Lifeboat Foundation

High-energy neutrinos are extremely rare particles that have so far proved very difficult to detect. Fluxes of these rare particles were first detected by the IceCube Collaboration back in 2013.

Recent papers featured in Physical Review D and The Astrophysical Journal Letters found that nearby supernovae, especially Galactic ones, would be promising sources of high-energy neutrinos. This has inspired new studies exploring the possibility of detecting neutrinos originating from these sources using large particle collider detectors, such as the ATLAS detector at CERN.

Researchers at Harvard University, University of Nevada and Pennsylvania State University recently demonstrated that the ATLAS detector can measure the flux of high-energy supernova neutrinos. Their new paper, published in Physical Review Letters, could inspire future efforts aimed at detecting fluxes of high-energy neutrinos.

Water and electronics don’t usually mix, but as it turns out, batteries could benefit from some H₂O.

By replacing the hazardous chemical electrolytes used in commercial batteries with water, scientists have developed a recyclable ‘water battery’ – and solved key issues with the emerging technology, which could be a safer and greener alternative.

Continue reading “New ‘Water Batteries’ Are Cheaper, Recyclable, And Won’t Explode” »

Despite major progress in Robotics and AI, robots are still basically “zombies” repeatedly achieving actions and tasks without understanding what they are doing. Deep-Learning AI programs classify tremendous amounts of data without grasping the meaning of their inputs or outputs. We still lack a genuine theory of the underlying principles and methods that would enable robots to understand their environment, to be cognizant of what they do, to take appropriate and timely initiatives, to learn from their own experience and to show that they know that they have learned and how. The rationale of this paper is that the understanding of its environment by an agent (the agent itself and its effects on the environment included) requires its self-awareness, which actual ly is itself emerging as a result of this understanding and the distinction that the agent is capable to make between its own mind-body and its environment. The paper develops along five issues: agent perception and interaction with the environment; learning actions; agent interaction with other agents–specifically humans; decision-making; and the cognitive architecture integrating these capacities.

We are interested here in robotic agents, i.e., physical machines with perceptual, computational and action capabilities. We believe we still lack a genuine theory of the underlying principles and methods that would explain how we can design robots that can understand their environment and not just build representations lacking meaning, to be cognizant about what they do and about the purpose of their actions, to take timely initiatives beyond goals set by human programmers or users, and to learn from their own experience, knowing what they have learned and how they did so.

Wang, H., Xue, Y., Qu, Y. et al. Multidimensional Bose quantum error correction based on neural network decoder. npj Quantum Inf 8, 134 (2022). https://doi.org/10.1038/s41534-022-00650-z.

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An intuitive modeling interface for infinite-dimensional optimization problems. — infiniteopt/InfiniteOpt.jl

Near 99 percent accuracy of bug patching in python programming language.

Repilot, a patch generation tool introduced in the ESEC/FSE’23 paper “Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair”

Year 2023

LLMs trained with a finite attention window can be extended to infinite sequence lengths without any fine-tuning.

Some excellent food for thought face_with_colon_three

We now have everything we need to build a physics engine with infinite precision.

Continue reading “Perfect, Infinite-Precision, Game Physics in Python (Part 3)” »

Organ-like groups of cells can be grown from amniotic fluid samples and offer hope for studying congenital conditions.