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The quantum superposition principle has been tested on a scale as never before in a new study by scientists at the University of Vienna in collaboration with the University of Basel. Hot, complex molecules composed of nearly two thousand atoms were brought into a quantum superposition and made to interfere. By confirming this phenomenon – “the heart of quantum mechanics”, in Richard Feynman’s words – on a new mass scale, improved constraints on alternative theories to quantum mechanics have been placed. The work was published in Nature Physics on September 23, 2019.

Quantum to classical?

The superposition principle is a hallmark of quantum theory which emerges from one of the most fundamental equations of quantum mechanics, the Schrödinger equation. It describes particles in the framework of wave functions, which, much like water waves on the surface of a pond, can exhibit interference effects. But in contrast to water waves, which are a collective behavior of many interacting water molecules, quantum waves can also be associated with isolated single particles.

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After three years of quietly toiling away on a robotic food system, Seattle startup Picnic has emerged from stealth mode with a system that assembles custom pizzas with little human intervention.

Picnic — previously known as Otto Robotics and Vivid Robotics — is the latest entrant in a cohort of startups and industry giants trying to find ways to automate restaurant kitchens in the face of slim margins and labor shortages. And its journey here wasn’t easy.

“Food is hard. It’s highly variable,” said Picnic CEO Clayton Wood. “We learned a lot about food science in the process of developing the system.”

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Geneva. Arts at CERN announces two open calls for art residencies – Collide Geneva/Dance and Accelerate Finland – and the arrival of the winners of Collide International, Rosa Menkman, and Collide Pro Helvetia, Christina Hemauer and Roman Keller. The art residency programmes are based on the particle physics laboratory’s cultural strategy, which aims to foster networks between local and international organisations through platforms that engage art and science.

“Arts at CERN plays an important role in augmenting the interest seen in the interaction of the arts and sciences in recent years. By inviting artists and scientists to have a dialogue in the Laboratory, the programme shows how the two fields impact one another. I am proud to announce new opportunities for participation, and to welcome artists-in-residence this autumn,” says Mónica Bello, head of Arts at CERN.

For the sixth Collide Geneva residency, Arts at CERN, the Republic and Canton of Geneva and the City of Geneva have joined forces. The three-month fully funded residency award will be granted to a Geneva-based artist or artist collective working in the field of dance. The winner will have the opportunity to carry out their research at CERN and work together with particle physicists, engineers and IT professionals. Collide Geneva/Dance encourages applications from dance artists inspired by scientific ideas or technological concepts, with innovative approaches in their artistic expression.

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The trawl found 20,500 articles tackling the topic, but shockingly, less than 1 percent of them were scientifically robust enough to be confident in their claims, say the authors. Of those, only 25 tested their deep learning models on unseen data, and only 14 actually compared performance with health professionals on the same test sample.

Nonetheless, when the researchers pooled the data from the 14 most rigorous studies, they found the deep learning systems correctly detected disease in 87 percent of cases, compared to 86 percent for healthcare professionals. They also did well on the equally important metric of excluding patients who don’t have a particular disease, getting it right 93 percent of the time compared to 91 percent for humans.

Ultimately, then, the results of the review are broadly positive for AI, but damning of the hype that has built up around the technology and the research practices of most of those trying to apply it to medical diagnosis.

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For the first time, physicists in the US have confirmed a decades-old theory regarding the breaking of time-reversal symmetry in gauge fields. Marin Soljacic at the Massachusetts Institute of Technology and an international team of researchers have made this first demonstration of the “non-Abelian Aharonov-Bohm effect” in two optics experiments. With improvements, their techniques could find use in optoelectronics and fault-tolerant quantum computers.

First emerging in Maxwell’s famous equations for classical electrodynamics, a gauge theory is a description of the physics of fields. Gauge theories have since become an important part of physicists’ descriptions of the dynamics of elementary particles – notably the theory of quantum electrodynamics.

A salient feature of a gauge theory is that the physics it describes does not change when certain transformations are made to the underlying equations describing the system. An example is the addition of a constant scalar potential or a “curl-free” vector potential to Maxwell’s equations. Mathematically, this does not change the electric and magnetic fields that act on a charged particle such as an electron – and therefore the behaviour of the electron – so Maxwell’s theory is gauge invariant.

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The jobs that are likely to be automated are repetitive and routine. They range from reading X-rays (human radiologists may soon have much more limited roles), to truck driving, to stocking a warehouse. While much has been written about the sorts of jobs that are likely to be eliminated, another perspective that has not been examined in as much detail is to ask not which jobs will be eliminated but rather which aspects of surviving jobs will be replaced by machines.

The future of work looks grim for many people. A recent study estimated that 10% of U.S. jobs would be automated this year, and another estimates that close to half of all U.S. jobs may be automated in the next decade. The jobs that are likely to be automated are repetitive and routine. They range from reading X-rays, to truck driving, to stocking a warehouse. In this context, employers say that they’re seeking candidates who have other sorts of “soft skills,” such as being able to learn adaptively, to make good decisions, and to work well with others. These sought-after abilities, of course, fit perfectly with the sorts of things that people can do well, but are and will continue to be difficult to automate. All of this suggests that our educational systems should concentrate not simply on how people interact with technology (e.g., by teaching students to code), but also how they can do the things that technology will not be doing soon. These are the skills that are hardest to understand and systematize, and the skills that give — and will continue to give —humans an edge over robots.

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