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A key algorithm that quietly empowers and simplifies our electronics is the Fourier transform, which turns the graph of a signal varying in time into a graph that describes it in terms of its frequencies.

Packaging signals that represent sounds or images in terms of their frequencies allows us to analyze and adjust sound and image files, Richard Stern, professor of electrical and computer engineering at Carnegie Mellon University, tells Popular Mechanics. This mathematical operation also makes it possible for us to store data efficiently.

The invention of color TV is a great example of this, Stern explains. In the 1950s, television was just black and white. Engineers at RCA developed color television, and used Fourier transforms to simplify the data transmission so that the industry could introduce color without tripling the demands on the channels by adding data for red, green, and blue light. Viewers with black-and-white TVs could continue to see the same images as they saw before, while viewers with color TVs could now see the images in color.

Summary: Researchers explain how deep neural networks are able to learn complex physics.

Source: Rice University.

One of the oldest tools in computational physics — a 200-year-old mathematical technique known as Fourier analysis — can reveal crucial information about how a form of artificial intelligence called a deep neural network learns to perform tasks involving complex physics like climate and turbulence modeling, according to a new study.

Microsoft announced new AI-powered classroom tools today. The company sees its new “Learning Accelerators” as helping students sharpen their speaking and math skills — while making teachers’ jobs a little easier — as children prepare for an even more technologically enhanced world.

Speaker Progress is a new AI classroom tool for teachers. Microsoft says it saves them time by “streamlining the process of creating, reviewing, and analyzing speaking and presentation assignments for students, groups, and classrooms.” It can provide tidy summaries of presentation-based skills while highlighting areas to improve. Additionally, it lets teachers review student recordings, identify their needs and track progress.

It will be a companion for Speaker Coach, an existing feature Microsoft launched in 2021 that provides one-on-one speaking guidance and feedback. For example, it uses AI to give real-time pointers on pacing, pitch and filler words. “Speaker Coach is one of those tools that kind of was a lightbulb tool for a lot of students that I’ve worked with,” said an unnamed teacher in a Microsoft launch video. “Being able to practice and get real-time feedback is where Speaker Coach really comes in and helps our students, and it even helps us as adults.”

Mathematical pursuits and religious pursuits are alike in many ways and evoke similar feelings and responses in their devotees. However, this observation is not a universal claim about the faith convictions of mathematical thinkers. Throughout mathematical history, we find plenty of adherents of various faith traditions — Ramanujan, Agnesi, Euler, al-Khwārizmī, or even the Pythagoreans come to mind. However, many mathematicians are atheist or agnostic. A 1998 survey of National Academy members shows that mathematicians in that organization are less religious than the general public (though they are slightly more religious than other scientists). Even so, those who pursue mathematical experiences and those who pursue religious experiences share a lot in common.

Such commonality is in part due to the explanatory power of both mathematics and religion. Mathematics offers insights about physical phenomena. Religion offers insights about human nature. So it is natural to seek them out for wisdom in their respective domains. Their truths are not always directly apparent, sometimes taking years of study. And their interpretations or applications sometimes need to be challenged.

Space “cubically” with shapes that act like spheres? A proof at the intersection of geometry and theoretical computer science says yes.

A new design for an optical fiber borrows concepts from topology to protect light from imperfections in the fiber’s light-guiding materials or from distortions in its cross section.

Using concepts from the mathematical field of topology, researchers at the University of Bath, UK, have designed an optical fiber that can robustly propagate light, even if there are variations in the properties of its light-guiding materials or in its overall geometry [1]. The team thinks that this newfound topological protection could enable advances in optical communication and photonic quantum computing.

The concept of topology is often explained using a joke about a donut and a coffee cup. A coffee cup made of rubber can be continuously twisted and stretched—no cuts need to be made—so that it takes on the shape of a donut. Even though the object’s outline changes under this transformation, its essence remains the same—it contains one hole. Thus, the quip goes, a topologist cannot tell the difference between the two things.

The michael shermer show # 294

What is time? Does the past still exist? How did the universe begin and how will it end? Do particles think? Was the universe made for us? Why doesn’t anyone ever get younger? Has physics ruled out free will? Will we ever have a theory of everything? According to Sabine Hossenfelder, it is not a coincidence that quantum entanglement and vacuum energy have become the go-to explanations of alternative healers, or that people believe their deceased grandmother is still alive because of quantum mechanics. Science and religion have the same roots, and they still tackle some of the same questions: Where do we come from? Where do we go to? How much can we know? The area of science that is closest to answering these questions is physics. Over the last century, physicists have learned a lot about which spiritual ideas are still compatible with the laws of nature. Not always, though, have they stayed on the scientific side of the debate.

Continue reading “Free Will and Determinism from a Physicist’s Perspective (Sabine Hossenfelder)” »

Working with hundreds of thousands of high-resolution images, researchers from the Allen Institute for Cell Science, a division of the Allen Institute, put numbers on the internal organization of human cells — a biological concept that has proven incredibly difficult to quantify until now.

The scientists also documented the diverse cell shapes of genetically identical cells grown under similar conditions in their work. Their findings were recently published in the journal Nature.

“The way cells are organized tells us something about their behavior and identity,” said Susanne Rafelski, Ph.D., Deputy Director of the Allen Institute for Cell Science, who led the study along with Senior Scientist Matheus Viana, Ph.D. “What’s been missing from the field, as we all try to understand how cells change in health and disease, is a rigorous way to deal with this kind of organization. We haven’t yet tapped into that information.”

https://youtube.com/watch?v=V8cPdjO3a_U

Find out what the world will be like a million years from now, as well as what kind of technology we’ll have available.
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Timestamps:
0:00 No Physical Bodies.
1:51 Wormhole Creation.
2:44 Travel At Speed Of Light.
3:21 Type 3 Civilization.
4:52 Gravitational Waves.
5:46 Computers the Size of Planets.
6:56 Computronium.

Continue reading “Future World: A Million Years Later — Artificial Intelligence Tech That Will Change The Universe” »