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Designing in situ power stations for future Mars missions
You’re in the lab analyzing Martian regolith samples within your cozy Mars habitat serving on the fifth human mission to Mars. The power within the habitat has been flowing flawlessly thanks to the MARS-MES (Mars Atmospheric Resource & Multimodal Energy System), including the general habitat lighting, science lab, sleeping quarters, exercise equipment, the virtual reality headsets the crew use for rest & relaxation, oxygen and fuel generation, and water. All this from converting the Martian atmosphere into workable electricity.
While this scenario might be decades away, scientists on Earth are working hard to make this concept a reality today. This includes a team of scientists from China who propose using a novel concept for converting the thin Martian atmosphere into heat and electricity. Their findings were recently published in National Science Review and could help revolutionize how electricity is produced on Mars through a process called in situ resource utilization (ISRU) without the need for power or power supplies being shipped from Earth.
For the study, the researchers propose several concepts for producing power and electricity on a future human Mars mission, including Martian air capture, in situ power generation and storage, and life support resources transformation. The team notes all these methods carry their own benefits and challenges while emphasizing the importance of using ISRU for powering future human Mars missions.
How everyday devices could train AI faster while keeping personal data on-device
A new method developed by MIT researchers can accelerate a privacy-preserving artificial intelligence training method by about 81%. This advance could enable a wider array of resource-constrained edge devices, like sensors and smartwatches, to deploy more accurate AI models while keeping user data secure.
The MIT researchers boosted the efficiency of a technique known as federated learning, which involves a network of connected devices that work together to train a shared AI model.
In federated learning, the model is broadcast from a central server to wireless devices. Each device trains the model using its local data and then transfers model updates back to the server. Data are kept secure because they remain on each device.
How AI is finding cancer treatments with fewer side-effects | BBC News
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Experimental quantum kernel trick with nuclear spins in a solid
Kusumoto, T., Mitarai, K., Fujii, K. et al. Experimental quantum kernel trick with nuclear spins in a solid. npj Quantum Inf 7, 94 (2021). https://doi.org/10.1038/s41534-021-00423-0
Designing better quantum circuits with AI
Researchers from the group of theoretical physicist Hans Briegel have collaborated with NVIDIA to develop an AI method that automatically generates efficient quantum circuits, a key bottleneck in making quantum computers practically useful.
The work was published in Machine Learning: Science and Technology, in a paper titled “Synthesis of discrete–continuous quantum circuits with multimodal diffusion models.”
Before a quantum computer can perform any useful task, a quantum algorithm needs to be translated into a sequence of elementary quantum operations, known as quantum gates. Writing these quantum circuits efficiently is one of the hardest open problems in the field.
The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
We examine how artificial intelligence transforms the core pillars of collaboration— performance, expertise sharing, and social engagement—through a pre-registered field experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods company. Working on real product innovation challenges, professionals were randomly assigned to work either with or without AI, and either individually or with another professional in new product development teams. Our findings reveal that AI significantly enhances performance: individuals with AI matched the performance of teams without AI, demonstrating that AI can effectively replicate certain benefits of human collaboration. Moreover, AI breaks down functional silos. Without AI, R&D professionals tended to suggest more technical solutions, while Commercial professionals leaned towards commerciallyoriented proposals.
Surrounded by stardust: Antarctic ice cores confirm Earth is accumulating iron-60 from local interstellar cloud
Our solar system is currently passing through the Local Interstellar Cloud, a region of highly diluted gas and dust between the stars. On its path, Earth continuously accumulates iron-60, a rare radioactive isotope of iron produced in stellar explosions. This has now been confirmed by an international research team led by the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) through the analysis of Antarctic ice tens of thousands of years old. From the steady but time-varying influx, the researchers conclude that the radioactive isotope has been stored within the cloud since a long-past stellar explosion. The results have been published in the journal Physical Review Letters.
Iron-60 is formed in the interiors of massive stars and is ejected into space when they explode. Geological archives show that our solar system was hit twice by iron-60 from supernovae millions of years ago. In more recent times, however, there have been no nearby stellar explosions—and thus no direct supply of iron-60. When scientists discovered iron-60 in Antarctic surface snow less than twenty years old a few years ago, the question of its origin arose.
“Our idea was that the Local Interstellar Cloud contains iron-60 and can store it over long time periods. As the solar system moves through the cloud, Earth could collect this material. However, we couldn’t prove this at the time,” explains Dr. Dominik Koll from the Institute of Ion Beam Physics and Materials Research at HZDR.