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An international team of researchers from the National Physical Laboratory (NPL), IBM, the University of Edinburgh and Auburn University have shown that a new device concept — a ‘squishy’ transistor — can overcome the predicted power bottleneck caused by CMOS (complementary metal-oxide-semiconductor) technology reaching its fundamental limits.

Moore’s law predicted that the number of transistors able to fit on a given die area would double every two years. As transistor density doubled, chip size shrank and processing speeds increased. This march of progress led to rapid advances in information technology and a surge in the number of interconnected devices. The challenge with making anything smaller is that there are fundamental physical limits that can’t be ignored and we are now entering the final years of CMOS transistor shrinkage.

Furthermore, this proliferation is driving an increase in data volume, accompanied by rising demands on energy to process, store and communicate it all; as a result, IT infrastructure now draws an estimated 10 % of the world’s electrical power. Previous efforts have focused on remediation by reducing the amount of energy per bit. However, soon we will hit a power barrier that will prevent continued voltage scaling. The development of novel, low-power devices based on different physical principles is therefore crucial to the continued evolution of IT.

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A small, Santa Fe, New Mexico-based company called Knowm claims it will soon begin commercializing a state-of-the-art technique for building computing chips that learn. Other companies, including HP HPQ and IBM IBM, have already invested in developing these so-called brain-based chips, but Knowm says it has just achieved a major technological breakthrough that it should be able to push into production hopefully within a few years.

The basis for Knowm’s work is a piece of hardware called a memristor, which functions (warning: oversimplification coming) by mimicking synapses in the brain. Rather than committing certain information to a software program and traditional computing memory, memristors are able to “learn” by strengthening the electrical charge between two resistors (the “ristor” part of memristor) much like synapses strengthen connections between commonly used neurons in the brain.

Done correctly—and this is the result that HP and IBM are after—memristors can make computer chips much smarter, but also very energy efficient. That could mean data centers that don’t use as much energy as small towns, as well as more viable robotics, driverless cars, and other autonomous devices. Alex Nugent, Knowm’s founder and CEO, says memristors—especially the ones his company is working on—offer “a massive leap in efficiency” over traditional CPUs, GPUs, and other hardware now used to power artificial intelligence workloads.

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Enter our new 3D NAND technology, which uses an innovative process architecture to provide 3X the capacity of planar NAND technologies while providing better performance and reliability.

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Intel today announced plans to invest $50 million over the next ten years as part of a quantum computing push to help solve problems such as “large-scale financial analysis and more effective drug development.”

But despite the ambitions and huge cost of the project, company vice president Mike Mayberry admits that “a fully functioning quantum computer is at least a dozen years away.”

The money will be channeled through QuTech, the quantum research institute of Delft University of Technology, and TNO, with Intel additionally pledging to commit its own “engineering resources” to the collaborative effort.

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Intel has taken the lid off its next-generation Skylake mobile chips. Fat L4 caches are coming to a lot more mobile hardware.

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New article on how tech can help achieve free education while also shrinking the prison system:

Micro drones, robot guards, and tracking chips will turn convicts into tax-paying, law-abiding citizens.

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