Lifeboat Foundation

It is expected to deliver performance up to eight times faster than its predecessor.

The Los Alamos National Laboratory (LANL) is in the final stages of setting up a new supercomputer dubbed Crossroads that will allow it to test the US nuclear stockpile without major tests, a press release said. The system has been supplied by Hewlett Packard and installation began in June of this year.

The Department of Energy (DoE) has been tasked with the responsibility of ensuring that the US nuclear stockpile can be relied upon if and when it needs to be used. For this purpose, the federal agency does not actually test the warheads but carries out simulations to determine the storage, maintenance, and efficacy of the weapons.

ChatGPT is not officially available in China.

China can’t buy US chips required for advanced artificial intelligence models, but that’s not stopping the country from churning out AI models. After receiving regulatory approval from the country’s internet watchdog, several Chinese tech companies launched their respective AI chatbots last week. This comes in response to OpenAI’s ChatGPT, which, since its launch, has prompted rival tech companies around the globe to launch their own chatbots.

According to a Reuters report, Baidu CEO Robin Li has claimed that over 70 large language models (LLMs) with over 1 billion parameters have been released in China.

Continue reading “China approves chatbots for public use in tech war with US” »

EU law requires manufacturers to adopt Type-C chargers in phones, tablets, etc by December 2024.

Apple will switch out its proprietary Lightning charging port in iPhones to be compatible with a USB Type-C cable instead, reported.

The EU law says that by 2024-end, all mobile phones, tablets, and cameras sold in countries under the EU will have to be equipped with a USB-C charging port. From spring 2026, the obligation will extend to laptops as well. The law’s overall purpose is to cut down on environmental waste and save consumers an estimated $247 million per annum.

A team of scientists from Ames National Laboratory has developed a new machine learning model for discovering critical-element-free permanent magnet materials. The model predicts the Curie temperature of new material combinations. It is an important first step in using artificial intelligence to predict new permanent magnet materials. This model adds to the team’s recently developed capability for discovering thermodynamically stable rare earth materials. The work is published in Chemistry of Materials.

High performance magnets are essential for technologies such as wind energy, data storage, electric vehicles, and magnetic refrigeration. These magnets contain critical materials such as cobalt and rare earth elements like neodymium and dysprosium. These materials are in high demand but have limited availability. This situation is motivating researchers to find ways to design new magnetic materials with reduced critical materials.

Machine learning (ML) is a form of artificial intelligence. It is driven by computer algorithms that use data and trial-and-error algorithms to continually improve its predictions. The team used experimental data on Curie temperatures and theoretical modeling to train the ML algorithm. Curie temperature is the maximum temperature at which a material maintains its magnetism.

In a major breakthrough, scientists have built a tool to predict the odour profile of a molecule, just based on its structure. It can identify molecules that look different but smell the same, as well as molecules that look very similar but smell totally different.

Professor Jane Parker, University of Reading, said: Vision research has wavelength, hearing research has frequency – both can be measured and assessed by instruments. But what about smell? We don’t currently have a way to measure or accurately predict the odour of a molecule, based on its molecular structure.

You can get so far with current knowledge of the molecular structure, but eventually you are faced with numerous exceptions where the odour and structure don’t match. This is what has stumped previous models of olfaction. The fantastic thing about this new ML generated model is that it correctly predicts the odour of those exceptions.

A combined team of physicists from the University of Sussex and the National Physical Laboratory, both in the U.K., has been designing experiments to identify ultra-light dark matter particles. In their paper published in the open-access New Journal of Physics, the group describes how they are attempting to use the high precision of atomic clocks to detect ultra-light dark matter particle “kicks” that would lead to time variations and, in so doing, would show evidence of dark matter.

Currently, dark matter is not something that has been shown to exist—instead it is more of a placeholder that has been created to explain observations of deviations from the Standard Model of physics—like certain gravitational effects on galaxies. Since its development as a theory back in the early 1930s, physicists around the world have been developing theories and experiments to prove that it exists.

Sadly, despite a lot of time and effort, no such proof has been found. In this new effort, the team in the U.K. is working on a novel way to add credence to dark matter theories—using atomic clocks to detect ultra-light dark matter particles.

Look, we write rather a lot about the Fermi Paradox, so trust us when we say that the Berserker Hypothesis may be the darkest explanation out there. Not only would it mean that the universe is a dead, lifeless husk, but it would also imply that our own destruction is imminent.

The Fermi Paradox at its most basic is, given the high probability that alien life exists out there (bearing in mind the vastness of space and that we keep finding planets within habitable zones), why has nobody got in touch yet?

Female kidneys are known to be more resilient to disease and injury, but males need not despair. A new USC Stem Cell-led study published in Developmental Cell describes not only how sex hormones drive differences in male and female mouse kidneys, but also how lowering testosterone can “feminize” this organ and improve its resilience.

“By exploring how differences emerge in male and female kidneys during development, we can better understand how to address sex-related health disparities for patients with kidney diseases,” said Professor Andy McMahon, the study’s corresponding author, and the director of the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at the Keck School of Medicine of USC.

First authors Lingyun “Ivy” Xiong and Jing Liu from the McMahon Lab and their collaborators identified more than 1,000 genes with different levels of activity in male and female mouse kidneys, in a study supported by the National Institutes of Health. The differences were most evident in the section of the kidney’s filtering unit known as the proximal tubule, responsible for reabsorbing most of the nutrients such as glucose and amino acids back into the blood stream.

An essential protein that acts as a gatekeeper for calcium entering cells promotes the growth of oral cancer and generates pain, according to a new study published in Science Signaling led by researchers at New York University College of Dentistry.

Targeting this protein—the ORAI1 calcium channel —could provide a new approach to treating oral cancer, which causes persistent pain that worsens as it progresses.

“Our results show that the ORAI1 channel fuels the growth of oral cancer tumors and produces an abundance of molecules that, once secreted, interact with neurons resulting in an increased sensitivity to pain,” said Ga-Yeon Son, a postdoctoral fellow in the Department of Molecular Pathobiology at NYU College of Dentistry and the study’s first author.