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Category: information science

Scientists at Imperial College London are attempting to use powerful lasers turn light into matter, potentially proving the 84-year-old theory known as the Breit-Wheeler process. According to this theory, it is technically possible to turn light into matter by smashing two photons to create a positron and an electron. While previous efforts to achieve this feat have required added high-energy particles, the Imperial scientists believe they have discovered a method that does not need additional energy to function. “This would be a pure demonstration of Einstein’s famous equation that relates energy and mass: E=mc2, which tells us how much energy is produced when matter is turned to energy,” explained Imperial Professor Steven Rose. “What we are doing is the same but backwards: turning photon energy into mass, i.e. m=E/c2.”

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You may have heard of Numerai — the unorthodox hedge fund that crowdsources predictive stock market models from data scientists around the world. It is now seeking more brain power and announced today that it is giving away $1 million worth of cryptocurrency to Kaggle users who sign up. The San Francisco-based hedge fund incentivizes its community members by giving them digital tokens they can stake during tournaments to express confidence in their predictions. The best trading algorithms are then selected based on how they perform on the live market, and their creators are rewarded with more tokens.

Looking at most Wall Street hedge funds’ models, it’s fair to say open, collaborative efforts aren’t at their core. Movies like Wall Street, which portrays a greedy Gordon Gekko, and The Wolf of Wall Street, which highlights the derailing decadence of power and money, paint a rather unflattering picture of egocentric traders and financiers. Numerai founder and CEO Richard Craib is looking to change that.

The 30-year-old South African wants to create a more open and decentralized ecosystem for hedge funds. Rather than restricting access to trading data, Craib encrypts it before sharing it with his global network of data scientists, which effectively prevents them stealing and replicating the trades on their own. They can, however, use the shared information to build predictive models for the hedge fund.

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Hey, remember that dog-like robot, SpotMini, that Boston Dynamics showed off last week, the one that opened a door for its robot friend? Well, the company just dropped a new video starring the canine contraption. In this week’s episode, a human with a hockey stick does everything in his power to stop the robot from opening the door, including tugging on the machine, which struggles in an … unsettling manner. But the ambush doesn’t work. The dogbot wins and gets through the door anyway.

The most subtle detail here is also the most impressive: The robot is doing almost all of this autonomously, at least according to the video’s description. Boston Dynamics is a notoriously tight-lipped company, so just the few sentences it provided with this clip is a relative gold mine. That information describes how a human handler drove the bot up to the door, then commanded it to proceed. The rest you can see for yourself. As SpotMini grips the handle and the human tries to shut the door, it braces itself and tugs harder—all on its own. As the human grabs a tether on its back and pulls it back violently, the robot stammers and wobbles and breaks free—still, of its own algorithmic volition.

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We all know that physics and maths can be pretty weird, but these three books tackle their mind-bending subjects in markedly contrasting ways. Clifford V. Johnson’s The Dialogues is a graphic novel, seeking to visualise cosmic ideas in comic-book style. Darling and Banerjee’s Weird Maths is a miscellany of fun oddities, ranging from chess-playing computers to prime-counting insects. Philip Ball’s Beyond Weird argues that we’ve got quantum mechanics all wrong: it’s not so weird actually, but quite sensible. All three books do a fine job for their respective audiences. Just make sure you know which target group you’re in.

The Dialogues is a sequence of illustrated conversations, often between pairs of youthful and attractive characters, scrupulously diverse in race and gender, who happen to meet in a café, gallery or train carriage, and find themselves talking about physics. Perhaps ‘The Lectures’ would be a better title, since one interlocutor is the expert, while the other is an interested lay person whose role is to feed questions at appropriate intervals.

The author shows himself to be a highly talented graphic artist as well as being a distinguished theoretician, and while the ping-pong chats may be somewhat lacking in narrative drive, they do provide a platform for some admirably lucid explanations of topics such as Maxwell’s equations or Einstein’s cosmological constant. Not the kind of comic book you roll up in your pocket, but a weighty hardback that would grace any coffee table.

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Like every other major tech company, Google has designs on being the first to achieve quantum supremacy — the point where a quantum computer could run particular algorithms faster than a classical computer. Today it’s announced that it believes its latest research, Bristlecone, is going to be the processor to help it achieve that. According to the Google Quantum AI Lab, it could provide “a compelling proof-of-principle for building larger scale quantum computers.”

One of the biggest obstacles to quantum supremacy is error rates and subsequent scalability. Qubits (the quantum version of traditional bits) are very unstable and can be adversely affected by noise, and most of these systems can only hold a state for less than 100 microseconds. Google believes that quantum supremacy can be “comfortably demonstrated” with 49 qubits and a two-qubit error below 0.5 percent. Previous quantum systems by Google have given two-qubit errors of 0.6 percent, which in theory sounds like a miniscule difference, but in the world of quantum computing remains significant.

However, each Bristlecone chip features 72 qubits, which may help mitigate some of this error, but as Google says, quantum computing isn’t just about qubits. “Operating a device such as Bristlecone at low system error requires harmony between a full stack of technology ranging from software and control electronics to the processor itself,” the team writes in a blog post. “Getting this right requires careful systems engineering over several iterations.”

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An international group of researchers has made a decisive step towards creating the technology to achieve simulations of brain-scale networks on future supercomputers of the exascale class. The breakthrough, published in Frontiers in Neuroinformatics, allows larger parts of the human brain to be represented, using the same amount of computer memory. Simultaneously, the new algorithm significantly speeds up brain simulations on existing supercomputers.

The human brain is an organ of incredible complexity, composed of 100 billion interconnected nerve cells. However, even with the help of the most powerful supercomputers available, it is currently impossible to simulate the exchange of neuronal signals in networks of this size.

“Since 2014, our software can simulate about one percent of the in the human brain with all their connections,” says Markus Diesmann, Director at the Jülich Institute of Neuroscience and Medicine (INM-6). In order to achieve this impressive feat, the software requires the entire main memory of petascale supercomputers, such as the K computer in Kobe and JUQUEEN in Jülich.

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Every major tech company is looking at quantum computers as the next big breakthrough in computing. Teams at Google, Microsoft, Intel, IBM and various startups and academic labs are racing to become the first to achieve quantum supremacy — that is, the point where a quantum computer can run certain algorithms faster than a classical computer ever could. Today, Google said that it believes that Bristlecone, its latest quantum processor, will put it on a path to reach quantum supremacy in the future.

The purpose of Bristlecone, Google says, it to provide its researchers with a testbed “for research into system error rates and scalability of our qubit technology, as well as applications in quantum simulation, optimization, and machine learning.”

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