genetics.

The use of artificial intelligence has played an important role in science teaching and learning. The purpose of this study was to fill a gap in the current review of research on AI in science education (AISE) in the early stage of education by systematically reviewing existing research in this area. This systematic review examined the trends and research foci of AI in the science of early stages of education. This review study employed a bibliometric analysis and content analysis to examine the characteristics of 76 studies on Artificial Intelligence in Science Education (AISE) indexed in Web of Science and Scopus from 2013 to 2023. The analytical tool CiteSpace was utilized for the analysis.