Tech

ProBeat: AI and quantum computing continue to collide

Depending on who you ask, quantum computing is here, not here, and both. A couple things this week reminded me that it doesn’t really matter whether you believe quantum-mechanical phenomena is going to change everything. The mere research into the field is already impacting technology across the board.

Binary digits (bits) are the basic units of information in classical computing, while quantum bits (qubits) make up quantum computing. Bits are always in a state of 0 or 1, while qubits can be in a state of 0, 1, or a superposition of the two. Quantum computing leverages qubits to perform computations that would be much more difficult for a classical computer. But today’s physical quantum computers are very noisy and there are still no commercially useful algorithms published for them.

AI and quantum information science

In short, a true quantum computer is still years, if not decades, away. When has that ever stopped researchers?

Last month, Mobileye cofounder Amnon Shashua and a team from Hebrew University in Israel published a paper in Physical Review Letters titled “Quantum Entanglement in Deep Learning Architectures.” (Intel acquired the computer vision firm Mobileye for $15.3 billion in March 2017.)

The paper argues that the latest advancements in deep neural networks could help physicists better understand the quantum behavior of nature. This week, Shashua discussed his computer science research group’s findings at the Science of Deep Learning conference in Washington, DC. He declared that they had mathematically proven that AI can help us understand quantum physics phenomena. It’s a question of when, not if.

That’s the argument for AI helping quantum physics. Now let’s go the other way.

Also this week, IBM Research, MIT, and Oxford scientists published a paper in Nature titled “Supervised learning with quantum enhanced feature spaces.” The paper describes that as quantum computers become more powerful, they will be able to perform feature mapping on highly complex data structures that classical computers cannot.

Feature mapping is a component of machine learning that disassembles data into non-redundant “features.” The authors argue they can use quantum computers to create new classifiers that generate more sophisticated data maps. Researchers would then be able to develop more effective AI that can, for example, identify patterns in data that are invisible to classical computers.

IBM did more than just publish a paper, though. The company offered the feature-mapping algorithms to IBM Q Experience users and IBM Q Network organizations through Qiskit Aqua, its quantum information science kit. The company even provided an online demo.

Neither of these papers necessarily means that AI will solve our quantum problems or that machine learning will benefit from quantum advancements. The point at which quantum computers surpass classical computers is still out of reach.

What did become increasingly clear this week, however, is that the two fields are on a collision course.

ProBeat is a column in which Emil rants about whatever crosses him that week.

Content sourced fromTNW

*This section only applies to third party rss feed users*
Kashmir Broadcasting Corporation allows the use of RSS Feeds, but with our content usage we expect that credit is given, but in the event that it is not. This content policy annotation will act as a credit towards KBC (Kashmir Broadcasting Corporation) Please visit kbcchannel.tv for more news and articles — we can not justify what is written on a third party site, as the content can be altered to their specification, if something is not authentic as it should be please visit kbcchannel.tv and look for the original content. if it is no longer there then it can no longer be associated with Kashmir Broadcasting Corporation and if the content on a third party site has been altered to the point of offence or deemed inappropriate please report it to KBC via email: report@kbcchannel.tv or fill the submission form on kbc’s website: https://www.kbcchannel.tv/report-form/ with the details of the site and article heading — Thank You

Website — https://www.kbcchannel.tv/
FaceBook — https://www.facebook.com/kbcchanneltv
Twitter — https://twitter.com/kbcchanneltv
YouTube — https://www.youtube.com/channel/UCV6TFLe3dGbavSYilnC2paQ
Instagram — https://www.instagram.com/kbcchanneltv/

Tags
Show More

Related Articles

Leave a Reply

Your email address will not be published. Required fields are marked *

Back to top button
Close

Adblock Detected

Please consider supporting us by disabling your ad blocker
%d bloggers like this: