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The Future of Cybersecurity Is the Quantum Random Number Generator

Truly random numbers will provide an unbreakable tool set for cryptography

10 min read
Illustration by Greg Mably
Illustration: Greg Mably

In 1882, a banker in Sacramento, Calif.,named Frank Miller developed an absolutely unbreakable encryption method. Nearly 140 years later, cryptographers have yet to come up with something better.

Miller had learned about cryptography while serving as a military investigator during the U.S. Civil War. Sometime later, he grew interested in telegraphy and especially the challenge of preventing fraud by wire—a problem that was frustrating many bankers at the time. As a contemporary, Robert Slater, the secretary of the French Atlantic Telegraph Co., wrote in his 1870 book Telegraphic Code, to Ensure Secresy [sic] in the Transmission of Telegrams, “Nothing then is easier for a dishonest cable operator than the commission of a fraud of gigantic extent.”

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Dialing Down a Quantum Compute Glitch by 100,000x

A low-key solution to qubits’ cosmic ray problem

3 min read
Conceptual computer artwork of electronic circuitry contained within spheres against beams of light, representing how data may be controlled and stored in a quantum computer.
Mehau Kulyk/Science Source

The kind of quantum computers that IBM, Google and Amazon are building suffer catastrophic errors roughly once every 10 seconds due to cosmic rays from outer space. Now a new study reveals a way to reduce this error rate by nearly a half-million-fold to less than once per month.

Quantum computers theoretically can find answers to problems no regular computer might ever hope to solve. Their key ingredients, known as quantum bits, or qubits, are linked together by a quantum effect known as entanglement.

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Deep Learning Gets a Boost From New Reconfigurable Processor

The ReAAP processor allows AI to be faster, more efficient

2 min read
different colored beams of light shooting up
iStock

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Deep learning is a critical computing approach that is pushing the boundaries of technology – crunching immense amounts of data and uncovering subtle patterns that humans could never discern on their own. But for optimal performance, deep learning algorithms need to be supported with the right software compiler and hardware combinations. In particular, reconfigurable processors, which allow for flexible use of hardware resources for computing as needed, are key.

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Accelerate the Future of Innovation

Download these free whitepapers to learn more about emerging technologies like 5G, 6G, and quantum computing

1 min read
Keysight
Keysight

Looking for help with technical challenges related to emerging technologies like 5G, 6G, and quantum computing?

Download these three whitepapers to help inspire and accelerate your future innovations:

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