Lifeboat Foundation

In 2010, a Canadian company called D-Wave announced that it had begun production of what it called the world’s first commercial quantum computer, which was based on theoretical work done at MIT. Quantum computers promise to solve some problems significantly faster than classical computers—and in at least one case, exponentially faster. In 2013, a consortium including Google and NASA bought one of D-Wave’s machines.

Over the years, critics have argued that it’s unclear whether the D-Wave machine is actually harnessing quantum phenomena to perform its calculations, and if it is, whether it offers any advantages over classical computers. But this week, a group of Google researchers released a paper claiming that in their experiments, a quantum algorithm running on their D-Wave machine was 100 million times faster than a comparable classical algorithm.

Scott Aaronson, an associate professor of electrical engineering and computer science at MIT, has been following the D-Wave story for years. MIT News asked him to help make sense of the Google researchers’ new paper.

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Why send a message back in time, but lock it so that no one can ever read the contents? Because it may be the key to solving currently intractable problems. That’s the claim of an international collaboration who have just published a paper in npj Quantum Information.

It turns out that an unopened message can be exceedingly useful. This is true if the experimenter entangles the message with some other system in the laboratory before sending it. Entanglement, a strange effect only possible in the realm of quantum physics, creates correlations between the time-travelling message and the laboratory system. These correlations can fuel a quantum computation.

Around ten years ago researcher Dave Bacon, now at Google, showed that a time-travelling quantum computer could quickly solve a group of problems, known as NP-complete, which mathematicians have lumped together as being hard.

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We have very good news for all fans of High RAM Powered Phones. Samsung started mass production of their new LPDDR4 DRAM, allowing for next Generation 6GB RAM phones in India. Samsung essentially produced the industry’s first 12Gigabit LPDDR4 RAM with Samsung’s 20nm manufacturing process.

The real advantage of those chips is that they have a 50% higher density PCB layout with increased capacity as well as reduced power usage. Both of these are very important factors in small devices like a phone/tablet where every mm2 and mW matters. Please note that this is Gigabits, not Gigabytes. 12 Gigabits is around 1.5GB of RAM. Most high end smartphones have four memory dies, that means 1.5GB x 4 = 6GB RAM phones for us.

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AMD has confirmed we will see high-end desktop FX processors of the Zen variety later on next year.

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Why send a message back in time, but lock it so that no one can ever read the contents? Because it may be the key to solving currently intractable problems. That’s the claim of an international collaboration who have just published a paper in npj Quantum Information.

It turns out that an unopened message can be exceedingly useful. This is true if the experimenter entangles the message with some other system in the laboratory before sending it. Entanglement, a strange effect only possible in the realm of quantum physics, creates correlations between the time-travelling message and the laboratory system. These correlations can fuel a quantum computation.

Around ten years ago researcher Dave Bacon, now at Google, showed that a time-travelling quantum computer could quickly solve a group of problems, known as NP-complete, which mathematicians have lumped together as being hard.

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But does it write book reports?

Get ready for a new generation of computers that can read millions of texts and understand the relationships between characters.

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For decades, engineers have designed computer systems with processors and memory chips laid out like single-story structures in a suburb. Wires connect these chips like streets, carrying digital traffic between the processors that compute data and the memory chips that store it.

But suburban-style layouts create long commutes and regular traffic jams in electronic circuits, wasting time and energy.

That is why researchers from three other universities are working with Stanford engineers, including Associate Professor Subhasish Mitra and Professor H.-S. Philip Wong, to create a revolutionary new high-rise architecture for computing.

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Machine learning now allows us to project a particular voice onto someone else’s face, which makes for some pretty hilarious pairings. http://voc.tv/1P6L9zh

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New advance could also lead to chips that can smell, taste.

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