Google Aims to Make Quantum Computing Viable by 2029

Google Aims to Make Quantum Computing Viable by 2029

Google makes products for consumers and businesses, but a lot of advanced computer science goes into making those products work. The company began working with neural networks around 20 years ago, enabling many of the cool features we take for granted on the user side. Now, Google is on to its next moonshot with the Quantum AI campus, where it hopes to build a useful, error-corrected quantum computer within the next decade. Ten years might sound like a long time, but it won’t be easy to crack quantum computing.

As Google explained during its recent quantum campus unveiling, quantum mechanics is the language of the universe. Quantum bits, or qubits, can be entangled in complex superpositions of states that mirror the way real molecules work. A computer that speaks that language has the potential to complete calculations much faster than traditional binary systems, enabling detailed simulations that could accelerate the development of batteries, drug discovery, unbreakable encryption, and more.

The Quantum AI campus is currently home to several cryostats (above) that house quantum computers, cooling them to almost absolute zero. This is a bid to reduce the error rate from quantum interference and other forms of decoherence. Google said in 2019 that it attained “quantum supremacy” by running a calculation that would have been impossible with a traditional computer. While some of Google’s competitors have cast doubt on this assertion, Google’s quantum computers won’t be useful until the company can address the error rate.

Google Aims to Make Quantum Computing Viable by 2029

Error correction in classical computing relies on redundancy. You make copies of the information, and if you later find that one of those copies is in disagreement, you can correct the error. However, you can’t copy quantum information without breaking the entanglement (know as the no-cloning theorem). Google wants to circumvent this apparent limitation by building 1,000 physical qubits, which can theoretically encode a single “logical qubit.” This qubit would have perfect error correction, remaining coherent until power is removed. If that scales, Google believes it can create a quantum transistor consisting of two error-corrected logical qubits. That breakthrough could make quantum computing viable.

It’s going to take years for Google to get there. Even its ten-year program might turn out to be wildly optimistic. If it can reduce quantum errors, Google thinks it can scale up to a 1 million physical qubit system that fills a room. Presumably, that room will be at Google’s fancy new Quantum AI campus. When or if that happens is anyone’s guess.

Continue reading

New Intel Rocket Lake Details: Backwards Compatible, Xe Graphics, Cypress Cove
New Intel Rocket Lake Details: Backwards Compatible, Xe Graphics, Cypress Cove

Intel has released a bit more information about Rocket Lake and its 10nm CPU that's been back-ported to 14nm.

Chromebooks Gain Market Share as Education Goes Online
Chromebooks Gain Market Share as Education Goes Online

Chromebook sales have exploded in the pandemic, with sales up 90 percent and future growth expected. This poses some challenges to companies like Microsoft.

Ryzen 9 5950X and 5900X Review: AMD Unleashes Zen 3 Against Intel’s Last Performance Bastions
Ryzen 9 5950X and 5900X Review: AMD Unleashes Zen 3 Against Intel’s Last Performance Bastions

AMD continues its onslaught on what was once Intel's undisputed turf.

How to Build a Face Mask Detector With a Jetson Nano 2GB and AlwaysAI
How to Build a Face Mask Detector With a Jetson Nano 2GB and AlwaysAI

Nvidia continues to make AI at the edge more affordable and easier to deploy. So instead of simply running through the benchmarks to review the new Jetson Nano 2GB, I decided to tackle the DIY project of building my own face mask detector.