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Category: information science – Page 283

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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Summary: Treatability of cancer was raised to over 80% by a new intelligent system that sifts through massive genetic datasets to pinpoint targets for cancer treatment, say these scientists. [This article first appeared on LongevityFacts. Author: Brady Hartman. ]

Scientists in Singapore have discovered a significantly improved way to treat cancer by listening to many different computer programs rather than just one.

Their new computer program reaches a consensus on how to treat a specific tumor, and it is significantly more accurate than existing predictive methods. The system isolates the Achilles heel of each individual tumor, helping doctors to choose the best treatment.

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