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Google launches TensorFlow Quantum


Quantum computers have been quite the rage recently with different tech companies vying for the top spot when it comes to building the most powerful quantum machine. While IBM and Google were in the headlines last year for achieving quantum supremacy, other companies like the Industrial giant Honeywell have been quietly working on its own quantum tech. The company plans to make available its quantum machine to clients via the internet in the next three months. However, Honeywell's approach is a little different than the traditional quantum computers which use superconducting qubits to operate. Honeywell's quantum computer uses a different technology, called ion traps, which hold ions in place with electromagnetic fields.

Running quantum algorithms in the cloud just got a lot faster

MIT Technology Review

Quantum computers could one day perform calculations beyond the reach of even the most powerful classical supercomputer, but for now building and maintaining these machines remains immensely expensive and difficult. So over the past few years, the nascent industry has begun to make some of the relatively few quantum machines in existence available to researchers and businesses via the computing cloud. A startup called Rigetti Computing has just taken the wraps off a new Quantum Cloud Service (QCS) that builds on its existing offering, which includes Forest, a software toolkit for quantum programming in the cloud. There's a $1 million prize for the first person or team using QCS to demonstrate that a quantum machine is capable of showing what the company calls "quantum advantage". Rigetti defines this as showing that a quantum machine can come up with a higher quality, faster, or cheaper solution to an important and valuable problem than a classical one can.

Quantum Computing Needs You to Help Solve Its Core Mystery


Since 2016, IBM has offered online access to a quantum computer. Anyone can log in and execute commands on a 5-qubit or 14-qubit machine located in Yorktown Heights, New York, from the comfort of their own home. This month, I finally tried it--nervously. I did not know what I was doing and worried I might break the hardware. "You won't mess anything up," IBM physicist James Wootton assured me via Skype.

Google has enlisted NASA to help it prove quantum supremacy within months

MIT Technology Review

Google wants NASA to help it prove quantum supremacy within a matter of months, according to a Space Act Agreement obtained by MIT Technology Review. Quantum supremacy is the idea, so far undemonstrated, that a sufficiently powerful quantum computer will be able to complete certain mathematical calculations that classical supercomputers cannot. Proving it would be a big deal because it could kick-start a market for devices that might one day crack previously unbreakable codes, boost AI, improve weather forecasts, or model molecular interactions and financial systems in exquisite detail. The agreement, signed in July, calls on NASA to "analyze results from quantum circuits run on Google quantum processors, and ... provide comparisons with classical simulation to both support Google in validating its hardware and establish a baseline for quantum supremacy." Google confirmed to MIT Technology Review that the agreement covered its latest 72-qubit quantum chip, called Bristlecone.

Will Quantum Computing Define The Future Of AI?


Google, this week, has launched a new version of their TensorFlow framework -- TensorFlow Quantum (TFQ), which is an open-source library for prototyping quantum machine learning models. Quantum computers aren't mainstream yet; however, when they do arrive, they will need algorithms. So, TFQ will bridge that gap and will make it possible for developers/users to create hybrid AI algorithms combining both traditional and quantum computing techniques. TFQ, a smart amalgamation of TensorFlow and Cinq, will allow users to build deep learning models to run on a future quantum computer with minimal lines of Python. According to the Google AI blog post, TFQ has been designed to provide the necessary tools to bring in the techniques of quantum computing and machine learning research communities together in order to build and control natural and artificial quantum systems.