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Professional video editing, color correction, visual effects and audio post production all in a single application. Free and paid versions for Mac, Windows and Linux.
Hey and we are back ⊠this is Max Flow and we will get to know more about the information limitations of psyche.
Neurons are living cells with a metabolism; they need oxygen and glucose to survive, and when theyâve been working hard, we experience fatigue. Every status update we read on social media, every tweet or text message we get from a friend, is competing for resources in our brains.
With such attentional restrictions, itâs clear why many of us feel overwhelmed by managing some of the most basic aspects of life. Our focus is short and erratic, our decision-making abilities go out the window and a list of unfinished projects begins to pile up.
Attention is the most essential mental resource for any organism. It determines which aspects of the environment we deal with, and most of the time, various automatic, subconscious processes make the correct choice about what gets passed through to our conscious awareness. For this to happen, millions of neurons are constantly monitoring the environment to select the most important things for us to focus on.
Weâve created a world with thousands of exabytes of human-made information, each one of us experiences on average more than 70 thousand thoughts on any given day, on higher end up to 3,000 thoughts per hour or 50 per minute, just under one per second.
Today, each of us individually generates more information than ever before in human history. Our world is now awash in an unprecedented volume of data. Average human processes five times as much information as 30 years ago. The trouble is, our brains havenât evolved to be able to process it all.
A research group led by Professor Kenji Ohmori at the Institute for Molecular Science, National Institutes of Natural Sciences are using an artificial crystal of 30,000 atoms aligned in a cubic array with a spacing of 0.5 micron, cooled to near absolute zero temperature. By manipulating the atoms with a special laser light that blinks for 10 picoseconds, they succeeded in executing quantum simulation of a model of magnetic materials.
Their novel âultrafast quantum computerâ scheme demonstrated last year was applied to quantum simulation. Their achievement shows that their novel âultrafast quantum simulatorâ is an epoch-making platform, as it can avoid the issue of external noise, one of the biggest concerns for quantum simulators. The âultrafast quantum simulatorâ is expected to contribute to the design of functional materials and the resolution of social problems.
Their results were published online in Physical Review Letters.
Pat Bennettâs prescription is a bit more complicated than âTake a couple of aspirins and call me in the morning.â But a quartet of baby-aspirin-sized sensors implanted in her brain are aimed at addressing a condition thatâs frustrated her and others: the loss of the ability to speak intelligibly. The devices transmit signals from a couple of speech-related regions in Bennettâs brain to state-of-the-art software that decodes her brain activity and converts it to text displayed on a computer screen.
Bennett, now 68, is a former human resources director and onetime equestrian who jogged daily. In 2012, she was diagnosed with amyotrophic lateral sclerosis, a progressive neurodegenerative disease that attacks neurons controlling movement, causing physical weakness and eventual paralysis.
Our brains remember how to formulate words even if the muscles responsible for saying them out loud are incapacitated. A brain-computer hookup is making the dream of restoring speech a reality.
The human brain, with its intricate network of approximately 86 billion neurons, is arguably among the most complex specimens scientists have ever encountered. It holds an immense, yet currently immeasurable, wealth of information, positioning it as the pinnacle of computational devices.
Grasping this level of intricacy is challenging, making it essential for us to employ advanced technologies that can decode the minute, intricate interactions happening within the brain at microscopic levels. Thus, imaging emerges as a pivotal instrument in the realm of neuroscience.
The new imaging and virtual reconstruction technology developed by Johann Danzlâs group at ISTA is a big leap in imaging brain activity and is aptly named LIONESS â Live Information Optimized Nanoscopy Enabling Saturated Segmentation. LIONESS is a pipeline to image, reconstruct, and analyze live brain tissue with a comprehensiveness and spatial resolution not possible until now.
This is leading to even better brain engineering đ đ đ đ đ.
Computer-augmented brains, cures to blindness, and rebuilding the brain after injury all sound like science fiction. Today, these disruptive technologies arenât just for Netflix, âTerminator,â and comic book fodder â in recent years, these advances are closer to reality than some might realize, and they have the ability to revolutionize neurological care.
Neurologic disease is now the worldâs leading cause of disability, and upwards of 11 million people have some form of permanent neurological problem from traumatic brain injuries and stroke. For example, if a traumatic brain injury has damaged the motor cortex â the region of the brain involved in voluntary movements â patients could become paralyzed, without hope of regaining full function. Or some stroke patients can suffer from aphasia, the inability to speak or understand language, due to damage to the brain regions that control speech and language comprehension.
Thanks to recent advances, sometimes lasting neurologic disease can be prevented. For example, if a stroke patient is seen quickly enough, life-threatening or-altering damage can be avoided, but itâs not always possible. Current treatments to most neurologic disease are fairly limited, as most therapies, including medications, aim to improve symptoms but canât completely recover lost brain function.
We often believe computers are more efficient than humans. After all, computers can complete a complex math equation in a moment and can also recall the name of that one actor we keep forgetting. However, human brains can process complicated layers of information quickly, accurately, and with almost no energy input: recognizing a face after only seeing it once or instantly knowing the difference between a mountain and the ocean. These simple human tasks require enormous processing and energy input from computers, and even then, with varying degrees of accuracy.
Creating brain-like computers with minimal energy requirements would revolutionize nearly every aspect of modern life. Funded by the Department of Energy, Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C) â a nationwide consortium led by the University of California San Diego â has been at the forefront of this research.
UC San Diego Assistant Professor of Physics Alex Frañó is co-director of Q-MEEN-C and thinks of the centerâs work in phases. In the first phase, he worked closely with President Emeritus of University of California and Professor of Physics Robert Dynes, as well as Rutgers Professor of Engineering Shriram Ramanathan. Together, their teams were successful in finding ways to create or mimic the properties of a single brain element (such as a neuron or synapse) in a quantum material.
Most of todayâs EVs use lithium-ion batteries, the same kind youâll find in your smartphone or laptop. These batteries all have two electrodes (one positive and one negative), and the negative one is usually made of graphite.
While the battery is being charged, the lithium ions flow from the side of the battery with the positive electrode to the side with the negative electrode. If the charging happens too fast, the flow can be disrupted, causing the battery to short circuit.
StoreDotâs EV battery replaces the graphite electrode with one made from nanoparticles based on the chemical element germanium â this allows the ions to flow more smoothly and quickly, enabling a faster charge.
Advance lays the groundwork for miniature devices for spectroscopy, communications, and quantum computing. Researchers have created chip-based photonic resonators that operate in the ultraviolet (UV) and visible regions of the spectrum and exhibit a record low UV light loss. The new resonators lay the groundwork for increasing the size, complexity, and fidelity of UV photonic integrated circuit (PIC) design, which could enable new miniature chip-based devices for applications such as spectroscopic sensing, underwater communication, and quantum information processing.
Founded in 2021, Virginia-based Procyon Photonics is a startup aiming to change the future of computing hardware with its focus on optical computing. What makes the company unique is that their entire team consists of current high school students, and its co-founder, CEO, and CTO, Sathvik Redrouthu, holds the distinction of being the worldâs youngest CEO in the photonic and optical computing sector.
Optical computing represents an innovative leap from traditional computing, which relies on electrons moving through wires and transistors. Instead, this relatively nascent field seeks to harness photons â particles of light â as the fundamental elements in computational processes. The promise of optical computing is compelling enough that industry giants like IBM and Microsoft, among others, are heavily investing in its research and development.
Procyon is attempting to differentiate itself in this competitive landscape not just by its youth, but with their technology. The team is pioneering a unique, industry-leading optical chip, and has published a conference paper detailing how a specialized form of matrix algebra could be executed on an optoelectronic chip.
