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China conducted a secret weapon test that has caught the US intelligence community off guard. Back in August, China lit up the sky when it tested a nuclear-capable hypersonic missile, which travels faster than the speed of sound. The global shipping supply crisis might affect Christmas, thanks in part to China’s power shortage. And a man in Jiangsu Province takes drastic measures after his daughter fails to solve a math problem correctly. Watch this episode of China Uncensored for that and more of this week’s China news headlines.

Jack ma’s dirty secret | power struggle rips ant financial • jack ma’s dirty secret | power strugg…

China’s POWER SHORTAGE could cause economic collapse • china’s POWER SHORTAGE could cause ec…

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Michael Levin is a Distinguished Professor in the Biology Department at Tufts University, where he holds the Vannevar Bush endowed Chair, and he is also associate faculty at the Wyss Institute at Harvard University. Michael and the Levin Lab work at the intersection of biology, artificial life, bioengineering, synthetic morphology, and cognitive science. Michael also appeared on the show in episode #151, which was all about synthetic life and collective intelligence. In this episode, Michael and Robinson discuss the nature of cognition, working with Daniel Dennett, how cognition can be realized by different structures and materials, how to define robots, a new class of robot called the Anthrobot, and whether or not we have moral obligations to biological robots.

The Levin Lab: https://drmichaellevin.org/

OUTLINE
00:00 Introduction.
02:14 What is Cognition?
08:01 On Working with Daniel Dennett.
13:17 Gatekeeping in Cognitive Science.
25:15 The Multi-Realizability of Cognition.
31:30 What are Anthrobots?
39:33 What Are Robots, Really?
59:53 Do We Have Moral Obligations to Biological Robots?

Robinson’s Website: ⁠http://robinsonerhardt.com

Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.

The worlds of quantum mechanics and neural networks have collided in a new system that’s setting benchmarks for solving previously intractable optimization problems. A multi-university team led by Shantanu Chakrabartty at Washington University in St. Louis has introduced NeuroSA, a neuromorphic architecture that leverages quantum tunneling mechanisms to reliably discover optimal solutions to complex mathematical puzzles.

Published March 31 in Nature Communications, NeuroSA represents a significant leap forward in optimization technology with immediate applications ranging from logistics to drug development. While typical neural systems often get trapped in suboptimal solutions, NeuroSA offers something remarkable: a mathematical guarantee of finding the absolute best answer if given sufficient time.

“We’re looking for ways to solve problems better than computers modeled on human learning have done before,” said Chakrabartty, the Clifford W. Murphy Professor and vice dean for research at WashU. “NeuroSA is designed to solve the ‘discovery’ problem, the hardest problem in machine learning, where the goal is to discover new and unknown solutions.”

Scientists have achieved a major leap in quantum technology by deriving an exact mathematical expression crucial for refining noisy quantum entanglement into the pure states needed for advanced quantum computing and communication. Their work revisits and corrects flawed theories from two decades

For decades, neuroscientists have developed mathematical frameworks to explain how brain activity drives behavior in predictable, repetitive scenarios, such as while playing a game. These algorithms have not only described brain cell activity with remarkable precision but also helped develop artificial intelligence with superhuman achievements in specific tasks, such as playing Atari or Go.

Yet these frameworks fall short of capturing the essence of human and animal behavior: our extraordinary ability to generalize, infer and adapt. Our study, published in Nature late last year, provides insights into how in mice enable this more complex, intelligent behavior.

Unlike machines, humans and animals can flexibly navigate new challenges. Every day, we solve new problems by generalizing from our knowledge or drawing from our experiences. We cook new recipes, meet new people, take a new path—and we can imagine the aftermath of entirely novel choices.

A UNSW Sydney mathematician has discovered a new method to tackle algebra’s oldest challenge—solving higher polynomial equations.

Polynomials are equations involving a variable raised to powers, such as the degree two polynomial: 1 + 4x – 3x2 = 0.

The equations are fundamental to math as well as science, where they have broad applications, like helping describe the movement of planets or writing computer programs.

The quantum black hole with (almost) no equations by Professor Gerard ‘t Hooft.

How to reconcile Einstein’s theory of General Relativity with Quantum Mechanics is a notorious problem. Special relativity, on the other hand, was united completely with quantum mechanics when the Standard Model, including Higgs mechanism, was formulated as a relativistic quantum field theory.

Since Stephen Hawking shed new light on quantum mechanical effects in black holes, it was hoped that black holes may be used to obtain a more complete picture of Nature’s laws in that domain, but he arrived at claims that are difficult to use in this respect. Was he right? What happens with information sent into a black hole?

The discussion is not over; in this lecture it is shown that a mild conical singularity at the black hole horizon may be inevitable, while it doubles the temperature of quantum radiation emitted by a black hole, we illustrate the situation with only few equations.

About the Higgs Lecture.

The Faculty of Natural, Mathematical & Engineering Sciences is delighted to present the Annual Higgs Lecture. The inaugural Annual Higgs Lecture was delivered in December 2012 by its name bearer, Professor Peter Higgs, who returned to King’s after graduating in 1950 with a first-class honours degree in Physics, and who famously predicted the Higgs Boson particle.