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OAK RIDGE, Tenn. — At Oak Ridge National Laboratory, the government-funded science research facility nestled between Tennessee’s Great Smoky Mountains and Cumberland Plateau that is perhaps best known for its role in the Manhattan Project, two supercomputers are currently rattling away, speedily making calculations meant to help tackle some of the biggest problems facing humanity.

You wouldn’t be able to tell from looking at them. A supercomputer called Summit mostly comprises hundreds of black cabinets filled with cords, flashing lights and powerful graphics processing units, or GPUs. The sound of tens of thousands of spinning disks on the computer’s file systems, and air cooling technology for ancillary equipment, make the device sound somewhat like a wind turbine — and, at least to the naked eye, the contraption doesn’t look much different from any other corporate data center. Its next-door neighbor, Frontier, is set up in a similar manner across the hall, though it’s a little quieter and the cabinets have a different design.

Yet inside those arrays of cabinets are powerful specialty chips and components capable of, collectively, training some of the largest AI models known. Frontier is currently the world’s fastest supercomputer, and Summit is the world’s seventh-fastest supercomputer, according to rankings published earlier this month. Now, as the Biden administration boosts its focus on artificial intelligence and touts a new executive order for the technology, there’s growing interest in using these supercomputers to their full AI potential.

With a gravitational field so strong that not even light can escape its grip, black holes are probably the most interesting and bizarre objects in the universe.

Due to their extreme properties, a theoretical description of these celestial bodies is impossible within the framework of Newton’s classical theory of gravity. It requires the use of general relativity, the theory proposed by Einstein in 1915, which treats gravitational fields as deformations in the fabric of space-time.

Black holes are usually formed from the collapse of massive stars during their final stage of evolution. Therefore, when a black hole is born, its mass does not exceed a few dozen solar masses.

Buckle up, because we’re entering the era of thinking machines that make humans look like chattering chimps! But don’t worry about polishing your resume to impress our future robot overlords just yet. The experts are wildly divided on when superintelligent AI will actually arrive. It’s like we’re staring at an AI time machine without knowing if it will teleport us to 2 years from now or 2 decades into the future!

In one corner, we have Mustafa Suleyman from Inflection AI. He says take a chill pill, we’ve got at least 10–20 more years before the AI apocalypse. But hang on…his company just whipped up the world’s 2nd biggest AI supercomputer! It’s cruising with 3X the horsepower of GPT-4, the chatbot with reading skills rivaling a university professor. So something tells me Suleyman’s timeline is slower than your grandma driving without her glasses.

Meanwhile, OpenAI is broadcasting a very different arrival time. They believe superintelligence could show up within just 4 years! To get ready, they’ve launched an AI safety SWAT team, led by brainiacs like Ilya Sutskever. They’re funneling millions into this initiative with a strict 2027 deadline. Why so urgent? Well, they say superintelligence could either catapult humanity into a sci-fi future utopia, or permanently reduce us to drooling toddlers. Not great options there.

Carlos Bravo-Prieto1,2,3, Ryan LaRose4, M. Cerezo1,5, Yigit Subasi6, Lukasz Cincio1, and Patrick J. Coles1

1Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87,545, USA. 2 Barcelona Supercomputing Center, Barcelona, Spain. 3 Institut de Ciències del Cosmos, Universitat de Barcelona, Barcelona, Spain. 4 Department of Computational Mathematics, Science, and Engineering & Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48,823, USA. 5 Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, USA 6 Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87,545, USA

Get full text pdfRead on arXiv Vanity.

Open-source supercomputer algorithm predicts patterning and dynamics of living materials and enables studying their behavior in space and time.

Biological materials are made of individual components, including tiny motors that convert fuel into motion. This creates patterns of movement, and the material shapes itself with coherent flows by constant consumption of energy. Such continuously driven materials are called “active matter.” The mechanics of cells and tissues can be described by active matter theory, a scientific framework to understand shape, flows, and form of living materials. The active matter theory consists of many challenging mathematical equations.

Scientists from the Max Planck Institute of Molecular Cell.

How are we so smart? We seem to be able to make process data with ease, doing tasks in seconds that take supercomputers much longer. Well, one thought is that we fundamentally take advantage of quantum mechanics to perform calculations similar to a quantum computer. This would give us a biologically produced quantum speed up in our brains. Until recently this was just a thought, there is no evidence that this is true. Well, now scientists believe that they may have found evidence of quantum interaction in our brains. Even more importantly, they showed that these quantum interactions are related to our consciousness. In this video, I discuss these latest results.

— References —
[1] https://iopscience.iop.org/article/10.1088/2399-6528/ac94be.
[2] https://phys.org/news/2022-10-brains-quantum.html.
[3] https://scitechdaily.com/shocking-experiment-indicates-our-b…mputation/

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An open-source advanced supercomputer algorithm predicts the patterning and dynamics of living materials, allowing for the exploration of their behaviors across space and time.

Biological materials consist of individual components, including tiny motors that transform fuel into motion. This process creates patterns of movement, leading the material to shape itself through coherent flows driven by constant energy consumption. These perpetually driven materials are called “active matter.”

The mechanics of cells and tissues can be described by active matter theory, a scientific framework to understand the shape, flows, and form of living materials. The active matter theory consists of many challenging mathematical equations.