Lifeboat Foundation

Researchers report a new, highly unusual, structured-light family of 3D topological solitons, the photonic hopfions, where the topological textures and topological numbers can be freely and independently tuned.

We can frequently find in our daily lives a localized wave structure that maintains its shape upon propagation—picture a smoke ring flying in the air. Similar stable structures have been studied in various research fields and can be found in magnets, nuclear systems, and particle physics. In contrast to a ring of smoke, they can be made resilient to perturbations. This is known in mathematics and physics as topological protection.

A typical example is the nanoscale hurricane-like texture of a magnetic field in magnetic thin films, behaving as particles—that is, not changing their shape—called skyrmions. Similar doughnut-shaped (or toroidal) patterns in 3D space, visualizing complex spatial distributions of various properties of a wave, are called hopfions. Achieving such structures with light waves is very elusive.

AI robots, with Elon Musk, Boston Dynamics. To learn AI, visit: https://brilliant.org/digitalengine where you’ll also find loads of fun courses on maths, science and computer science.

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Ray Kurzweil on the Law of accelerating returns:

Ray Kurzweil: Acceleration of technology is the implication of what I call the law of accelerating returns. The nature of technological progress is exponential. If I count linearly 30 steps: 1, 2, 3, 4, 5… I get to 30. If I count exponentially: 2, 4, 8, 16… 30 steps later I’m at a billion. It makes a dramatic difference.

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AI is being used to generate everything from images to text to artificial proteins, and now another thing has been added to the list: speech. Last week researchers from Microsoft released a paper on a new AI called VALL-E that can accurately simulate anyone’s voice based on a sample just three seconds long. VALL-E isn’t the first speech simulator to be created, but it’s built in a different way than its predecessors—and could carry a greater risk for potential misuse.

Most existing text-to-speech models use waveforms (graphical representations of sound waves as they move through a medium over time) to create fake voices, tweaking characteristics like tone or pitch to approximate a given voice. VALL-E, though, takes a sample of someone’s voice and breaks it down into components called tokens, then uses those tokens to create new sounds based on the “rules” it already learned about this voice. If a voice is particularly deep, or a speaker pronounces their A’s in a nasal-y way, or they’re more monotone than average, these are all traits the AI would pick up on and be able to replicate.

The model is based on a technology called EnCodec by Meta, which was just released this part October. The tool uses a three-part system to compress audio to 10 times smaller than MP3s with no loss in quality; its creators meant for one of its uses to be improving the quality of voice and music on calls made over low-bandwidth connections.

Chengyi wang*, sanyuan chen*, yu wu*, ziqiang zhang, long zhou, shujie liu, zhuo chen, yanqing liu, huaming wang, jinyu li, lei he, sheng zhao, furu wei.

Microsoft

Abstract. We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called VALL-E) using discrete codes derived from an off-the-shelf neural audio codec model, and regard TTS as a conditional language modeling task rather than continuous signal regression as in previous work. During the pre-training stage, we scale up the TTS training data to 60K hours of English speech which is hundreds of times larger than existing systems. VALL-E emerges in-context learning capabilities and can be used to synthesize high-quality personalized speech with only a 3-second enrolled recording of an unseen speaker as an acoustic prompt. Experiment results show that VALL-E significantly outperforms the state-of-the-art zero-shot TTS system in terms of speech naturalness and speaker similarity. In addition, we find VALL-E could preserve the speaker’s emotion and acoustic environment of the acoustic prompt in synthesis.

Patreon: https://www.patreon.com/seanmcarroll.
Blog post with audio player, show notes, and transcript: https://www.preposterousuniverse.com/podcast/2022/02/07/183-…e-physics/

Modern particle physics is a victim of its own success. We have extremely good theories — so good that it’s hard to know exactly how to move beyond them, since they agree with all the experiments. Yet, there are strong indications from theoretical considerations and cosmological data that we need to do better. But the leading contenders, especially supersymmetry, haven’t yet shown up in our experiments, leading some to wonder whether anthropic selection is a better answer. Michael Dine gives us an expert’s survey of the current situation, with pointers to what might come next.

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Last week, Rice University in Houston announced that one of its assistant professors of bioengineering, Jerzy Szablowski, received a Young Faculty Award from DARPA to research non-genetic drugs that can “temporarily enhance the human body’s resilience to extreme cold exposure.”

Thermogenesis is the use of energy to create heat, and our bodies have two different ways of doing this. One is shivering, which we’re all familiar with. The other, which Szablowski simply calls non-shivering thermogenesis, involves burning off brown adipose tissue (BAT), or brow n fat.

This type of fat exists specifically to warm us up when we get cold; it stores energy and only activates in cold temperatures. Most of our body fat is white fat. It builds up when we ingest more calories than we burn and stores those calories for when we don’t get enough energy from food. An unfortunate majority of American adults have the opposite problem: too much white fat, which increases the risk of conditions like heart disease and Type 2 diabetes.

Molecular detective work is zeroing in on the origins of sexual reproduction. The protein tools for cell mergers seem to have long predated sex — so what were they doing?

Cellular reprogramming builds on the Nobel Prize-winning work of Shinya Yamanaka, who showed that adult cells could be transformed back into stem cells by exposing them to a specific set of genome-regulating proteins known as transcription factors. The Salk team’s innovation was to reduce the exposure times to the so-called Yamanaka factors, which they found could reverse epigenetic changes to the cells without reverting them to stem cells.

While the approach led to clear increases in lifespan in prematurely aging mice, the fact that no one had been able to replicate the result in healthy mice since then raised doubts about the approach. “Different groups have tried this experiment, and the data have not been positive so far,” Alejandro Ocampo, from the University of Lausanne in Switzerland, who carried out the original Salk experiments, told MIT Technology Review.

But now, Rejuvenate Bio claims that when they exposed healthy mice near the end of their lives to a subset of the Yamanaka factors, they lived for another 18 weeks on average, compared to just 9 weeks for those that didn’t undergo cellular reprogramming.