Lifeboat Foundation: Safeguarding Humanity
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Recently, researchers have been incorporating graphene-based materials into superconducting quantum computing devices, which promise faster, more efficient computing, among other perks. Until now, however, there’s been no recorded coherence for these advanced qubits, so there’s no knowing if they’re feasible for practical quantum computing.

In a paper published today in Nature Nanotechnology, the researchers demonstrate, for the first time, a coherent qubit made from graphene and exotic materials. These materials enable the qubit to change states through voltage, much like transistors in today’s traditional computer chips — and unlike most other types of superconducting qubits. Moreover, the researchers put a number to that coherence, clocking it at 55 nanoseconds, before the qubit returns to its ground state.

The work combined expertise from co-authors William D. Oliver, a physics professor of the practice and Lincoln Laboratory Fellow whose work focuses on quantum computing systems, and Pablo Jarillo-Herrero, the Cecil and Ida Green Professor of Physics at MIT who researches innovations in graphene.

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Large language models are widely adopted in a range of natural language tasks, such as question-answering, common sense reasoning, and summarization. These models, however, have had difficulty with tasks requiring quantitative reasoning, such as resolving issues in mathematics, physics, and engineering.

Researchers find quantitative reasoning an intriguing application for language models as they put language models to the test in various ways. The ability to accurately parse a query with normal language and mathematical notation, remember pertinent formulas and constants and produce step-by-step answers requiring numerical computations and symbolic manipulation are necessary for solving mathematical and scientific problems. Therefore, scientists have believed that machine learning models will require significant improvements in model architecture and training methods to solve such reasoning problems.

A new Google research introduces Minerva, a language model that uses sequential reasoning to answer mathematical and scientific problems. Minerva resolves such problems by providing solutions incorporating numerical computations and symbolic manipulation.

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The Space Force has assumed command of a new unit that will be focused on keeping an eye out for foreign threats in space, but it comes as Congress is warning the small service branch that it has to prepare to slow its growth.

Delta 18 and the brand-new National Space Intelligence Center were officially commissioned late last month at Wright-Patterson Air Force Base in Dayton, Ohio. It will be staffed by nearly 350 civilian and military personnel.

Delta 18’s mission is to “deliver critical intelligence on threat systems, foreign intentions, and activities in the space domain to support national leaders, allies, partners and joint war fighters,” according to a press release.

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While you read this sentence, the neurons in your brain are communicating with one another by firing off quick electrical signals. They communicate with one another via synapses, which are tiny, specialized junctions.

There are many various kinds of synapses that develop between neurons, including “excitatory” and “inhibitory,” and scientists are still unsure of the specific methods by which these structures are formed. A biochemistry team has provided significant insight into this topic by demonstrating that the types of chemicals produced from synapses ultimately determine which types of synapses occur between neurons.

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Video games seem to be a unique type of digital activity. Empirically, the cognitive benefits of video games have support from multiple observational and experimental studies23,24,25. Their benefits to intelligence and school performance make intuitive sense and are aligned with theories of active learning and the power of deliberate practice26,27. There is also a parallel line of evidence from the literature on cognitive training intervention apps28,29, which can be considered a special (lab developed) category of video games and seem to challenge some of the same cognitive processes. Though, like for other digital activities, there are contradictory findings for video games, some with no effects30,31 and negative effects32,33.

The contradictions among studies on screen time and cognition are likely due to limitations of cross-sectional designs, relatively small sample sizes, and, most critically, failures to control for genetic predispositions and socio-economic context10. Although studies account for some confounding effects, very few have accounted for socioeconomic status and none have accounted for genetic effects. This matters because intelligence, educational attainment, and other cognitive abilities are all highly heritable9,34. If these genetic predispositions are not accounted for, they will confound the potential impact of screen time on the intelligence of children. For example, children with a certain genetic background might be more prone to watch TV and, independently, have learning issues. Their genetic background might also modify the impact over time of watching TV. Genetic differences are a major confounder in many psychological and social phenomena35,36, but until recently this has been hard to account for because single genetic variants have very small effects. Socioeconomic status (SES) could also be a strong moderator of screen time in children37. For example, children in lower SES might be in a less functional home environment that makes them more prone to watch TV as an escape strategy, and, independently, the less functional home environment creates learning issues. Although SES is commonly assumed to represent a purely environmental factor, half of the effect of SES on educational achievement is probably genetically mediated38,39—which emphasizes the need for genetically informed studies on screen time.

Here, we estimated the impact of different types of screen time on the change in the intelligence of children in a large, longitudinal sample, while accounting for the critical confounding influences of genetic and socioeconomic backgrounds. In specific, we had a strong expectation that time spent playing video games would have a positive effect on intelligence, and were interested in contrasting it against other screen time types. Our sample came from the ABCD study (http://abcdstudy.org) and consisted of 9,855 participants aged 9–10 years old at baseline and 5,169 of these followed up two years later.

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