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Feature Article

Feature Article

Intel’s New Path to Quantum Computing

In this article in IEEE Spectrum, Jim Clarke, Intel’s Director of Quantum Hardware, speaks about Intel’s two different technological approaches to quantum computing hardware. Despite all of the hype and promises, quantum computing is still an immature technology, and the ultimate technological approach for practical systems is still to be determined.

One approach uses superconducting quantum bits, or qubits, designed to operate at temperatures as low as 0.01 K. This is similar to an approach being pursued by Google and D-Wave Systems, among others. A 49-qubit system (code-named Tangle Lake) has been packaged and tested, and is shown in the photograph as the small object with gold connectors.

The other approach is based on Si quantum dots, where the qubits are essentially single-electron transistors, and the information is encoded in the spin of the electron. These are compatible with CMOS processing, and full wafers of chips with up to 26 qubits (shown in the photograph) have been fabricated and tested. These chips still need cryogenic temperatures, but may operate at slightly warmer temperatures than the superconductor approach, up to about 1 K. They may also be more compatible with integrated semiconductor control circuitry.

Intel also has a free online simulator for small quantum systems.

Another recent article in Semiconductor Engineering provides an overview of quantum computing R&D, including contributions from IBM, Google, Microsoft, LETI, and D-Wave Systems, as well as Intel.

Technology Spotlight

Technology Spotlight

HPE Progress in Memory Driven Computing and AI

The HPE Discover Conference was held in Las Vegas, Nevada in June 2018. This video includes interviews with speakers Kirk Bresniker, HPE Chief Architect, and Beena Ammanath, HPE Global VP for AI.

Bresniker spoke about Memory-Driven Computing, a new generation of systems designing to deal with Big Data sets, and how this technology is being co-developed between HPE Labs and several potential customers. A “development sandbox” has been created in the cloud, so that customers may determine how to use this technology most effectively, with their own data sets.

Ammanath spoke about the present and future development of AI, and that it is important to distinguish between the reality and the hype. The present reality deals with what might be called narrow AI, where computer systems can learn a narrow subject area and can sometimes beat out human experts. Efforts to develop general AI, where computer systems try to duplicate general human intelligence in much broader areas, have been much less successful. Super AI, which could in principle out-compete any and all humans, should not really be a concern for the foreseeable future.

For the video interviews, see here.