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Category: robotics/AI – Page 1,733

Part of the Divine Mind, and so we are.

The most recent observations at both quantum and cosmological scales are casting serious doubts on our current models. For instance, at quantum scale, the latest electronic hydrogen proton radius measurement resulted in a much smaller radius than the one predicted by the standard model of particles physics, which now is off by 4%. At cosmological scale, the amount of observations regarding black holes and galactic formation heading in the direction of a radically different cosmological model, is overwhelming. Black holes have shown being much older than their hosting galaxies, galactic formation is much younger than our models estimates, and there is evidence of at least 64 black holes aligned with respect to their axis of rotation, suggesting the presence of a large scale spatial coherence in angular momentum that is impossible to predict with our current models. Under such scenario, it should not fall as a surprise the absence of a better alternative to unify quantum theory and relativity, and thus connect the very small to the very big, than the idea that the universe is actually a neural network. And for this reason, a theory of everything would be based on it.


As explained in Targemann’s interview to Vanchurin on Futurism, the work of Vanchurin, proposes that we live in a huge neural network that governs everything around us.

“it’s a possibility that the entire universe on its most fundamental level is a neural network… With this respect it could be considered as a proposal for the theory of everything, and as such it should be easy to prove it wrong”. Vitaly Vanchurin The idea was born when he was studying deep machine learning. He wrote the book “Towards a theory of machine learning”, in order to apply the methods of statistical mechanics to study the behavior of neural networks, and he saw that in certain limits the learning (or training) dynamics of neural networks is very similar to the quantum dynamics. So, he decided to explore the idea that the physical world is a neural network.

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Artificial intelligence and machine learning are already an integral part of our everyday lives online. For example, search engines such as Google use intelligent ranking algorithms, and video streaming services such as Netflix use machine learning to personalize movie recommendations.

As the demands for AI online continue to grow, so does the need to speed up AI performance and find ways to reduce its energy consumption.

Now a University of Washington-led team has come up with a system that could help: an core prototype that uses phase-change material. This system is fast, energy efficient and capable of accelerating the used in AI and . The technology is also scalable and directly applicable to cloud computing.

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Researchers from the Max Planck Society assessed humans’ capabilities for controlling killer AI. Read the details.

Researchers from Osaka University propose a concept for next-generation ultra-intense lasers, possibly increasing the current record from 10 Petawatts to 500 Petawatts.

Ultra-intense lasers with ultra-short pulses and ultra-high energies are powerful tools for exploring unknowns in physics, cosmology, material science, etc. With the help of the famous technology “Chirped Pulse Amplification (CPA)” (2018 Nobel Prize in Physics), the current record has reached 10 Petawatts (or 1016 Watts). In a study recently published in Scientific Reports, researchers from Osaka University proposed a concept for next-generation ultra-intense lasers with a simulated peak power up to the Exawatt class (1 Exawatt equals 1000 Petawatts).

The laser, which was invented by Dr. T. H. Maiman in 1960, has one important characteristic of high intensity (or high peak power for pulse lasers): historically, laser peak power has experienced two-stage development. Just after the birth of the laser, Q-switching and mode-locking technologies increased laser peak power to Kilowatt (103 Watt) and Gigawatt (109 Watt) levels. After CPA technology was invented by Gérard Mourou and Donna Strickland in 1985, by which material damage and optical nonlinearity were avoided, laser peak power was dramatically increased to Terawatt (1012 Watt) and Petawatt (1015 Watt) levels. Today, two 10-Petawatt CPA lasers have been demonstrated in Europe (ELI-NP laser) and China (SULF laser), respectively.

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Researchers from the Max Planck Society assessed humans’ capabilities for controlling killer AI. Read the details.

Researchers have found a simple way to eliminate almost all sequencing errors produced by a widely used portable DNA sequencer, potentially enabling scientists working outside the lab to study and track microorganisms like the SARS-CoV-2 virus more efficiently.

Using special molecular tags, the team was able to reduce the five-to-15 percent error rate of Oxford Nanopore Technologies’ MinION device to less than 0.005 percent — even when sequencing many long stretches of DNA at a time.

“The MinION has revolutionized the field of genomics by freeing DNA sequencing from the confines of large laboratories,” says Ryan Ziels, an assistant professor of civil engineering at the University of British Columbia and the co-lead author of the study, which was published on January 112021, in Nature Methods. “But until now, researchers haven’t been able to rely on the device in many settings because of its fairly high out-of-the-box error rate.”

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The result was a bizarre, Lego-like human tissue that replicates the basic circuits behind how we decide to move. Without external prompting, when churned together like ice cream, the three ingredients physically linked up into a fully functional circuit. The 3D mini-brain, through the information highway formed by the artificial spinal cord, was able to make the lab-grown muscle twitch on demand.

In other words, if you think isolated mini-brains—known formally as brain organoids—floating in a jar is creepy, upgrade your nightmares. The next big thing in probing the brain is assembloids—free-floating brain circuits—that now combine brain tissue with an external output.

The end goal isn’t to freak people out. Rather, it’s to recapitulate our nervous system, from input to output, inside the controlled environment of a Petri dish. An autonomous, living brain-spinal cord-muscle entity is an invaluable model for figuring out how our own brains direct the intricate muscle movements that allow us stay upright, walk, or type on a keyboard.

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Elon Musk’s Neuralink showcases working implanted brain computer and promises future health benefits.

Elon Musk company Neuralink has been researching how directly interfacing with the brain could be used as therapy for chronic and debilitating medical conditions, as well as exploring how technological augmentation could expand and develop the capabilities of the human brain.

Longevity. Technology: Neuralink have been decidedly cagey about their progress, despite having $158m, in funding, $100m of which comes from Musk himself [1]. Tonight’s live broadcast featured misbehaving pigs (I’m looking at you here, Gertrude!) and a glimpse of the future of robotic surgery, but Elon Musk continued to operate at his self-proclaimed “speed of thought” pushing the boundaries between brains and technology.

Prior to today’s update, the last real news was in July last year, when they announced they were developing a “sewing machine-like” device that could implant incredibly thin (4 to 6 μm) threads in the brain. The company also demonstrated a system that read information from a lab rat via 1500 electrodes and revealed they planned to start experiments with humans in 2020 [2].

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