Check your subscription status, update your details and more. The controversial idea that consciousness has a quantum origin is facing a new challenge, after a mathematical analysis appears to show that a long-known law of physics makes it impossible. What physical process makes us conscious, and whether we could observe and analyse it, is one of the great open questions of modern science. In the 1990s, mathematician Roger Penrose and anesthesiologist Stuart Hameroff proposed that classical physics can't explain consciousness alone and so it must arise in the quantum realm. The idea was received with scepticism and remains controversial, but attempts to bring quantumness into explanations of consciousness have persisted since.

The company has drawn governments, a major chipmaker, and the Pentagon into an effort to control fragile photons and build a useful quantum machine. It aims to be the first. PsiQuantum aims to build a quantum computer that can solve some of science's hardest problems. Its chips, cut from wafers like the one shown here, will perform computations using photons, the particles of light. The machine that could change the world will be housed in a room that looks like a data center crossed with an ice cream factory. Inside will be some 100 stainless-steel cabinets, each about six feet tall and connected to a supply of liquid helium that keeps them only a few degrees above absolute zero. Inside those cabinets will be hundreds of chips, and on those, thousands of particles of light flying through a maze of optical switches and beam splitters.

The US government wants to get hold of a quantum computer good enough to contribute to scientific breakthroughs in just two years. It will use it to try to accelerate the research and development of new materials, pharmaceuticals and molecules useful in agriculture and manufacturing. Once a dream of theoretical physicists, quantum computers are now undoubtedly real, but have yet to prove unambiguously useful or to have broad commercial value. Their computational power depends on their size - how many components called qubits they comprise - and how reliable they are. Existing devices are still too small and too error-prone.

Can video games help us better understand quantum mechanics? The world of quantum video games is vast - there are hundreds that are either inspired by quantum mechanics or use quantum computers in their development. A pale yellow square awkwardly lands on a green block shaped like the letter "z". Next to them stands a pillar made of smaller turquoise blocks. We've all seen, you can probably picture it.

Quantum'Jamming' Could Help Unlock the Mysteries of Causality To keep communications secure in a post-quantum world, cryptographers are digging down into the concept of cause and effect. For the past few decades, researchers have understood that quantum computers should eventually be able to crack the widely used codes that secure much of the digital world. To protect against this fate, they've spent years developing new codes that appear to be safe from future safecrackers armed with quantum computers. At the same time, they've also devised ingenious ways to use the rules of quantum mechanics to keep communications secure. But quantum mechanics, just like the "classical" mechanics that preceded it, is just a theory of nature.

Charles Bennett and Gilles Brassard pioneered quantum information theory. Now they've been awarded the highest honor in computer science. Today it's widely acknowledged that the future of computing will involve the quantum realm . Companies like Google, Microsoft, IBM, and a few well-funded startups are frantically building quantum computers and routinely claiming advances that seem to bring this exotic, world-changing technology within reach. In 1979 all of this was unthinkable.

You can never truly empty a box. Suppose you want to empty a box. You remove all its visible contents, pump out any gases, and--applying some science-fiction technology--evacuate any unseeable material such as dark matter. According to quantum mechanics, what's left inside? It sounds like a trick question.

This paper presents a text classification algorithm inspired by the notion of superposition of states in quantum physics.

Researchers at the company are trying to understand their A.I. system's mind--examining its neurons, running it through psychology experiments, and putting it on the therapy couch. It has become increasingly clear that Claude's selfhood, much like our own, is a matter of both neurons and narratives. A large language model is nothing more than a monumental pile of small numbers. It converts words into numbers, runs those numbers through a numerical pinball game, and turns the resulting numbers back into words. Similar piles are part of the furniture of everyday life. Meteorologists use them to predict the weather. Epidemiologists use them to predict the paths of diseases. Among regular people, they do not usually inspire intense feelings. But when these A.I. systems began to predict the path of a sentence--that is, to talk--the reaction was widespread delirium. As a cognitive scientist wrote recently, "For hurricanes or pandemics, this is as rigorous as science gets; for sequences of words, everyone seems to lose their mind." It's hard to blame them. Language is, or rather was, our special thing. We weren't prepared for the arrival of talking machines. Ellie Pavlick, a computer scientist at Brown, has drawn up a taxonomy of our most common responses. There are the "fanboys," who man the hype wires. They believe that large language models are intelligent, maybe even conscious, and prophesy that, before long, they will become superintelligent. The venture capitalist Marc Andreessen has described A.I. as "our alchemy, our Philosopher's Stone--we are literally making sand think." The fanboys' deflationary counterparts are the "curmudgeons," who claim that there's no there, and that only a blockhead would mistake a parlor trick for the soul of the new machine. In the recent book " The AI Con," the linguist Emily Bender and the sociologist Alex Hanna belittle L.L.M.s as "mathy maths," "stochastic parrots," and "a racist pile of linear algebra." But, Pavlick writes, "there is another way to react." It is O.K., she offers, "to not know." What Pavlick means, on the most basic level, is that large language models are black boxes. We don't really understand how they work. We don't know if it makes sense to call them intelligent, or if it will ever make sense to call them conscious. The existence of talking machines--entities that can do many of the things that only we have ever been able to do--throws a lot of other things into question. We refer to our own minds as if they weren't also black boxes.

If your New Year's resolution is to understand quantum computing this year, take a cue from a 9-year-old podcaster talking to some of the biggest minds in the field, says quantum columnist Karmela Padavic-Callaghan Quantum computing seems to pop up in the news pretty often these days. You've probably seen quantum chips gracing your feeds and their odd, steampunk-ish cooling systems in the pages of magazines and newspapers. Politicians and business leaders are peppering their announcements with the word "quantum" more frequently, too. If you're feeling a little confused about it all, it's a good year for a New Year's resolution to finally figure out what quantum computing is all about. This is an ambitious goal, and the timing certainly makes sense.