Lifeboat Foundation

Analysing pendulum videos, the artificial intelligence tool identified variables not present in current mathematics.

An artificial intelligence tool has examined physical systems and not surprisingly, found new ways of describing what it found.

How do we make sense of the universe? There’s no manual. There’s no prescription.

Continue reading “Artificial intelligence discovers new physics variables!” »

* At Long Last, Mathematical Proof That Black Holes Are Stable * Who Gets to Work in the Digital Economy? * Mice produce rat sperm with technique that could help conservation.

* Quantum computer can simulate infinitely many chaotic particles * Radar / AI & ML: Scaling False Peaks * Cyber security for the human world | George Loukas | TEDx.

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Multivariable calculus, differential equations, linear algebra—topics that many MIT students can ace without breaking a sweat—have consistently stumped machine learning models. The best models have only been able to answer elementary or high school-level math questions, and they don’t always find the correct solutions.

Now, a multidisciplinary team of researchers from MIT and elsewhere, led by Iddo Drori, a lecturer in the MIT Department of Electrical Engineering and Computer Science (EECS), has used a neural network model to solve university-level math problems in a few seconds at a human level.

The model also automatically explains solutions and rapidly generates new problems in university math subjects. When the researchers showed these machine-generated questions to university students, the students were unable to tell whether the questions were generated by an algorithm or a human.

The received view in physics is that the direction of time is provided by the second law of thermodynamics, according to which the passage of time is measured by ever-increasing disorder in the universe. This view, Julian Barbour argues, is wrong. If we reject Newton’s faulty assumptions about the existence of absolute space and time, Newtonian dynamics can be shown to provide a very different arrow of time. Its direction, according to this theory, is given by the increase in the complexity and order of a system of particles, exactly the opposite of what the received view about time suggests.

Two of the most established beliefs of contemporary cosmology are that the universe is expanding and that the direction of the arrow of time in the universe is defined by ever-increasing disorder (entropy), as described by the second law of thermodynamics. But both of these beliefs rest on shaky ground. In saying that the universe is expanding, physicists implicitly assume its size is measured by a rod that exists outside the universe, providing an absolute scale. It’s the last vestige of Newton’s absolute space and should have no place in modern cosmology. And in claiming that entropy is what gives time its arrow, physicists uncritically apply the laws of thermodynamics, originally discovered through the study of steam engines, to the universe as a whole. That too needs to be questioned.

Continue reading “Time is the increase of order, not disorder” »

This research paper presents the design of a wireless power transfer (WPT) circuit integrated with magnetic resonance coupling (MRC) and harvested radio frequency (RF) energy to wirelessly charge the battery of a mobile device. A capacitor (100 µF, 16 V) in the RF energy harvesting circuit stored the converted power, and the accumulated voltage stored in the capacitor was 9.46 V. The foundation of the proposed WPT prototype circuit included two coils (28 AWG)—a transmitter coil, and a receiver coil. The transmitter coil was energized by the alternating current (AC), which produced a magnetic field, which in turn induced a current in the receiver coil. The harvested RF energy (9.46 V) was converted into AC, which energized the transmitter coil and generated a magnetic field. The electronics in the receiver coil then converted the AC into direct current (DC), which became usable power to charge the battery of a mobile device. The experimental setup based on mathematical modeling and simulation displayed successful charging capabilities of MRC, with the alternate power source being the harvested RF energy. Mathematical formulae were applied to calculate the amount of power generated from the prototype circuit. LTSpice simulation software was applied to demonstrate the behavior of the different components in the circuit layout for effective WPT transfer.

For now, the acrylic table is under construction and open only to the stuffed mouse, originally a cat toy, used to help set up the cameras. The toy squeaks when Kennedy presses it. “Usually, you do a surgery to remove the squeaker” before using them to set up experiments, says Kennedy, assistant professor of neuroscience at Northwestern University in Chicago, Illinois.

The playful squeak is a startling sound in a lab that is otherwise defined by the quiet of computational modeling. Among her projects, Kennedy is expanding her work with an artificial-intelligence-driven tool called the Mouse Action Recognition System (MARS) that can automatically classify mouse social behaviors. She also uses her modeling work to study how different brain areas and cell types interact with one another, and to connect neural activity with behaviors to learn how the brain integrates sensory information. In her office on the fifth floor of Northwestern’s Ward Building in downtown Chicago, most of this work happens on computers with data, code and graphs. Quiet also prevails in a room down the hall, where Kennedy’s small group of postdoctoral researchers and technicians sit at workstations in a lab that she launched less than a year and a half ago.

Kennedy’s ability to talk about abstract concepts, with a little stuffed animal as a prop, sets her apart, her colleagues say. She is a rare theoretical neuroscientist who can translate her mathematical work into real-world experiments. “That is her gift,” says Larry Abbott, a theoretical neuroscientist at Columbia University who was Kennedy’s graduate school advisor. “She’s good at the technical stuff, but if you can’t make that reach across to the data and the experiments, a person is not going to be that effective. She’s really just great at that — finding the right mathematics to apply to the particular problem that she’s looking at.”

Check out the math & physics courses that I mentioned (many of which are free!) and support this channel by going to https://brilliant.org/Sabine/ where you can create your Brilliant account. The first 200 will get 20% off the annual premium subscription.

This is a video I have promised you almost two years ago: How does superdeterminism make sense of quantum mechanics? It’s taken me a long time to finish this because I have tried to understand why people dislike the idea that everything is predetermined so much. I hope that in this video I have addressed the biggest misconceptions. I genuinely think that discarding superdeterminism unthinkingly is the major reason that research in the foundations of physics is stuck.

Continue reading “Does Superdeterminism save Quantum Mechanics? Or does it kill free will and destroy science?” »

“The final theory of nature must be octonionic,” observed Michael Atiyah, a British mathematician who united mathematics and physics during the 1960s in a way not seen since the days of Isaac Newton.

“Octonions are to physics what the Sirens were to Ulysses,” Pierre Ramond, a particle physicist and string theorist at the University of Florida, said to Natalie Walchover for Quanta.

Many physicists and mathematicians over the decades suspected that the peculiar panoply of forces and particles that comprise reality spring logically from the properties of eight-dimensional numbers called “octonions.” Proof surfaced in 1,898, writes Walchover in Quanta, that the reals, complex numbers, quaternions and octonions are the only kinds of numbers that can be added, subtracted, multiplied and divided.

“It is very exciting to see this unusual phase of matter realized in an actual experiment, especially because the mathematical description is based on a theoretical ‘extra’ time dimension,” Philipp Dumitrescu, study co-author and research fellow at the Flatiron Institute’s Center for Computational Quantum Physics, told the magazine.

In order to successfully create the topological phase, and thus the “extra” dimension, the scientists targeted a quantum computer’s quantum bits — or qubits — with a quasi-periodic laser pulse based on the Fibonacci sequence. Think quasicrystal.

“The Fibonacci sequence is a non-repeating but also not totally random sequence,” study co-author Andrew Potter, a quantum physicist at the University of British Columbia, told Vice. “Which effectively lets us realize two independent time-dimensions in the system.”