Lifeboat Foundation

The price of bitcoin plunged about 10% hours after it was revealed that Elon Musk’s SpaceX sold the cryptocurrency.

The Wall Street Journal reported on Thursday that SpaceX, which first purchased bitcoin in 2021, wrote down the value of its bitcoin holdings by a total of $373 million in 2021 and 2022 and has sold the crypto.

The write-down coincides with a steep drop in bitcoin’s price, which crashed in late 2021, setting off a “crypto winter” that extended through most of 2022.

Scientists working in connectomics, a research field occupied with the reconstruction of neuronal networks in the brain, are aiming at completely mapping of the millions or billions of neurons found in mammalian brains. In spite of impressive advances in electron microscopy, the key bottleneck for connectomics is the amount of human labor required for the data analysis. Researchers at the Max Planck Institute for Brain Research in Frankfurt, Germany, have now developed reconstruction software that allows researchers to fly through the brain tissue at unprecedented speed. Together with the startup company scalable minds they created webKnossos, which turns researchers into brain pilots, gaining an about 10-fold speedup for data analysis in connectomics.

Billions of nerve cells are working in parallel inside our brains in order to achieve behaviours as impressive as hypothesizing, predicting, detecting, thinking. These neurons form a highly complex network, in which each nerve cell communicates with about one thousand others. Signals are sent along ultrathin cables, called axons, which are sent from each neuron to its about one thousand “followers.”

Continue reading “10-fold Speed up For The Reconstruction of Neuronal Networks” »

Seemingly countless self-help books and seminars tell you to tap into the right side of your brain to stimulate creativity. But forget the “right-brain” myth—a new study suggests it’s how well the two brain hemispheres communicate that sets highly creative people apart.

For the study, statisticians David Dunson of Duke University and Daniele Durante of the University of Padova analyzed the network of white matter connections among 68 separate brain regions in healthy college-age volunteers.

The brain’s white matter lies underneath the outer grey matter. It is composed of bundles of wires, or axons, which connect billions of neurons and carry electrical signals between them.

Another concern was the dissipation of electrical power on the Enchilada Trap, which could generate significant heat, leading to increased outgassing from surfaces, a higher risk of electrical breakdown and elevated levels of electrical field noise. To address this issue, production specialists designed new microscopic features to reduce the capacitance of certain electrodes.

“Our team is always looking ahead,” said Sandia’s Zach Meinelt, the lead integrator on the project. “We collaborate with scientists and engineers to learn about the kind of technology, features and performance improvements they will need in the coming years. We then design and fabricate traps to meet those requirements and constantly seek ways to further improve.”

Sandia National Laboratories is a multimission laboratory operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. Sandia Labs has major research and development responsibilities in nuclear deterrence, global security, defense, energy technologies and economic competitiveness, with main facilities in Albuquerque, New Mexico, and Livermore, California.

Recent advancements in deep learning have significantly impacted computational imaging, microscopy, and holography-related fields. These technologies have applications in diverse areas, such as biomedical imaging, sensing, diagnostics, and 3D displays. Deep learning models have demonstrated remarkable flexibility and effectiveness in tasks like image translation, enhancement, super-resolution, denoising, and virtual staining. They have been successfully applied across various imaging modalities, including bright-field and fluorescence microscopy; deep learning’s integration is reshaping our understanding and capabilities in visualizing the intricate world at microscopic scales.

In computational imaging, prevailing techniques predominantly employ supervised learning models, necessitating substantial datasets with annotations or ground-truth experimental images. These models often rely on labeled training data acquired through various methods, such as classical algorithms or registered image pairs from different imaging modalities. However, these approaches have limitations, including the laborious acquisition, alignment, and preprocessing of training images and the potential introduction of inference bias. Despite efforts to address these challenges through unsupervised and self-supervised learning, the dependence on experimental measurements or sample labels persists. While some attempts have used labeled simulated data for training, accurately representing experimental sample distributions remains complex and requires prior knowledge of sample features and imaging setups.

To address these inherent issues, researchers from the UCLA Samueli School of Engineering introduced an innovative approach named GedankenNet, which, on the other hand, presents a revolutionary self-supervised learning framework. This approach eliminates the need for labeled or experimental training data and any resemblance to real-world samples. By training based on physics consistency and artificial random images, GedankenNet overcomes the challenges posed by existing methods. It establishes a new paradigm in hologram reconstruction, offering a promising solution to the limitations of supervised learning approaches commonly utilized in various microscopy, holography, and computational imaging tasks.

Quantum mechanically entangled groups of eight and ten ultracold atoms provide a critical demonstration for optical-lattice-based quantum processing.

The way in which supermassive black holes grew to tremendous sizes in the early universe has been a mystery for astronomers, but the puzzle could soon be solved.

Two molecular languages at the origin of life have been successfully recreated and mathematically validated, thanks to pioneering work by Canadian scientists at Université de Montréal.

The study, “Programming chemical communication: allostery vs. multivalent mechanism,” published August 15, 2023 in the Journal of the American Chemical Society, opens new doors for the development of nanotechnologies with applications ranging from biosensing, drug delivery and molecular imaging.

Living organisms are made up of billions of nanomachines and nanostructures that communicate to create higher-order entities able to do many essential things, such as moving, thinking, surviving and reproducing.

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Faith Popcorn founded her futurist marketing consultancy in 1974. She’s been called “The Trend Oracle” by the NY Times and “The Nostradamus of Marketing” by Fortune. Faith is a trusted advisor to the CEOs of Fortune 200 companies and has predicted a variety of trends such as Cocooning and its impact on the COVID culture, Social Media, and The Metaverse. She has been invited to speak all over the planet and is the best-selling author of four books. Finally, in her own words, Faith is a jew educated at a Christian School, a Caucasian who grew up among Asians, a 6^th generation New Yorker and the adopted mother of 2 girls from China.

During our 2-hour conversation with Faith Popcorn, we cover a variety of interesting topics such as why she is the Cassandra of our era; her unique background and upbringing; the origins of her Faith Popcorn name; futurism, misogyny and gender equality; her mission to bring a vision of what’s coming; saving the planet and the trends to pay attention to; her client cases like Campbell Soup, Kodak, Coke, Pepsi, Tyson Foods and others; male vs female leaders; Futurism vs Applied Futurism; why the future is vegan; why the biggest shifts are in humanity, not in technology; trend recognition, utilization, and creation; AI and the singularity.