A US startup is looking to our closest satellite to fill a resources gap here on Earth. Helium-3 is rare on terra firma, but is thought to be abundant in the regolith of the Moon. Interlune has now revealed a full-scale excavator prototype that forms a key component of its lunar Harvester.
The shortage of helium-3 – a stable isotope of helium important for applications ranging from energy production to medical research – was first identified in the US toward the middle of 2008. The US government officially recognized the issue in early 2009, and mitigation efforts put in place.
“The United States supply of 3He comes from the decay of tritium (3H), which the Nation had in large quantities because of our nuclear weapons complex; however, the tritium stockpile has declined in recent years through radioactive decay and is expected to decline in the future because of reduced demand for tritium,” read the intro to a National Isotope Development Center newsletter from 2014.
Tech News : Dubai residents will soon enjoy free access to ChatGPT Plus, a premium AI chatbot, thanks to a partnership between OpenAI and the UAE government. This
Interestingly, however, despite Komatsu’s early lead, Vermeer and Interlune seem to have caught up and could be ahead. For example, the new prototype is bigger and full-scale, showing great promise through testing.
The Vermeer-Interlune excavator has a larger excavation capacity, more funding and government support. To this end, Interlune is targeting a lunar mission by 2030.
“The high-rate excavation needed to harvest helium-3 from the moon in large quantities has never been attempted before, let alone with high efficiency,” said Gary Lai, Interlune co-founder and CTO.
Classical biomedical data science models are trained on a single modality and aimed at one specific task. However, the exponential increase in the size and capabilities of the foundation models inside and outside medicine shows a shift toward task-agnostic models using large-scale, often internet-based, data. Recent research into smaller foundation models trained on specific literature, such as programming textbooks, demonstrated that they can display capabilities similar to or superior to large generalist models, suggesting a potential middle ground between small task-specific and large foundation models. This study attempts to introduce a domain-specific multimodal model, Congress of Neurological Surgeons (CNS)-Contrastive Language-Image Pretraining (CLIP), developed for neurosurgical applications, leveraging data exclusively from Neurosurgery Publications.
METHODS:
We constructed a multimodal data set of articles from Neurosurgery Publications through PDF data collection and figure-caption extraction using an artificial intelligence pipeline for quality control. Our final data set included 24 021 figure-caption pairs. We then developed a fine-tuning protocol for the OpenAI CLIP model. The model was evaluated on tasks including neurosurgical information retrieval, computed tomography imaging classification, and zero-shot ImageNet classification.
“Space weather can impact systems that use IT for critical functions and everyday processes,” James Spann, a senior scientist at the Office of Space Weather Observations at the U.S. National Oceanic and Atmospheric Administration’s (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) department, told Space.com in an email. “These space weather impacts can have the same symptoms as a cyberattack, where systems will be brought down, or lockup, or transmit erroneous information.”
NESDIS oversaw a tabletop space weather exercise conducted in May 2024, the first such drill testing the U.S. preparedness for a major solar storm. Results of the exercise, which brought together 35 US government agencies, were published in a report in April.
In one of the simulations during the exercise, NOAA and the U.S. Air Force reported a severe solar flare and radio burst, but another federal department or agency “reported contradictory information, suggesting that the radio and communications disruptions were possibly the result of a cyberattack,” according to the report. Above all, it showed the need for effective communication following such events.
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Artificial intelligence could be affecting the scientific rigor of new research, according to a study from the University of Surrey.
The research team has called for a range of measures to reduce the flood of “low-quality” and “science fiction” papers, including stronger peer review processes and the use of statistical reviewers for complex datasets.
In a study published in PLOS Biology, researchers reviewed papers proposing an association between a predictor and a health condition using an American government dataset called the National Health and Nutrition Examination Survey (NHANES), published between 2014 and 2024.
A new technique that uses soundwaves to separate materials for recycling could help prevent potentially harmful chemicals leaching into the environment.
Researchers at the University of Leicester have achieved a major milestone in fuel cell recycling, advancing techniques to efficiently separate valuable catalyst materials and fluorinated polymer membranes (PFAS) from catalyst-coated membranes (CCMs). The articles are published in RSC Sustainability and Ultrasonic Sonochemistry.
This development addresses critical environmental challenges posed by PFAS—often referred to as “forever chemicals”—which are known to contaminate drinking water and have serious health implications. The Royal Society of Chemistry has urged government intervention to reduce PFAS levels in UK water supplies.
