Lifeboat Foundation

A key challenge in neuroscience is to understand how the brain can adapt to a changing world, even with a relatively static anatomy. The way the brain’s areas are structurally and functionally related to each other—its connectivity—is a key component. In order to explain its dynamics and functions, we also need to add another piece to the puzzle: receptors.

Now, a new mapping by Human Brain Project (HBP) researchers from the Forschungszentrum Jülich (Germany) and Heinrich-Heine-University Düsseldorf (Germany), in collaboration with scientists from the University of Bristol (UK), New York University (U.S.), Child Mind Institute (U.S.), and University of Paris Cité (France) had made advances on our understanding of the distribution of receptors across the brain.

The findings were published in Nature Neuroscience, and the data is now freely available to the neuroscientific community via the HBP’s EBRAINS infrastructure.

Superfast, subatomic-sized particles called muons have been used to wirelessly navigate underground for the first time. By using muon-detecting ground stations synchronized with an underground muon-detecting receiver, researchers at the University of Tokyo were able to calculate the receiver’s position in the basement of a six-story building.

As GPS cannot penetrate rock or water, this new technology could be used in future search and rescue efforts, to monitor undersea volcanoes, and guide autonomous vehicles underground and underwater. The findings are published in the journal iScience.

GPS, the global positioning system, is a well-established navigation tool and offers an extensive list of positive applications, from safer air travel to real-time location mapping. However, it has some limitations. GPS signals are weaker at higher latitudes and can be jammed or spoofed (where a counterfeit signal replaces an authentic one). Signals can also be reflected off surfaces like walls, interfered with by trees, and can’t pass through buildings, rock or water.

Early Dark Energy Spectroscopic Instrument (DESI) release holds nearly two million objects, including distant galaxies, quasars and stars in our own Milky Way.

Dark Energy Spectroscopic Instrument (DESI), the most robust multi-object survey spectrograph, capable of mapping more than 40 million galaxies, quasars, and stars, recorded an 80-terabyte data set this Tuesday.

Continue reading “First batch of DESI data available for scientists to mine” »

Photosynthesis. The maps elucidate the complex energy transfer process in photosynthesizing bacteria, providing a clear picture of how sunlight energy is channeled from the outer to the inner molecular ring of the light-harvesting complex.

Systems obeying quantum mechanics are notoriously difficult to visualize, but researchers at the University of Illinois Urbana-Champaign have developed an illustration technique that displays quantum features in an easy-to-read diagram called a coherence map. The researchers used these maps to study the quantum mechanisms that underlay photosynthesis, the process by which plants and some bacteria use sunlight to convert carbon dioxide and water into food.

This image of galaxy cluster MACS J1206.2–0847 (or MACS 1,206 for short) is part of a broad survey with NASA’s Hubble Space Telescope.

The distorted shapes in the cluster are distant galaxies from which the light is bent by the gravitational pull of an invisible material called dark matter within the cluster of galaxies. This cluster is an early target in a survey that will allow astronomers to construct the most detailed dark matter maps of more galaxy clusters than ever before.

These maps are being used to test previous, but surprising, results that suggest that dark matter is more densely packed inside clusters than some models predict. This might mean that galaxy cluster assembly began earlier than commonly thought.

A recently discovered formation of galaxies spanning 3.3 billion light-years is one of the largest known structures in the universe, contradicting some of the most fundamental beliefs of astronomers about the cosmos. The Giant Arc is composed of galaxies, galaxy clusters, and a significant amount of gas and dust. It is located 9.2 billion light-years away and covers approximately one-fifteenth of the visible universe.

The discovery was “fortuitous,” according to Alexia Lopez, a doctoral candidate in cosmology at the University of Central Lancashire (UCLan) in the United Kingdom. Lopez was creating maps of the night sky using light from around 120,000 quasars, which are the bright centres of galaxies where supermassive black holes consume matter and generate energy.

By measuring magnesium’s imprints, Lopez could calculate the distance to the intervening gas and dust, as well as the composition of the substance. The quasars were used as “spotlights in a dark room,” illuminating the intervening matter, according to Lopez. A structure began to emerge in the middle of the cosmic maps, a massive arc that was an indication of the Giant Arc.

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Does your robot know where it is right now? Does it? Are you sure? And what about all of its robot friends—do they know where they are too? This is important. So important, in fact, that some would say that multirobot simultaneous localization and mapping (SLAM) is a crucial capability to obtain timely situational awareness over large areas. Those some would be a group of MIT roboticists who just won the IEEE Transactions on Robotics Best Paper Award for 2022, presented at this year’s IEEE International Conference on Robotics and Automation (ICRA 2023), in London. Congratulations!

Out of more than 200 papers published in Transactions on Robotics last year, reviewers and editors voted to present the 2022 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award to Yulun Tian, Yun Chang, Fernando Herrera Arias, Carlos Nieto-Granda, Jonathan P. How, and Luca Carlone from MIT for their paper Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems.

I had an amazing experience at the Foresight Institute’s Whole-Brain Emulation (WBE) Workshop at a venue near Oxford! For more information and a list of participants, see: https://foresight.org/whole-brain-emulation-workshop-2023/ I had the opportunity to work within a group of some of the most brilliant, ambitious, and visionary people I’ve ever encountered on the quest for recreating the human brain in a computer. We also discussed in depth the existential risks of upcoming artificial superintelligence and how to mitigate these risks, perhaps with the aid of WBE.

My subgroup focused on exploring the challenge of human connectomics (mapping all of the neurons and synapses in the brain).

WBE is a potential technology to generate software intelligence that is human-aligned simply by being based directly on human brains. Generally past discussions have assumed a fairly long timeline to WBE, while past AGI timelines had broad uncertainty. There were also concerns that the neuroscience of WBE might boost AGI capability development without helping safety, although no consensus did develop. Recently many people have updated their AGI timelines towards earlier development, raising safety concerns. That has led some people to consider whether WBE development could be significantly speeded up, producing a differential technology development re-ordering of technology arrival that might lessen the risk of unaligned AGI by the presence of aligned software intelligence.

Tanzania has a lot of mineral respources I have all geological maps of Tanzania to prove it. Tanzania also found huge lithium deposits and many are scrambling for them. One thing Musk can do is buy companies to gain competitive advantage.

Dar es Salaam. Tesla, the American multinational automotive, artificial intelligence and clean energy company, has signed an agreement under which it will purchase Anode Active Material (AAM) from Tanzania.

By Alex Nelson Malanga

Continue reading “Tanzanian firm signs mining supply deal with Elon Musk’s Tesla” »